Compare commits

..
Author SHA1 Message Date
forforever73andYiChen Lv 5522498343 metal : port new kernels into the split sources
Move the kernels added on master after the split (lightning indexer,
DSv4 hyper-connections, silu_back, f16 bin ops) into the corresponding
kernels/*.metal sources. Copied verbatim, no functional change.
2026-08-05 16:22:32 +08:00
Georgi GerganovandYiChen Lv db0a8ce844 ggml-metal: FWHT kernel for metal backend (#25924) 2026-08-05 16:22:32 +08:00
Georgi GerganovandYiChen Lv b2d79a7e7f metal: fuse snake activation (mul, sin, sqr, mul, add) (#25459) 2026-08-05 16:22:32 +08:00
Georgi GerganovandYiChen Lv 0b6cbb572c metal : add Q2_0 support (#25419) 2026-08-05 16:22:32 +08:00
Georgi GerganovandYiChen Lv 7649856ea2 metal : add CONV_2D_DW (depthwise convolution) support (#21565) 2026-08-05 16:22:32 +08:00
Georgi GerganovandYiChen Lv f348d51391 metal : add set_rows with src0 f16 (#25434) 2026-08-05 16:22:32 +08:00
Georgi GerganovandYiChen Lv d2112aa30e metal: add col2im_1d op (f32/f16/bf16) (#25176) 2026-08-05 16:22:32 +08:00
YiChen Lvandlvyichen ff8169ce01 metal : per-op source split + parallel compile (#24021)
* preliminary extract common header

* op source split

* split metallib into 8 libs && load in parallel

* derive kernel->library routing from functionNames

* x-macro lib list + underscore filenames, dedup QK_NL, MRC fixes

* op source split 8 to 20

* improve robustness of source fallback

* clean up

* change bool -> atomic_bool

* only prepend headers that source actually includes

* no semaphore, use GCD global queue

* dedup library compile path, fix NSError lifetime, rename gla

* relocate upstream concat/rope_back/repeat kernel changes into split files

* move ggml-common.h from common.h into dequantize.h to shrink binary size

---------

Co-authored-by: lvyichen <lvyichen@stepfun.com>
2026-08-05 16:22:32 +08:00
Aleksander GrygierandGitHub e031d95679 ui: Update vulnerable packages + cleanup Storybook config (#26607)
* chore: Upgrade Storybook

* chore: Bump package-lock

* chore: bump vitest to 4.1.10

* ui: bump fast-uri to 3.1.5

* ui: bump ip-address to 10.4.0

* ui: bump js-yaml to 4.3.1

* ui: bump immutable to 5.1.9

* ui: bump postcss to 8.5.25

* ui: bump brace-expansion to safe versions

* ui: bump sharp to 0.35.3 via override

* ui: bump body-parser to 2.3.0

* ui: bump vite to 7.3.6 and esbuild to 0.28.1

Assisted-by: Claude Sonnet

* ui: bump hono to 4.13.0

* ui: bump dompurify to 3.4.13

* ui: bump @sveltejs/kit to 2.70.2

* ui: bump @modelcontextprotocol/sdk to 1.30.0

* ui: bump valibot to 1.4.2 via override

* chore: Remove legacy setup file

* refactor: Nits cleanup
2026-08-05 08:06:37 +02:00
Evan HuusandGitHub 6ea215d171 Prefer npm ci over install for security (#26601) 2026-08-05 00:14:22 +02:00
PascalandGitHub 4308a4f035 server: decode Windows OEM output to UTF-8 in built-in tools (#26597)
a child process writes in the OEM code page, which is not UTF-8 on a
western Windows install, so accented output reaches the JSON layer as
invalid bytes and gets replaced there, silently losing the characters

run() spawns without a console, so the child never inherits the console
code page and GetOEMCP is the one that applies

decode with MB_ERR_INVALID_CHARS so a wrong code page returns the text
untouched instead of emitting replacement characters, and pass text that
already decodes as UTF-8 through so a child emitting UTF-8 is never
decoded twice

the check drops an incomplete trailing sequence before validating, since
a streamed chunk can end in the middle of a multi-byte character
2026-08-04 22:24:55 +02:00
Abhinay KrishnaandGitHub 474c92e722 mtmd: correcting duplicate empty audio chunks for short inputs (#26536)
* correcting duplicate empty audio chunks for short inputs

* tests.sh code restored
2026-08-04 22:05:56 +02:00
Oliver SimonsandGitHub a6aa6f5450 sampler : remove "full-context windows" from history-based samplers (#26524)
* Resolve -1 to 1024 instead of ctx-len for samplers

Because of backend-sampling we initialize samplers before the complete
llama_context is there. Therefore, we cannot infer the resolved context
length yet at the time we construct the samplers.

* Shared default of 64 for history-based samplers, remove context_size
2026-08-04 21:28:55 +03:00
76c956c137 gguf-split: Add option to delete split parts during merge (#26538)
* Add delete-files option to split parameters

Added a new option to delete split files during execution to free up disk space.

* Add test for delete files on merge option

* Fix tests

* Update tools/gguf-split/gguf-split.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>

* Update tools/gguf-split/gguf-split.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>

* Uncomment tests

* Improvements to address PR comments

* Fix formatting

* Fix formatting

* Rename --delete-files to --delete-splits

* Comment tests

* Move delete inside loop

* style cleanup

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
2026-08-04 21:27:47 +03:00
2f56fc3431 ui: CWD for agent (#26518)
* server : extend file_glob_search for UI pickers

* ui : add per-conversation working directory with picker

* ui : add path navigation and search scope to cwd picker

Treat path-like queries (starting with / or ~) as directory navigation
instead of glob-matching the whole query: search the parent for the last
segment, and descend into an exactly-typed directory by listing its
children. Show the effective search scope in the footer and auto-search
on open so the current directory and its siblings appear immediately.

Assisted-by: Claude

* db : persist per-call tool cwd on tool result messages

* ui : abbreviate tool paths under home with a tilde

* ui : show the per-call cwd on exec shell rows

* ui : clarify the synthetic cwd message for the model

* ui : reuse the trailing cwd row on a repeated pick

* ui : don't jump when a cwd row is injected mid-chat

* chore: Formatting

* refactor: Cleanup comments

* ui : unify working directory naming and add a synthetic-message flag

* ui : render synthetic cwd rows without a scroll jump

* ui : decouple the working directory picker into utils and sub-components

* ui : add get_info tool call block

* chore: Formatting

* refactor: Cleanup

* refactor: Cleanup

* refactor: Cleanup

* fix: UI

* server : harden file_glob_search listing (kind enum, timeout, symlink guard, absolute base)

* ui : use persisted isSynthetic flag for cwd rows, drop legacy formats

* ui : cache picker search, fail visibly on native resolve

* ui : escape glob metacharacters in picker search glob

* ui : simplify auto-scroll pin

* chore: Format

* fix: Use `SvelteMap`

* refactor: Post-review fixes

* ui: accept Windows roots in the working directory picker

recognize a drive root (C:) and a UNC share (//host/share) as path
navigation, alongside the POSIX root and ~, so a query like D:\repos
lists that directory instead of glob-matching it under the home dir

split below the root, so a bare drive resolves to its root rather than
to a drive-relative prefix

rewrite backslashes into forward slashes only when the query carries a
Windows root, since a backslash is a legal POSIX filename character

paths keep travelling with forward slashes, which is what the server
returns and what Windows accepts

---------

Co-authored-by: Pascal <admin@serveurperso.com>
2026-08-04 19:05:48 +02:00
99 changed files with 15179 additions and 12601 deletions
+4 -4
View File
@@ -2008,9 +2008,9 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
).set_sampling());
add_opt(common_arg(
{"--repeat-last-n"}, "N",
string_format("last n tokens to consider for penalize (default: %d, 0 = disabled, -1 = ctx_size)", params.sampling.penalty_last_n),
string_format("last n tokens to consider for penalize (default: %d, 0 = disabled)", params.sampling.penalty_last_n),
[](common_params & params, int value) {
if (value < -1) {
if (value < 0) {
throw std::runtime_error(string_format("error: invalid repeat-last-n = %d\n", value));
}
params.sampling.penalty_last_n = value;
@@ -2081,9 +2081,9 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
).set_sampling());
add_opt(common_arg(
{"--dry-penalty-last-n"}, "N",
string_format("set DRY penalty for the last n tokens (default: %d, 0 = disable, -1 = context size)", params.sampling.dry_penalty_last_n),
string_format("set DRY penalty for the last n tokens (default: %d, 0 = disable)", params.sampling.dry_penalty_last_n),
[](common_params & params, int value) {
if (value < -1) {
if (value < 0) {
throw std::runtime_error(string_format("error: invalid dry-penalty-last-n = %d\n", value));
}
params.sampling.dry_penalty_last_n = value;
+1 -12
View File
@@ -1302,23 +1302,12 @@ common_init_result::common_init_result(common_params & params, bool model_only)
params.sampling.logit_bias_eog.begin(), params.sampling.logit_bias_eog.end());
}
//if (params.sampling.penalty_last_n == -1) {
// LOG_TRC("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
// params.sampling.penalty_last_n = llama_n_ctx(lctx);
//}
//if (params.sampling.dry_penalty_last_n == -1) {
// LOG_TRC("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
// params.sampling.dry_penalty_last_n = llama_n_ctx(lctx);
//}
// init the backend samplers as part of the context creation
pimpl->samplers.resize(cparams.n_seq_max);
pimpl->samplers_seq_config.resize(cparams.n_seq_max);
const int32_t n_ctx = cparams.n_ctx > 0 ? (int32_t) cparams.n_ctx : llama_model_n_ctx_train(model);
for (int i = 0; i < (int) cparams.n_seq_max; ++i) {
pimpl->samplers[i].reset(common_sampler_init(model, params.sampling, n_ctx));
pimpl->samplers[i].reset(common_sampler_init(model, params.sampling));
pimpl->samplers_seq_config[i] = { i, common_sampler_get(pimpl->samplers[i].get()) };
}
+2 -2
View File
@@ -235,14 +235,14 @@ struct common_params_sampling {
float temp = 0.80f; // <= 0.0 to sample greedily, 0.0 to not output probabilities
float dynatemp_range = 0.00f; // 0.0 = disabled
float dynatemp_exponent = 1.00f; // controls how entropy maps to temperature in dynamic temperature sampler
int32_t penalty_last_n = 64; // last n tokens to penalize (0 = disable penalty, -1 = context size)
int32_t penalty_last_n = 64; // last n tokens to penalize (0 = disable penalty)
float penalty_repeat = 1.00f; // 1.0 = disabled
float penalty_freq = 0.00f; // 0.0 = disabled
float penalty_present = 0.00f; // 0.0 = disabled
float dry_multiplier = 0.0f; // 0.0 = disabled; DRY repetition penalty for tokens extending repetition:
float dry_base = 1.75f; // 0.0 = disabled; multiplier * base ^ (length of sequence before token - allowed length)
int32_t dry_allowed_length = 2; // tokens extending repetitions beyond this receive penalty
int32_t dry_penalty_last_n = -1; // how many tokens to scan for repetitions (0 = disable penalty, -1 = context size)
int32_t dry_penalty_last_n = 64; // how many tokens to scan for repetitions (0 = disable penalty)
float adaptive_target = -1.0f; // select tokens near this probability (valid range 0.0 to 1.0; negative = disabled)
float adaptive_decay = 0.90f; // EMA decay for adaptation; history ≈ 1/(1-decay) tokens (0.0 - 0.99)
int32_t mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0
+2 -7
View File
@@ -186,8 +186,7 @@ std::string common_params_sampling::print() const {
struct common_sampler * common_sampler_init(
const struct llama_model * model,
struct common_params_sampling & params,
int32_t n_ctx) {
struct common_params_sampling & params) {
if (!std::isfinite(params.penalty_repeat) ||
params.penalty_repeat <= 0.0f ||
!std::isfinite(1.0f/params.penalty_repeat)) {
@@ -199,10 +198,6 @@ struct common_sampler * common_sampler_init(
if (!std::isfinite(params.penalty_present)) {
throw std::invalid_argument("penalty_present must be finite");
}
if (params.penalty_last_n == -1) {
params.penalty_last_n = n_ctx > 0 ? n_ctx : llama_model_n_ctx_train(model);
}
const llama_vocab * vocab = llama_model_get_vocab(model);
llama_sampler_chain_params lparams = llama_sampler_chain_default_params();
@@ -355,7 +350,7 @@ struct common_sampler * common_sampler_init(
for (const auto & str : params.dry_sequence_breakers) {
c_breakers.push_back(str.c_str());
}
samplers.push_back(llama_sampler_init_dry(vocab, llama_model_n_ctx_train(model), params.dry_multiplier, params.dry_base, params.dry_allowed_length, params.dry_penalty_last_n, c_breakers.data(), c_breakers.size()));
samplers.push_back(llama_sampler_init_dry(vocab, params.dry_multiplier, params.dry_base, params.dry_allowed_length, params.dry_penalty_last_n, c_breakers.data(), c_breakers.size()));
}
break;
case COMMON_SAMPLER_TYPE_TOP_K:
+1 -2
View File
@@ -39,8 +39,7 @@ struct common_sampler;
// note: can mutate params in some cases
struct common_sampler * common_sampler_init(
const struct llama_model * model,
struct common_params_sampling & params,
int32_t n_ctx = 0);
struct common_params_sampling & params);
void common_sampler_free(struct common_sampler * gsmpl);
-3
View File
@@ -341,9 +341,6 @@ set(GGML_PUBLIC_HEADERS
include/gguf.h)
set_target_properties(ggml PROPERTIES PUBLIC_HEADER "${GGML_PUBLIC_HEADERS}")
#if (GGML_METAL)
# set_target_properties(ggml PROPERTIES RESOURCE "${CMAKE_CURRENT_SOURCE_DIR}/src/ggml-metal.metal")
#endif()
install(TARGETS ggml LIBRARY PUBLIC_HEADER)
install(TARGETS ggml-base LIBRARY)
+119 -51
View File
@@ -24,62 +24,119 @@ if (GGML_METAL_NDEBUG)
endif()
set(METALLIB_COMMON "${CMAKE_CURRENT_SOURCE_DIR}/../ggml-common.h")
set(METALLIB_KERNELS_COMMON "${CMAKE_CURRENT_SOURCE_DIR}/kernels/common.h")
set(METALLIB_KERNELS_DEQUANTIZE "${CMAKE_CURRENT_SOURCE_DIR}/kernels/dequantize.h")
set(METALLIB_KERNELS_QUANTIZE "${CMAKE_CURRENT_SOURCE_DIR}/kernels/quantize.h")
set(METALLIB_KERNEL_SOURCES
kernels/fa.metal
kernels/mul_mv.metal
kernels/mul_mm.metal
kernels/quantize.metal
kernels/softmax.metal
kernels/norm.metal
kernels/unary.metal
kernels/binbcast.metal
kernels/reduce.metal
kernels/tri.metal
kernels/ssm.metal
kernels/wkv.metal
kernels/gated_delta_net.metal
kernels/solve_tri.metal
kernels/rope.metal
kernels/conv.metal
kernels/upscale.metal
kernels/argsort.metal
kernels/pool.metal
kernels/misc.metal
)
if (GGML_METAL_EMBED_LIBRARY)
enable_language(ASM)
add_compile_definitions(GGML_METAL_EMBED_LIBRARY)
set(METALLIB_SOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal")
set(METALLIB_IMPL "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal-impl.h")
set(METALLIB_IMPL "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal-impl.h")
file(MAKE_DIRECTORY "${CMAKE_CURRENT_BINARY_DIR}/autogenerated")
# merge ggml-common.h and ggml-metal.metal into a single file
set(METALLIB_EMBED_ASM "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed.s")
set(METALLIB_SOURCE_EMBED "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed.metal")
set(METALLIB_SOURCE_EMBED_TMP "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed.metal.tmp")
set(METALLIB_EMBED_ASM_FILES "")
foreach(src ${METALLIB_KERNEL_SOURCES})
get_filename_component(kind ${src} NAME_WE)
# symbol names must be valid C identifiers ('-' is not allowed)
string(REPLACE "-" "_" kind_sym ${kind})
add_custom_command(
OUTPUT "${METALLIB_EMBED_ASM}"
COMMAND echo "Embedding Metal library"
COMMAND sed -e "/__embed_ggml-common.h__/r ${METALLIB_COMMON}" -e "/__embed_ggml-common.h__/d" < "${METALLIB_SOURCE}" > "${METALLIB_SOURCE_EMBED_TMP}"
COMMAND sed -e "/\#include \"ggml-metal-impl.h\"/r ${METALLIB_IMPL}" -e "/\#include \"ggml-metal-impl.h\"/d" < "${METALLIB_SOURCE_EMBED_TMP}" > "${METALLIB_SOURCE_EMBED}"
COMMAND echo ".section __DATA,__ggml_metallib" > "${METALLIB_EMBED_ASM}"
COMMAND echo ".globl _ggml_metallib_start" >> "${METALLIB_EMBED_ASM}"
COMMAND echo "_ggml_metallib_start:" >> "${METALLIB_EMBED_ASM}"
COMMAND echo .incbin "\"${METALLIB_SOURCE_EMBED}\"" >> "${METALLIB_EMBED_ASM}"
COMMAND echo ".globl _ggml_metallib_end" >> "${METALLIB_EMBED_ASM}"
COMMAND echo "_ggml_metallib_end:" >> "${METALLIB_EMBED_ASM}"
DEPENDS ../ggml-common.h ggml-metal.metal ggml-metal-impl.h
COMMENT "Generate assembly for embedded Metal library"
VERBATIM
)
set(SRC "${CMAKE_CURRENT_SOURCE_DIR}/kernels/${kind}.metal")
set(EMBED "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed-${kind}.metal")
set(ASM "${CMAKE_CURRENT_BINARY_DIR}/autogenerated/ggml-metal-embed-${kind}.s")
target_sources(ggml-metal PRIVATE "${METALLIB_EMBED_ASM}")
# only prepend headers that this source actually includes
set(HEADERS_FOR_SRC ${METALLIB_KERNELS_COMMON})
file(STRINGS ${SRC} _has_dequantize REGEX "#include \"dequantize\\.h\"")
file(STRINGS ${SRC} _has_quantize REGEX "#include \"quantize\\.h\"")
if(_has_dequantize)
list(APPEND HEADERS_FOR_SRC ${METALLIB_KERNELS_DEQUANTIZE})
endif()
if(_has_quantize)
list(APPEND HEADERS_FOR_SRC ${METALLIB_KERNELS_QUANTIZE})
endif()
add_custom_command(
OUTPUT "${ASM}"
# Step 1: concatenate shared headers + this kernel source
COMMAND cat ${HEADERS_FOR_SRC} ${SRC} > "${EMBED}.tmp1"
# Step 2: remove internal #include and #pragma once
COMMAND sed -e "/\#include \"common.h\"/d" -e "/\#include \"dequantize.h\"/d" -e "/\#include \"quantize.h\"/d" -e "/\#pragma once/d" < "${EMBED}.tmp1" > "${EMBED}.tmp2"
# Step 3: inline ggml-common.h (replacing __embed_ggml-common.h__ sentinel)
COMMAND sed -e "/__embed_ggml-common.h__/r ${METALLIB_COMMON}" -e "/__embed_ggml-common.h__/d" < "${EMBED}.tmp2" > "${EMBED}.tmp3"
# Step 4: inline ggml-metal-impl.h
COMMAND sed -e "/\#include \"ggml-metal-impl.h\"/r ${METALLIB_IMPL}" -e "/\#include \"ggml-metal-impl.h\"/d" < "${EMBED}.tmp3" > "${EMBED}"
# Step 5: emit an asm chunk with kind-specific start/end symbols
# note: '-' is illegal in C symbols, so we use kind_sym; the macOS
# section name is limited to 16 chars so we keep it shared
# across kinds (__ggml_metallib) and only vary the global symbols.
COMMAND echo ".section __DATA,__ggml_metallib" > "${ASM}"
COMMAND echo ".globl _ggml_metallib_${kind_sym}_start" >> "${ASM}"
COMMAND echo "_ggml_metallib_${kind_sym}_start:" >> "${ASM}"
COMMAND echo .incbin "\"${EMBED}\"" >> "${ASM}"
COMMAND echo ".globl _ggml_metallib_${kind_sym}_end" >> "${ASM}"
COMMAND echo "_ggml_metallib_${kind_sym}_end:" >> "${ASM}"
DEPENDS ../ggml-common.h ggml-metal-impl.h
kernels/common.h kernels/dequantize.h kernels/quantize.h
kernels/${kind}.metal
COMMENT "Generate embedded Metal library for ${kind}"
VERBATIM
)
list(APPEND METALLIB_EMBED_ASM_FILES "${ASM}")
endforeach()
target_sources(ggml-metal PRIVATE ${METALLIB_EMBED_ASM_FILES})
else()
# copy metal files to bin directory
# copy header files to bin directory
configure_file(../ggml-common.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-common.h COPYONLY)
configure_file(ggml-metal.metal ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal COPYONLY)
configure_file(ggml-metal-impl.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal-impl.h COPYONLY)
file(MAKE_DIRECTORY "${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels")
configure_file(kernels/common.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels/common.h COPYONLY)
configure_file(kernels/dequantize.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels/dequantize.h COPYONLY)
configure_file(kernels/quantize.h ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels/quantize.h COPYONLY)
foreach(src ${METALLIB_KERNEL_SOURCES})
configure_file(${src} ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${src} COPYONLY)
endforeach()
if (GGML_METAL_SHADER_DEBUG)
# custom command to do the following:
# xcrun -sdk macosx metal -fno-fast-math -c ggml-metal.metal -o ggml-metal.air
# xcrun -sdk macosx metallib ggml-metal.air -o default.metallib
#
# note: this is the only way I found to disable fast-math in Metal. it's ugly, but at least it works
# disabling fast math is needed in order to pass tests/test-backend-ops
# note: disabling fast math is needed in order to pass tests/test-backend-ops
# note: adding -fno-inline fixes the tests when using MTL_SHADER_VALIDATION=1
# note: unfortunately, we have to call it default.metallib instead of ggml.metallib
# ref: https://github.com/ggml-org/whisper.cpp/issues/1720
# note: adding -g causes segmentation fault during compile
#set(XC_FLAGS -fno-fast-math -fno-inline -g)
set(XC_FLAGS -fno-fast-math -fno-inline)
else()
set(XC_FLAGS -O3)
endif()
# Append macOS metal versioning flags
if (GGML_METAL_MACOSX_VERSION_MIN)
message(STATUS "Adding -mmacosx-version-min=${GGML_METAL_MACOSX_VERSION_MIN} flag to metal compilation")
list (APPEND XC_FLAGS -mmacosx-version-min=${GGML_METAL_MACOSX_VERSION_MIN})
@@ -90,35 +147,46 @@ else()
list (APPEND XC_FLAGS -std=${GGML_METAL_STD})
endif()
# Compile each kernel source to .air, then link into default.metallib
set(AIR_FILES "")
foreach(src ${METALLIB_KERNEL_SOURCES})
get_filename_component(name ${src} NAME_WE)
set(AIR "${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${name}.air")
list(APPEND AIR_FILES ${AIR})
add_custom_command(
OUTPUT ${AIR}
COMMAND xcrun -sdk macosx metal ${XC_FLAGS} -I ${CMAKE_RUNTIME_OUTPUT_DIRECTORY} -c ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${src} -o ${AIR}
DEPENDS ${src} kernels/common.h kernels/dequantize.h kernels/quantize.h ${METALLIB_COMMON} ggml-metal-impl.h
COMMENT "Compiling ${src}"
VERBATIM
)
endforeach()
add_custom_command(
OUTPUT ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
COMMAND xcrun -sdk macosx metal ${XC_FLAGS} -c ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal -o - |
xcrun -sdk macosx metallib - -o ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
COMMAND xcrun -sdk macosx metallib ${AIR_FILES} -o ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-common.h
COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal.metal
DEPENDS ggml-metal.metal ${METALLIB_COMMON}
COMMENT "Compiling Metal kernels"
)
COMMAND rm -f ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/ggml-metal-impl.h
COMMAND rm -rf ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/kernels
DEPENDS ${AIR_FILES}
COMMENT "Linking Metal kernels into default.metallib"
)
# FIXME: only add to the ggml-metal target?
add_custom_target(
ggml-metal-lib ALL
DEPENDS ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
)
)
endif() # GGML_METAL_EMBED_LIBRARY
if (NOT GGML_METAL_EMBED_LIBRARY)
install(
FILES src/ggml-metal/ggml-metal.metal
PERMISSIONS
OWNER_READ
OWNER_WRITE
GROUP_READ
WORLD_READ
DESTINATION ${CMAKE_INSTALL_BINDIR})
DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/kernels/
DESTINATION ${CMAKE_INSTALL_BINDIR}/kernels
FILES_MATCHING PATTERN "*.metal" PATTERN "*.h"
)
install(
FILES ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
DESTINATION ${CMAKE_INSTALL_BINDIR}
)
install(
FILES ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/default.metallib
DESTINATION ${CMAKE_INSTALL_BINDIR}
)
endif()
+423 -128
View File
@@ -95,8 +95,63 @@ int ggml_metal_pipeline_max_theads_per_threadgroup(struct ggml_metal_pipeline_wi
return pipeline.pipeline->obj.maxTotalThreadsPerThreadgroup;
}
//
// MTLLibrary collection (one library per op-source, compiled separately)
//
// Single source of truth for the per-kind metal libraries. The order here
// defines the enum values and every per-kind table below, so adding a library
// is a one-line change here (plus adding its source to CMakeLists.txt).
// X(suffix, name): name is both the kernels/<name>.metal basename and the
// ggml_metallib_<name>_{start,end} embed-symbol stem.
#define GGML_METAL_LIBS \
X(FA, fa) \
X(MUL_MV, mul_mv) \
X(MUL_MM, mul_mm) \
X(QUANTIZE, quantize) \
X(SOFTMAX, softmax) \
X(NORM, norm) \
X(UNARY, unary) \
X(BINBCAST, binbcast) \
X(REDUCE, reduce) \
X(TRI, tri) \
X(SSM, ssm) \
X(WKV, wkv) \
X(GATED_DELTA_NET, gated_delta_net)\
X(SOLVE_TRI, solve_tri) \
X(ROPE, rope) \
X(CONV, conv) \
X(UPSCALE, upscale) \
X(ARGSORT, argsort) \
X(POOL, pool) \
X(MISC, misc)
enum ggml_metal_lib_kind {
#define X(e, s) GGML_METAL_LIB_##e,
GGML_METAL_LIBS
#undef X
GGML_METAL_LIB_COUNT,
};
static const char * const k_lib_names[GGML_METAL_LIB_COUNT] = {
#define X(e, s) [GGML_METAL_LIB_##e] = #s,
GGML_METAL_LIBS
#undef X
};
struct ggml_metal_library {
id<MTLLibrary> obj;
// Per-kind compiled libraries. When single_library is true, the whole library
// (e.g. a pre-compiled default.metallib or a from-source build) lives at
// objs[0] and the remaining slots are nil.
id<MTLLibrary> objs[GGML_METAL_LIB_COUNT];
bool single_library; // true: combined library at objs[0]; false: per-kind libs in objs[*]
// Routing table: kernel function name -> objs[] index, populated from each
// compiled library's -[MTLLibrary functionNames]. The actual compiled
// libraries are the single source of truth for which library owns a kernel,
// so adding kernels later requires no manual routing maintenance.
// nil in single_library mode (everything resolves to objs[0]).
NSMutableDictionary<NSString *, NSNumber *> * fn_to_lib;
ggml_metal_device_t dev;
ggml_metal_pipelines_t pipelines; // cache of compiled pipelines
@@ -104,160 +159,376 @@ struct ggml_metal_library {
NSLock * lock;
};
ggml_metal_library_t ggml_metal_library_init(ggml_metal_device_t dev) {
id<MTLLibrary> library = nil;
id<MTLDevice> device = ggml_metal_device_get_obj(dev);
// Build the fn_to_lib routing table by querying each compiled library's public
// function names. Call once after all per-kind libraries have been compiled.
static void ggml_metal_library_build_index(ggml_metal_library_t lib) {
@autoreleasepool {
NSMutableDictionary<NSString *, NSNumber *> * index = [[NSMutableDictionary alloc] init];
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
for (NSString * fname in [lib->objs[kind] functionNames]) {
index[fname] = @(kind);
}
}
lib->fn_to_lib = index;
}
}
// load library
//
// - first check if the library is embedded
// - then check if the library is in the bundle
// - if not found, load the source and compile it
// - if that fails, return NULL
//
// TODO: move to a function
{
const int64_t t_start = ggml_time_us();
// Parse a `#include "name"` line. Returns the quoted name in *include_name on
// success. Whitespace-tolerant; ignores `#include <...>` (system headers).
static bool ggml_metal_library_parse_quoted_include(NSString * line, NSString ** include_name) {
NSScanner * scanner = [NSScanner scannerWithString:line];
scanner.charactersToBeSkipped = [NSCharacterSet whitespaceCharacterSet];
NSError * error = nil;
NSString * src = nil;
if (![scanner scanString:@"#" intoString:NULL] ||
![scanner scanString:@"include" intoString:NULL] ||
![scanner scanString:@"\"" intoString:NULL]) {
return false;
}
#if GGML_METAL_EMBED_LIBRARY
GGML_LOG_INFO("%s: using embedded metal library\n", __func__);
NSString * name = nil;
if (![scanner scanUpToString:@"\"" intoString:&name]) {
return false;
}
extern const char ggml_metallib_start[];
extern const char ggml_metallib_end[];
if (include_name) {
*include_name = name;
}
return true;
}
src = [[NSString alloc] initWithBytes:ggml_metallib_start length:(ggml_metallib_end-ggml_metallib_start) encoding:NSUTF8StringEncoding];
#else
// Recursively inline `#include "name"` directives. System includes (<...>),
// `#if/#else/#endif`, and other preprocessor lines are passed through to the
// Metal compiler unchanged. `#pragma once` is dropped since `seen` already
// guards against double-inclusion.
static bool ggml_metal_library_flatten_file(NSMutableString * dst, NSString * path,
NSArray<NSString *> * search_paths,
NSMutableSet<NSString *> * seen, NSError ** error) {
NSString * key = [path stringByStandardizingPath];
if ([seen containsObject:key]) {
return true;
}
[seen addObject:key];
#ifdef SWIFT_PACKAGE
NSBundle * bundle = SWIFTPM_MODULE_BUNDLE;
#else
NSBundle * bundle = [NSBundle bundleForClass:[GGMLMetalClass class]];
#endif
NSString * src = [NSString stringWithContentsOfFile:path encoding:NSUTF8StringEncoding error:error];
if (!src) {
return false;
}
NSString * path_lib = [bundle pathForResource:@"default" ofType:@"metallib"];
if (path_lib == nil) {
// Try to find the resource in the directory where the current binary located.
NSString * bin_cur = [[NSProcessInfo processInfo] arguments][0];
NSString * bin_dir = [bin_cur stringByDeletingLastPathComponent];
NSFileManager * fm = [NSFileManager defaultManager];
for (NSString * line in [src componentsSeparatedByString:@"\n"]) {
NSString * trimmed = [line stringByTrimmingCharactersInSet:[NSCharacterSet whitespaceCharacterSet]];
if ([trimmed isEqualToString:@"#pragma once"]) {
continue;
}
NSString * path_lib_default = [NSString pathWithComponents:@[bin_dir, @"default.metallib"]];
if ([[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) {
GGML_LOG_INFO("%s: found '%s'\n", __func__, [path_lib_default UTF8String]);
NSDictionary * atts = [[NSFileManager defaultManager] attributesOfItemAtPath:path_lib_default error:&error];
if (atts && atts[NSFileType] == NSFileTypeSymbolicLink) {
// Optionally, if this is a symlink, try to resolve it.
path_lib_default = [[NSFileManager defaultManager] destinationOfSymbolicLinkAtPath:path_lib_default error:&error];
if (path_lib_default && [path_lib_default length] > 0 && ![[path_lib_default substringToIndex:1] isEqualToString:@"/"]) {
// It is a relative path, adding the binary directory as directory prefix.
path_lib_default = [NSString pathWithComponents:@[bin_dir, path_lib_default]];
}
if (!path_lib_default || ![[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) {
// Link to the resource could not be resolved.
path_lib_default = nil;
} else {
GGML_LOG_INFO("%s: symlink resolved '%s'\n", __func__, [path_lib_default UTF8String]);
}
NSString * include_name = nil;
if (ggml_metal_library_parse_quoted_include(line, &include_name)) {
NSString * resolved = nil;
for (NSString * dir in search_paths) {
NSString * candidate = [dir stringByAppendingPathComponent:include_name];
if ([fm isReadableFileAtPath:candidate]) {
resolved = candidate;
break;
}
} else {
// The resource couldn't be found in the binary's directory.
path_lib_default = nil;
}
path_lib = path_lib_default;
if (!resolved) {
if (error) {
NSString * msg = [NSString stringWithFormat:@"could not resolve include \"%@\" from '%@'", include_name, path];
*error = [NSError errorWithDomain:@"ggml-metal-source-flatten" code:1
userInfo:@{NSLocalizedDescriptionKey: msg}];
}
return false;
}
if (!ggml_metal_library_flatten_file(dst, resolved, search_paths, seen, error)) {
return false;
}
continue;
}
if (path_lib != nil) {
// pre-compiled library found
NSURL * libURL = [NSURL fileURLWithPath:path_lib];
GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_lib UTF8String]);
[dst appendString:line];
[dst appendString:@"\n"];
}
library = [device newLibraryWithURL:libURL error:&error];
if (error) {
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
return nil;
}
} else {
GGML_LOG_INFO("%s: default.metallib not found, loading from source\n", __func__);
return true;
}
NSString * path_source;
NSString * path_resource = [[NSProcessInfo processInfo].environment objectForKey:@"GGML_METAL_PATH_RESOURCES"];
static NSString * ggml_metal_library_flatten_source(NSString * path_source, NSError ** error) {
// Search paths cover both runtime layout (build/bin/kernels + build/bin)
// and source-tree layout (ggml/src/ggml-metal/kernels + ggml/src/ggml-metal + ggml/src).
NSString * path_kernels = [path_source stringByDeletingLastPathComponent];
NSString * path_base = [path_kernels stringByDeletingLastPathComponent];
NSArray<NSString *> * search_paths = @[
path_kernels,
path_base,
[path_base stringByDeletingLastPathComponent],
];
GGML_LOG_INFO("%s: GGML_METAL_PATH_RESOURCES = %s\n", __func__, path_resource ? [path_resource UTF8String] : "nil");
NSMutableString * src = [[NSMutableString alloc] init];
NSMutableSet<NSString *> * seen = [NSMutableSet set];
if (path_resource) {
path_source = [path_resource stringByAppendingPathComponent:@"ggml-metal.metal"];
} else {
path_source = [bundle pathForResource:@"ggml-metal" ofType:@"metal"];
if (!ggml_metal_library_flatten_file(src, path_source, search_paths, seen, error)) {
[src release];
return nil;
}
return src;
}
// Compile all per-kind libraries in parallel. `source_for_kind` returns the MSL
// source for a kind (the helper takes ownership and releases it), or nil with
// *err set on failure. On success the objs[] slots are populated and the routing
// index is built; on any failure every error is logged and false is returned
// (the caller is responsible for freeing `res`).
static bool ggml_metal_library_compile_all(
ggml_metal_library_t res,
id<MTLDevice> device,
NSDictionary * prep,
NSString * (^source_for_kind)(int kind, NSError ** err),
const char * origin) {
const int64_t t_start = ggml_time_us();
int64_t * t_per_lib = calloc(GGML_METAL_LIB_COUNT, sizeof(int64_t));
NSError ** err_per_lib = calloc(GGML_METAL_LIB_COUNT, sizeof(NSError *));
__block atomic_bool any_failure = false;
dispatch_group_t group = dispatch_group_create();
dispatch_queue_t queue = dispatch_get_global_queue(QOS_CLASS_USER_INITIATED, 0);
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
dispatch_group_async(group, queue, ^{
const int64_t t0 = ggml_time_us();
NSError * error = nil;
NSString * src = source_for_kind(kind, &error);
if (!src) {
err_per_lib[kind] = [error retain];
atomic_store(&any_failure, true);
return;
}
if (path_source == nil) {
GGML_LOG_WARN("%s: error: could not use bundle path to find ggml-metal.metal, falling back to trying cwd\n", __func__);
path_source = @"ggml-metal.metal";
}
id<MTLLibrary> lib = nil;
GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_source UTF8String]);
src = [NSString stringWithContentsOfFile:path_source encoding:NSUTF8StringEncoding error:&error];
if (error) {
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
return nil;
}
}
#endif
if (!library) {
@autoreleasepool {
// dictionary of preprocessor macros
NSMutableDictionary * prep = [NSMutableDictionary dictionary];
if (ggml_metal_device_get_props(dev)->has_bfloat) {
[prep setObject:@"1" forKey:@"GGML_METAL_HAS_BF16"];
}
if (ggml_metal_device_get_props(dev)->has_tensor) {
[prep setObject:@"1" forKey:@"GGML_METAL_HAS_TENSOR"];
}
#if GGML_METAL_EMBED_LIBRARY
[prep setObject:@"1" forKey:@"GGML_METAL_EMBED_LIBRARY"];
#endif
MTLCompileOptions * options = [MTLCompileOptions new];
options.preprocessorMacros = prep;
//[options setFastMathEnabled:false];
lib = [device newLibraryWithSource:src options:options error:&error];
library = [device newLibraryWithSource:src options:options error:&error];
if (error) {
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
return nil;
}
#if !__has_feature(objc_arc)
[options release];
#endif
// retain the error before the autorelease pool drains it
if (!lib) {
err_per_lib[kind] = [error retain];
}
}
[src release];
t_per_lib[kind] = ggml_time_us() - t0;
if (!lib) {
atomic_store(&any_failure, true);
return;
}
res->objs[kind] = lib;
});
}
dispatch_group_wait(group, DISPATCH_TIME_FOREVER);
dispatch_release(group);
const bool ok = !atomic_load(&any_failure);
if (ok) {
const int64_t t_total = ggml_time_us() - t_start;
int64_t t_max = 0;
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
GGML_LOG_DEBUG("%s: compiled '%s' library in %.3f sec\n",
__func__, k_lib_names[kind], t_per_lib[kind] / 1e6);
if (t_per_lib[kind] > t_max) t_max = t_per_lib[kind];
}
GGML_LOG_INFO("%s: loaded %d libraries from %s in %.3f sec (max single = %.3f sec)\n",
__func__, GGML_METAL_LIB_COUNT, origin, t_total / 1e6, t_max / 1e6);
ggml_metal_library_build_index(res);
} else {
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
if (err_per_lib[kind]) {
GGML_LOG_ERROR("%s: failed to build '%s' library: %s\n", __func__,
k_lib_names[kind], [[err_per_lib[kind] description] UTF8String]);
[err_per_lib[kind] release];
}
}
#if GGML_METAL_EMBED_LIBRARY
[src release];
#endif // GGML_METAL_EMBED_LIBRARY
GGML_LOG_INFO("%s: loaded in %.3f sec\n", __func__, (ggml_time_us() - t_start) / 1e6);
}
ggml_metal_library_t res = calloc(1, sizeof(struct ggml_metal_library));
free(err_per_lib);
free(t_per_lib);
res->obj = library;
return ok;
}
ggml_metal_library_t ggml_metal_library_init(ggml_metal_device_t dev) {
id<MTLDevice> device = ggml_metal_device_get_obj(dev);
ggml_metal_library_t res = calloc(1, sizeof(struct ggml_metal_library));
res->dev = dev;
res->pipelines = ggml_metal_pipelines_init();
res->lock = [NSLock new];
// shared MTLCompileOptions preprocessor macros (matches the build-time defines)
NSMutableDictionary * prep = [NSMutableDictionary dictionary];
if (ggml_metal_device_get_props(dev)->has_bfloat) {
[prep setObject:@"1" forKey:@"GGML_METAL_HAS_BF16"];
}
if (ggml_metal_device_get_props(dev)->has_tensor) {
[prep setObject:@"1" forKey:@"GGML_METAL_HAS_TENSOR"];
}
#if GGML_METAL_EMBED_LIBRARY
[prep setObject:@"1" forKey:@"GGML_METAL_EMBED_LIBRARY"];
#endif
#if GGML_METAL_EMBED_LIBRARY
GGML_LOG_INFO("%s: using embedded metal library\n", __func__);
// start/end symbols emitted by CMake (see CMakeLists.txt), one pair per kind
#define X(e, s) extern const char ggml_metallib_##s##_start[]; extern const char ggml_metallib_##s##_end[];
GGML_METAL_LIBS
#undef X
static const char * const lib_start[GGML_METAL_LIB_COUNT] = {
#define X(e, s) [GGML_METAL_LIB_##e] = ggml_metallib_##s##_start,
GGML_METAL_LIBS
#undef X
};
static const char * const lib_end[GGML_METAL_LIB_COUNT] = {
#define X(e, s) [GGML_METAL_LIB_##e] = ggml_metallib_##s##_end,
GGML_METAL_LIBS
#undef X
};
const bool ok = ggml_metal_library_compile_all(res, device, prep,
^NSString * (int kind, NSError ** err) {
(void) err;
return [[NSString alloc] initWithBytes:lib_start[kind]
length:(lib_end[kind] - lib_start[kind])
encoding:NSUTF8StringEncoding];
}, "embedded data");
if (!ok) {
ggml_metal_library_free(res);
return NULL;
}
return res;
#else
#ifdef SWIFT_PACKAGE
NSBundle * bundle = SWIFTPM_MODULE_BUNDLE;
#else
NSBundle * bundle = [NSBundle bundleForClass:[GGMLMetalClass class]];
#endif
const int64_t t_start = ggml_time_us();
NSError * error = nil;
NSString * path_lib = [bundle pathForResource:@"default" ofType:@"metallib"];
if (path_lib == nil) {
// Try to find the resource in the directory where the current binary located.
NSString * bin_cur = [[NSProcessInfo processInfo] arguments][0];
NSString * bin_dir = [bin_cur stringByDeletingLastPathComponent];
NSString * path_lib_default = [NSString pathWithComponents:@[bin_dir, @"default.metallib"]];
if ([[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) {
GGML_LOG_INFO("%s: found '%s'\n", __func__, [path_lib_default UTF8String]);
NSDictionary * atts = [[NSFileManager defaultManager] attributesOfItemAtPath:path_lib_default error:&error];
if (atts && atts[NSFileType] == NSFileTypeSymbolicLink) {
// Optionally, if this is a symlink, try to resolve it.
path_lib_default = [[NSFileManager defaultManager] destinationOfSymbolicLinkAtPath:path_lib_default error:&error];
if (path_lib_default && [path_lib_default length] > 0 && ![[path_lib_default substringToIndex:1] isEqualToString:@"/"]) {
// It is a relative path, adding the binary directory as directory prefix.
path_lib_default = [NSString pathWithComponents:@[bin_dir, path_lib_default]];
}
if (!path_lib_default || ![[NSFileManager defaultManager] isReadableFileAtPath:path_lib_default]) {
// Link to the resource could not be resolved.
path_lib_default = nil;
} else {
GGML_LOG_INFO("%s: symlink resolved '%s'\n", __func__, [path_lib_default UTF8String]);
}
}
} else {
// The resource couldn't be found in the binary's directory.
path_lib_default = nil;
}
path_lib = path_lib_default;
}
if (path_lib != nil) {
// pre-compiled library found: a single combined default.metallib
NSURL * libURL = [NSURL fileURLWithPath:path_lib];
GGML_LOG_INFO("%s: loading '%s'\n", __func__, [path_lib UTF8String]);
res->objs[0] = [device newLibraryWithURL:libURL error:&error];
res->single_library = true;
if (!res->objs[0]) {
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
ggml_metal_library_free(res);
return NULL;
}
GGML_LOG_INFO("%s: loaded in %.3f sec\n", __func__, (ggml_time_us() - t_start) / 1e6);
return res;
}
// no pre-compiled metallib: fall back to compiling each kernel source separately
GGML_LOG_INFO("%s: default.metallib not found, loading kernel sources\n", __func__);
NSString * path_resource = [[NSProcessInfo processInfo].environment objectForKey:@"GGML_METAL_PATH_RESOURCES"];
if (path_resource) {
GGML_LOG_INFO("%s: GGML_METAL_PATH_RESOURCES = %s\n", __func__, [path_resource UTF8String]);
}
// resolve each kind's source path up front (file lookup/logging stays on the calling thread)
NSString ** path_per_kind = calloc(GGML_METAL_LIB_COUNT, sizeof(NSString *));
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
NSString * rel = [NSString stringWithFormat:@"kernels/%s.metal", k_lib_names[kind]];
NSString * path_source = nil;
if (path_resource) {
path_source = [path_resource stringByAppendingPathComponent:rel];
} else {
NSString * stem = [NSString stringWithFormat:@"kernels/%s", k_lib_names[kind]];
path_source = [bundle pathForResource:stem ofType:@"metal"];
}
if (path_source == nil || ![[NSFileManager defaultManager] isReadableFileAtPath:path_source]) {
GGML_LOG_WARN("%s: could not locate %s in bundle, falling back to cwd\n", __func__, [rel UTF8String]);
path_source = rel;
}
GGML_LOG_DEBUG("%s: loading '%s'\n", __func__, [path_source UTF8String]);
path_per_kind[kind] = [path_source retain];
}
const bool ok = ggml_metal_library_compile_all(res, device, prep,
^NSString * (int kind, NSError ** err) {
return ggml_metal_library_flatten_source(path_per_kind[kind], err);
}, "source");
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
[path_per_kind[kind] release];
}
free(path_per_kind);
if (!ok) {
ggml_metal_library_free(res);
return NULL;
}
return res;
#endif
}
ggml_metal_library_t ggml_metal_library_init_from_source(ggml_metal_device_t dev, const char * source, bool verbose) {
@@ -319,10 +590,11 @@ ggml_metal_library_t ggml_metal_library_init_from_source(ggml_metal_device_t dev
return NULL;
}
res->obj = library;
res->dev = dev;
res->pipelines = ggml_metal_pipelines_init();
res->lock = [NSLock new];
res->objs[0] = library;
res->single_library = true;
res->dev = dev;
res->pipelines = ggml_metal_pipelines_init();
res->lock = [NSLock new];
return res;
}
@@ -332,8 +604,14 @@ void ggml_metal_library_free(ggml_metal_library_t lib) {
return;
}
if (lib->obj) {
[lib->obj release];
for (int kind = 0; kind < GGML_METAL_LIB_COUNT; ++kind) {
if (lib->objs[kind]) {
[lib->objs[kind] release];
}
}
if (lib->fn_to_lib) {
[lib->fn_to_lib release];
}
ggml_metal_pipelines_free(lib->pipelines);
@@ -394,11 +672,28 @@ struct ggml_metal_pipeline_with_params ggml_metal_library_compile_pipeline(ggml_
GGML_LOG_DEBUG("%s: compiling pipeline: base = '%s', name = '%s'\n", __func__, base, name);
// route to the library that actually defines this kernel; fn_to_lib is
// built from -[MTLLibrary functionNames] so it's always in sync
int lib_idx = 0;
if (!lib->single_library) {
NSNumber * idx = lib->fn_to_lib[base_func];
if (!idx) {
[lib->lock unlock];
GGML_LOG_ERROR("%s: kernel not found in any metal library: base = '%s', name = '%s'\n", __func__, base, name);
return res;
}
lib_idx = [idx intValue];
}
id<MTLLibrary> mtl_lib = lib->objs[lib_idx];
id<MTLFunction> mtl_function;
if (!cv) {
mtl_function = [lib->obj newFunctionWithName:base_func];
mtl_function = [mtl_lib newFunctionWithName:base_func];
} else {
mtl_function = [lib->obj newFunctionWithName:base_func constantValues:cv->obj error:&error];
mtl_function = [mtl_lib newFunctionWithName:base_func constantValues:cv->obj error:&error];
}
if (!mtl_function) {
[lib->lock unlock];
File diff suppressed because it is too large Load Diff
+232
View File
@@ -0,0 +1,232 @@
#include "common.h"
// bitonic sort implementation following the CUDA kernels as reference
typedef void (argsort_t)(
constant ggml_metal_kargs_argsort & args,
device const char * src0,
device int32_t * dst,
threadgroup int32_t * shmem_i32 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]);
template<ggml_sort_order order>
kernel void kernel_argsort_f32_i32(
constant ggml_metal_kargs_argsort & args,
device const char * src0,
device int32_t * dst,
threadgroup int32_t * shmem_i32 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
// bitonic sort
const int col = tpitg[0];
const int ib = tgpig[0] / args.ne01;
const int i00 = ib*ntg.x;
const int i01 = tgpig[0] % args.ne01;
const int i02 = tgpig[1];
const int i03 = tgpig[2];
device const float * src0_row = (device const float *) (src0 + args.nb01*i01 + args.nb02*i02 + args.nb03*i03);
// initialize indices
shmem_i32[col] = i00 + col;
threadgroup_barrier(mem_flags::mem_threadgroup);
for (int k = 2; k <= ntg.x; k *= 2) {
for (int j = k / 2; j > 0; j /= 2) {
int ixj = col ^ j;
if (ixj > col) {
if ((col & k) == 0) {
if (shmem_i32[col] >= args.ne00 ||
(shmem_i32[ixj] < args.ne00 && (order == GGML_SORT_ORDER_ASC ?
src0_row[shmem_i32[col]] > src0_row[shmem_i32[ixj]] :
src0_row[shmem_i32[col]] < src0_row[shmem_i32[ixj]]))
) {
SWAP(shmem_i32[col], shmem_i32[ixj]);
}
} else {
if (shmem_i32[ixj] >= args.ne00 ||
(shmem_i32[col] < args.ne00 && (order == GGML_SORT_ORDER_ASC ?
src0_row[shmem_i32[col]] < src0_row[shmem_i32[ixj]] :
src0_row[shmem_i32[col]] > src0_row[shmem_i32[ixj]]))
) {
SWAP(shmem_i32[col], shmem_i32[ixj]);
}
}
}
threadgroup_barrier(mem_flags::mem_threadgroup);
}
}
const int64_t i0 = ib*args.top_k;
// copy the result to dst without the padding
if (i0 + col < args.ne0 && col < args.top_k) {
dst += i0 + args.ne0*i01 + args.ne0*args.ne1*i02 + args.ne0*args.ne1*args.ne2*i03;
dst[col] = shmem_i32[col];
}
}
template [[host_name("kernel_argsort_f32_i32_asc")]] kernel argsort_t kernel_argsort_f32_i32<GGML_SORT_ORDER_ASC>;
template [[host_name("kernel_argsort_f32_i32_desc")]] kernel argsort_t kernel_argsort_f32_i32<GGML_SORT_ORDER_DESC>;
typedef void (argsort_merge_t)(
constant ggml_metal_kargs_argsort_merge & args,
device const char * src0,
device const int32_t * tmp,
device int32_t * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]);
template<ggml_sort_order order>
kernel void kernel_argsort_merge_f32_i32(
constant ggml_metal_kargs_argsort_merge & args,
device const char * src0,
device const int32_t * tmp,
device int32_t * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int im = tgpig[0] / args.ne01;
const int i01 = tgpig[0] % args.ne01;
const int i02 = tgpig[1];
const int i03 = tgpig[2];
const int start = im * (2 * args.len);
const int len0 = MIN(args.len, MAX(0, args.ne0 - (int)(start)));
const int len1 = MIN(args.len, MAX(0, args.ne0 - (int)(start + args.len)));
const int total = len0 + len1;
device const int32_t * tmp0 = tmp + start
+ i01*args.ne0
+ i02*args.ne0*args.ne01
+ i03*args.ne0*args.ne01*args.ne02;
device const int32_t * tmp1 = tmp0 + args.len;
dst += start
+ i01*args.top_k
+ i02*args.top_k*args.ne01
+ i03*args.top_k*args.ne01*args.ne02;
device const float * src0_row = (device const float *)(src0
+ args.nb01*i01
+ args.nb02*i02
+ args.nb03*i03);
if (total == 0) {
return;
}
const int chunk = (total + ntg.x - 1) / ntg.x;
const int k0 = tpitg.x * chunk;
const int k1 = MIN(MIN(k0 + chunk, total), args.top_k);
if (k0 >= args.top_k) {
return;
}
if (k0 >= total) {
return;
}
int low = k0 > len1 ? k0 - len1 : 0;
int high = MIN(k0, len0);
// binary-search partition (i, j) such that i + j = k
while (low < high) {
const int mid = (low + high) >> 1;
const int32_t idx0 = tmp0[mid];
const int32_t idx1 = tmp1[k0 - mid - 1];
const float val0 = src0_row[idx0];
const float val1 = src0_row[idx1];
bool take_left;
if (order == GGML_SORT_ORDER_ASC) {
take_left = (val0 <= val1);
} else {
take_left = (val0 >= val1);
}
if (take_left) {
low = mid + 1;
} else {
high = mid;
}
}
int i = low;
int j = k0 - i;
// keep the merge fronts into registers
int32_t idx0 = 0;
float val0 = 0.0f;
if (i < len0) {
idx0 = tmp0[i];
val0 = src0_row[idx0];
}
int32_t idx1 = 0;
float val1 = 0.0f;
if (j < len1) {
idx1 = tmp1[j];
val1 = src0_row[idx1];
}
for (int k = k0; k < k1; ++k) {
int32_t out_idx;
if (i >= len0) {
while (k < k1) {
dst[k++] = tmp1[j++];
}
break;
} else if (j >= len1) {
while (k < k1) {
dst[k++] = tmp0[i++];
}
break;
} else {
bool take_left;
if (order == GGML_SORT_ORDER_ASC) {
take_left = (val0 <= val1);
} else {
take_left = (val0 >= val1);
}
if (take_left) {
out_idx = idx0;
++i;
if (i < len0) {
idx0 = tmp0[i];
val0 = src0_row[idx0];
}
} else {
out_idx = idx1;
++j;
if (j < len1) {
idx1 = tmp1[j];
val1 = src0_row[idx1];
}
}
}
dst[k] = out_idx;
}
}
template [[host_name("kernel_argsort_merge_f32_i32_asc")]] kernel argsort_merge_t kernel_argsort_merge_f32_i32<GGML_SORT_ORDER_ASC>;
template [[host_name("kernel_argsort_merge_f32_i32_desc")]] kernel argsort_merge_t kernel_argsort_merge_f32_i32<GGML_SORT_ORDER_DESC>;
+228
View File
@@ -0,0 +1,228 @@
#include "common.h"
// OP: 0 - add, 1 - sub, 2 - mul, 3 - div
constant short FC_bin_op [[function_constant(FC_BIN + 0)]];
constant short FC_bin_f [[function_constant(FC_BIN + 1)]];
constant bool FC_bin_rb [[function_constant(FC_BIN + 2)]];
constant bool FC_bin_cb [[function_constant(FC_BIN + 3)]];
template <typename T0, typename T1, typename T>
kernel void kernel_bin_fuse_impl(
constant ggml_metal_kargs_bin & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
#define FC_OP FC_bin_op
#define FC_F FC_bin_f
#define FC_RB FC_bin_rb
#define FC_CB FC_bin_cb
if (FC_RB) {
// row broadcast
const uint i0 = tgpig.y*args.ne00 + tgpig.x;
const uint i1 = FC_CB ? tgpig.x%args.ne10 : tgpig.x;
device const T0 * src0_row = (device const T0 *) (src0);
device T * dst_row = (device T *) (dst);
if (FC_F == 1) {
device const T1 * src1_row = (device const T1 *) (src1 + args.o1[0]);
if (FC_OP == 0) {
dst_row[i0] = src0_row[i0] + src1_row[i1];
}
if (FC_OP == 1) {
dst_row[i0] = src0_row[i0] - src1_row[i1];
}
if (FC_OP == 2) {
dst_row[i0] = src0_row[i0] * src1_row[i1];
}
if (FC_OP == 3) {
dst_row[i0] = src0_row[i0] / src1_row[i1];
}
} else {
T0 res = src0_row[i0];
if (FC_OP == 0) {
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
res += ((device const T1 *) (src1 + args.o1[j]))[i1];
}
}
if (FC_OP == 1) {
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
res -= ((device const T1 *) (src1 + args.o1[j]))[i1];
}
}
if (FC_OP == 2) {
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
res *= ((device const T1 *) (src1 + args.o1[j]))[i1];
}
}
if (FC_OP == 3) {
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
res /= ((device const T1 *) (src1 + args.o1[j]))[i1];
}
}
dst_row[i0] = res;
}
} else {
const int i03 = tgpig.z;
const int i02 = tgpig.y;
const int i01 = tgpig.x;
if (i01 >= args.ne01) {
return;
}
const int i13 = i03%args.ne13;
const int i12 = i02%args.ne12;
const int i11 = i01%args.ne11;
device const T0 * src0_ptr = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + args.offs);
device T * dst_ptr = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1 + args.offs);
if (FC_F == 1) {
device const T1 * src1_ptr = (device const T1 *) (src1 + args.o1[0] + i13*args.nb13 + i12*args.nb12 + i11*args.nb11);
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const int i10 = FC_CB ? i0%args.ne10 : i0;
if (FC_OP == 0) {
dst_ptr[i0] = src0_ptr[i0] + src1_ptr[i10];
}
if (FC_OP == 1) {
dst_ptr[i0] = src0_ptr[i0] - src1_ptr[i10];
}
if (FC_OP == 2) {
dst_ptr[i0] = src0_ptr[i0] * src1_ptr[i10];
}
if (FC_OP == 3) {
dst_ptr[i0] = src0_ptr[i0] / src1_ptr[i10];
}
}
} else {
device const T1 * src1_ptr[8];
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
src1_ptr[j] = (device const T1 *) (src1 + args.o1[j] + i13*args.nb13 + i12*args.nb12 + i11*args.nb11);
}
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const int i10 = FC_CB ? i0%args.ne10 : i0;
T res = src0_ptr[i0];
if (FC_OP == 0) {
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
res += src1_ptr[j][i10];
}
}
if (FC_OP == 1) {
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
res -= src1_ptr[j][i10];
}
}
if (FC_OP == 2) {
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
res *= src1_ptr[j][i10];
}
}
if (FC_OP == 3) {
FOR_UNROLL (short j = 0; j < FC_F; ++j) {
res /= src1_ptr[j][i10];
}
}
dst_ptr[i0] = res;
}
}
}
#undef FC_OP
#undef FC_F
#undef FC_RB
#undef FC_CB
}
typedef decltype(kernel_bin_fuse_impl<float, float, float>) kernel_bin_fuse_t;
template [[host_name("kernel_bin_fuse_f32_f32_f32")]] kernel kernel_bin_fuse_t kernel_bin_fuse_impl<float, float, float>;
template [[host_name("kernel_bin_fuse_f32_f32_f32_4")]] kernel kernel_bin_fuse_t kernel_bin_fuse_impl<float4, float4, float4>;
template [[host_name("kernel_bin_fuse_f16_f16_f16")]] kernel kernel_bin_fuse_t kernel_bin_fuse_impl<half, half, half>;
template [[host_name("kernel_bin_fuse_f16_f16_f16_4")]] kernel kernel_bin_fuse_t kernel_bin_fuse_impl<half4, half4, half4>;
kernel void kernel_add_id(
constant ggml_metal_kargs_add_id & args,
device const char * src0,
device const char * src1,
device const char * src2,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i1 = tgpig.x;
const int i2 = tgpig.y;
const int i11 = *((device const int32_t *) (src2 + i1*sizeof(int32_t) + i2*args.nb21));
const size_t nb1 = args.ne0 * sizeof(float);
const size_t nb2 = args.ne1 * nb1;
device float * dst_row = (device float *)((device char *)dst + i1*nb1 + i2*nb2);
device const float * src0_row = (device const float *)((device char *)src0 + i1*args.nb01 + i2*args.nb02);
device const float * src1_row = (device const float *)((device char *)src1 + i11*args.nb11);
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
dst_row[i0] = src0_row[i0] + src1_row[i0];
}
}
template<typename T>
kernel void kernel_repeat(
constant ggml_metal_kargs_repeat & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i3 = tgpig.z;
const int i2 = tgpig.y;
const int i1 = tgpig.x;
const int i03 = i3%args.ne03;
const int i02 = i2%args.ne02;
const int i01 = i1%args.ne01;
device const char * src0_ptr = src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01;
device char * dst_ptr = dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const int i00 = i0%args.ne00;
*((device T *)(dst_ptr + i0*args.nb0)) = *((device T *)(src0_ptr + i00*args.nb00));
}
}
typedef decltype(kernel_repeat<float>) kernel_repeat_t;
template [[host_name("kernel_repeat_f32")]] kernel kernel_repeat_t kernel_repeat<float>;
template [[host_name("kernel_repeat_f16")]] kernel kernel_repeat_t kernel_repeat<half>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_repeat_bf16")]] kernel kernel_repeat_t kernel_repeat<bfloat>;
#endif
template [[host_name("kernel_repeat_i32")]] kernel kernel_repeat_t kernel_repeat<int>;
template [[host_name("kernel_repeat_i16")]] kernel kernel_repeat_t kernel_repeat<short>;
+126
View File
@@ -0,0 +1,126 @@
#pragma once
#include "ggml-metal-impl.h"
#include <metal_stdlib>
#ifdef GGML_METAL_HAS_TENSOR
#include <metal_tensor>
#include <MetalPerformancePrimitives/MetalPerformancePrimitives.h>
#endif
using namespace metal;
#define MAX(x, y) ((x) > (y) ? (x) : (y))
#define MIN(x, y) ((x) < (y) ? (x) : (y))
#define SWAP(x, y) { auto tmp = (x); (x) = (y); (y) = tmp; }
#define PAD2(x, n) (((x) + (n) - 1) & ~((n) - 1))
#define FOR_UNROLL(x) _Pragma("clang loop unroll(full)") for (x)
#define N_SIMDWIDTH 32 // assuming SIMD group size is 32
// ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf
//
// cmd:
// .../usr/bin/metal -dM -E -c ggml/src/ggml-metal/kernels/<src>.metal
// .../usr/bin/metal -dM -E -c -target air64-apple-ios14.0 ggml/src/ggml-metal/kernels/<src>.metal
//
#if __METAL_VERSION__ < 310 && defined(GGML_METAL_HAS_BF16)
#undef GGML_METAL_HAS_BF16
#endif
#if defined(GGML_METAL_HAS_BF16)
typedef matrix<bfloat, 4, 4> bfloat4x4;
typedef matrix<bfloat, 2, 4> bfloat2x4;
#endif
constexpr constant static float kvalues_iq4nl_f[16] = {
-127.f, -104.f, -83.f, -65.f, -49.f, -35.f, -22.f, -10.f, 1.f, 13.f, 25.f, 38.f, 53.f, 69.f, 89.f, 113.f
};
constexpr constant static float kvalues_mxfp4_f[16] = {
0, .5f, 1.f, 1.5f, 2.f, 3.f, 4.f, 6.f, -0, -.5f, -1.f, -1.5f, -2.f, -3.f, -4.f, -6.f
};
static inline int best_index_int8(int n, constant float * val, float x) {
if (x <= val[0]) return 0;
if (x >= val[n-1]) return n-1;
int ml = 0, mu = n-1;
while (mu-ml > 1) {
int mav = (ml+mu)/2;
if (x < val[mav]) mu = mav; else ml = mav;
}
return x - val[mu-1] < val[mu] - x ? mu-1 : mu;
}
static inline float e8m0_to_fp32(uint8_t x) {
uint32_t bits;
if (x == 0) {
bits = 0x00400000;
} else {
bits = (uint32_t) x << 23;
}
return as_type<float>(bits);
}
static inline float dot(float x, float y) {
return x*y;
}
static inline float sum(float x) {
return x;
}
static inline float sum(float4 x) {
return x[0] + x[1] + x[2] + x[3];
}
enum ggml_sort_order {
GGML_SORT_ORDER_ASC,
GGML_SORT_ORDER_DESC,
};
constant float GELU_COEF_A = 0.044715f;
constant float GELU_QUICK_COEF = -1.702f;
constant float SQRT_2_OVER_PI = 0.79788456080286535587989211986876f;
constant float SQRT_2_INV = 0.70710678118654752440084436210484f;
// based on Abramowitz and Stegun formula 7.1.26 or similar Hastings' approximation
// ref: https://www.johndcook.com/blog/python_erf/
constant float p_erf = 0.3275911f;
constant float a1_erf = 0.254829592f;
constant float a2_erf = -0.284496736f;
constant float a3_erf = 1.421413741f;
constant float a4_erf = -1.453152027f;
constant float a5_erf = 1.061405429f;
template<typename T>
inline T erf_approx(T x) {
T sign_x = sign(x);
x = fabs(x);
T t = 1.0f / (1.0f + p_erf * x);
T y = 1.0f - (((((a5_erf * t + a4_erf) * t) + a3_erf) * t + a2_erf) * t + a1_erf) * t * exp(-x * x);
return sign_x * y;
}
template<typename T> T elu_approx(T x);
template<> inline float elu_approx<float>(float x) {
return (x > 0.f) ? x : (exp(x) - 1);
}
template<> inline float4 elu_approx<float4>(float4 x) {
float4 res;
res[0] = (x[0] > 0.0f) ? x[0] : (exp(x[0]) - 1.0f);
res[1] = (x[1] > 0.0f) ? x[1] : (exp(x[1]) - 1.0f);
res[2] = (x[2] > 0.0f) ? x[2] : (exp(x[2]) - 1.0f);
res[3] = (x[3] > 0.0f) ? x[3] : (exp(x[3]) - 1.0f);
return res;
}
+723
View File
@@ -0,0 +1,723 @@
#include "common.h"
typedef void (im2col_t)(
constant ggml_metal_kargs_im2col & args,
device const float * x,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template <typename T>
kernel void kernel_im2col(
constant ggml_metal_kargs_im2col & args,
device const float * x,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
// const int64_t IC = tgpg[0];
const int64_t OH = tgpg[1];
const int64_t OW = tgpg[2];
const int64_t KH = ntg[1];
const int64_t KW = ntg[2];
int64_t in = tpitg[0];
const int64_t ikh = tpitg[1];
const int64_t ikw = tpitg[2];
const int64_t iic = tgpig[0];
const int64_t ioh = tgpig[1];
const int64_t iow = tgpig[2];
const int64_t iiw = iow*args.s0 + ikw*args.d0 - args.p0;
const int64_t iih = ioh*args.s1 + ikh*args.d1 - args.p1;
int64_t offset_dst = (in*OH*OW + ioh*OW + iow)*args.CHW + (iic*(KH*KW) + ikh*KW + ikw);
device T * pdst = (device T *) (dst);
if (iih < 0 || iih >= args.IH || iiw < 0 || iiw >= args.IW) {
while (in < args.N) {
pdst[offset_dst] = 0.0f;
offset_dst += ntg[0]*args.CHW*OH*OW;
in += ntg[0];
}
} else {
int64_t offset_src = in*args.ofs0 + iic*args.ofs1 + iih*args.IW + iiw;
while (in < args.N) {
pdst[offset_dst] = x[offset_src];
offset_dst += ntg[0]*args.CHW*OH*OW;
offset_src += ntg[0]*args.ofs0;
in += ntg[0];
}
}
}
template [[host_name("kernel_im2col_f32")]] kernel im2col_t kernel_im2col<float>;
template [[host_name("kernel_im2col_f16")]] kernel im2col_t kernel_im2col<half>;
// TODO: optimize
typedef void (im2col_ext_t)(
constant ggml_metal_kargs_im2col & args,
device const float * x,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template <typename T>
kernel void kernel_im2col_ext(
constant ggml_metal_kargs_im2col & args,
device const float * x,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]], // tgpg[0] = D x IC x KH x KW, CHW = IC x KH x KW
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) { // [M, 1, 1]
const int64_t KHW = (int64_t)args.KHW;
const int64_t d = tgpig[0] / args.CHW;
const int64_t chw = tgpig[0] % args.CHW;
const int64_t tgpig_0 = chw / KHW; // 0 ~ (IC - 1)
const int64_t HW = tgpig[0] % KHW;
const int64_t tpitg_0 = (d * ntg[0]) + tpitg[0];
if (tpitg_0 >= args.N) {
return;
}
const int64_t tpitg_1 = HW / args.KW;
const int64_t tpitg_2 = HW % args.KW;
const int64_t iiw = tgpig[2] * args.s0 + tpitg_2 * args.d0 - args.p0;
const int64_t iih = tgpig[1] * args.s1 + tpitg_1 * args.d1 - args.p1;
const int64_t offset_dst =
(tpitg_0 * tgpg[1] * tgpg[2] + tgpig[1] * tgpg[2] + tgpig[2]) * args.CHW +
(tgpig_0 * KHW + tpitg_1 * args.KW + tpitg_2);
device T * pdst = (device T *) (dst);
if (iih < 0 || iih >= args.IH || iiw < 0 || iiw >= args.IW) {
pdst[offset_dst] = 0.0f;
} else {
const int64_t offset_src = tpitg_0 * args.ofs0 + tgpig_0 * args.ofs1;
pdst[offset_dst] = x[offset_src + iih * args.IW + iiw];
}
}
template [[host_name("kernel_im2col_ext_f32")]] kernel im2col_ext_t kernel_im2col_ext<float>;
template [[host_name("kernel_im2col_ext_f16")]] kernel im2col_ext_t kernel_im2col_ext<half>;
template <typename T>
kernel void kernel_col2im_1d(
constant ggml_metal_kargs_col2im_1d & args,
device const T * col,
device T * dst,
uint tgpig [[threadgroup_position_in_grid]],
uint tpitg [[thread_position_in_threadgroup]],
uint ntg [[threads_per_threadgroup]]) {
const int idx = tgpig * ntg + tpitg;
if (idx >= args.T_out * args.OC) {
return;
}
const int t_out = idx % args.T_out;
const int oc = idx / args.T_out;
const int t_abs = t_out + args.p0; // absolute position in uncropped signal
int t_in_min = (t_abs - args.K + args.s0) / args.s0; // ceil((t_abs - K + 1) / s0)
if (t_in_min < 0) {
t_in_min = 0;
}
int t_in_max = t_abs / args.s0;
if (t_in_max >= args.T_in) {
t_in_max = args.T_in - 1;
}
float sum = 0.0f;
for (int t_in = t_in_min; t_in <= t_in_max; t_in++) {
const int k = t_abs - t_in * args.s0;
sum += float(col[(oc * args.K + k) + t_in * args.K_OC]);
}
dst[t_out + oc * args.T_out] = T(sum);
}
template [[host_name("kernel_col2im_1d_f32")]] kernel void kernel_col2im_1d<float>(constant ggml_metal_kargs_col2im_1d &, device const float *, device float *, uint, uint, uint);
template [[host_name("kernel_col2im_1d_f16")]] kernel void kernel_col2im_1d<half>(constant ggml_metal_kargs_col2im_1d &, device const half *, device half *, uint, uint, uint);
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_col2im_1d_bf16")]] kernel void kernel_col2im_1d<bfloat>(constant ggml_metal_kargs_col2im_1d &, device const bfloat *, device bfloat *, uint, uint, uint);
#endif
template <typename TK>
kernel void kernel_conv_2d(
constant ggml_metal_kargs_conv_2d & args,
device const char * weights,
device const char * src,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const uint threads_per_tg = ntg.x * ntg.y * ntg.z;
const uint tg_index = (tgpig.z * tgpg.y + tgpig.y) * tgpg.x + tgpig.x;
const uint local_thread = tpitg.z * (ntg.x * ntg.y) + tpitg.y * ntg.x + tpitg.x;
const uint thread_index = tg_index * threads_per_tg + local_thread;
const uint64_t total_threads = (uint64_t) threads_per_tg * tgpg.x * tgpg.y * tgpg.z;
const uint64_t total_outputs = (uint64_t) args.N * args.OC * args.OH * args.OW;
for (uint64_t index = thread_index; index < total_outputs; index += total_threads) {
uint64_t tmp = index;
const int32_t ow = tmp % args.OW; tmp /= args.OW;
const int32_t oh = tmp % args.OH; tmp /= args.OH;
const int32_t oc = tmp % args.OC; tmp /= args.OC;
const int32_t n = tmp;
float acc = 0.0f;
const int32_t base_x = ow*args.s0 - args.p0;
const int32_t base_y = oh*args.s1 - args.p1;
int32_t ky_start = 0;
if (base_y < 0) {
ky_start = (-base_y + args.d1 - 1)/args.d1;
}
int32_t ky_end = args.KH;
const int32_t y_max = args.IH - 1 - base_y;
if (y_max < 0) {
ky_end = ky_start;
} else if (base_y + (args.KH - 1)*args.d1 >= args.IH) {
ky_end = min(ky_end, y_max/args.d1 + 1);
}
int32_t kx_start = 0;
if (base_x < 0) {
kx_start = (-base_x + args.d0 - 1)/args.d0;
}
int32_t kx_end = args.KW;
const int32_t x_max = args.IW - 1 - base_x;
if (x_max < 0) {
kx_end = kx_start;
} else if (base_x + (args.KW - 1)*args.d0 >= args.IW) {
kx_end = min(kx_end, x_max/args.d0 + 1);
}
if (ky_start < ky_end && kx_start < kx_end) {
const uint64_t src_base_n = (uint64_t) n * args.nb13;
const uint64_t w_base_oc = (uint64_t) oc * args.nb03;
for (int32_t ic = 0; ic < args.IC; ++ic) {
const uint64_t src_base_nc = src_base_n + (uint64_t) ic * args.nb12;
const uint64_t w_base_ocic = w_base_oc + (uint64_t) ic * args.nb02;
for (int32_t ky = ky_start; ky < ky_end; ++ky) {
const int32_t iy = base_y + ky*args.d1;
const uint64_t src_base_row = src_base_nc + (uint64_t) iy * args.nb11;
const uint64_t w_base_row = w_base_ocic + (uint64_t) ky * args.nb01;
for (int32_t kx = kx_start; kx < kx_end; ++kx) {
const int32_t ix = base_x + kx*args.d0;
const uint64_t src_offs = src_base_row + (uint64_t) ix * args.nb10;
const uint64_t w_offs = w_base_row + (uint64_t) kx * args.nb00;
const float x = *(device const float *)(src + src_offs);
const float w = (float) (*(device const TK *)(weights + w_offs));
acc += x * w;
}
}
}
}
const uint64_t dst_offs =
(uint64_t) n * args.nb3 +
(uint64_t) oc * args.nb2 +
(uint64_t) oh * args.nb1 +
(uint64_t) ow * args.nb0;
*(device float *)(dst + dst_offs) = acc;
}
}
template [[host_name("kernel_conv_2d_f32_f32")]]
kernel void kernel_conv_2d<float>(
constant ggml_metal_kargs_conv_2d & args,
device const char * weights,
device const char * src,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template [[host_name("kernel_conv_2d_f16_f32")]]
kernel void kernel_conv_2d<half>(
constant ggml_metal_kargs_conv_2d & args,
device const char * weights,
device const char * src,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
typedef void (conv_transpose_1d_t)(
constant ggml_metal_kargs_conv_transpose_1d & args,
device const float * src0,
device const float * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]);
template <typename T>
kernel void kernel_conv_transpose_1d(
constant ggml_metal_kargs_conv_transpose_1d & args,
device const T * src0,
device const float * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]) {
// For output position j on the time axis, only input positions
// i such that i*s0 <= j < i*s0 + K
// contribute -- i.e. i in [ceil((j - K + 1)/s0), floor(j/s0)]
// intersected with [0, IL-1]. That's at most ceil(K/s0) values
// (typically 2 for stride==K/2 transposed convs).
const int32_t j = tgpig[0];
const int32_t s0 = args.s0;
const int32_t K = args.K;
const int32_t IL = args.IL;
int32_t i_min;
{
int32_t a = j - K + 1;
i_min = a <= 0 ? 0 : (a + s0 - 1) / s0; // ceil(a/s0) for a>0
}
int32_t i_max = j / s0;
if (i_max > IL - 1) i_max = IL - 1;
float v = 0.0f;
if (i_min <= i_max) {
for (int64_t c = 0; c < args.IC; c++) {
const int32_t kernel_offset = c * tgpg[1] * K + K * tgpig[1];
const int32_t input_offset = c * IL;
for (int32_t i = i_min; i <= i_max; i++) {
v += float(src0[kernel_offset + j - i * s0]) * src1[input_offset + i];
}
}
}
device float * dst_ptr = (device float *) (dst + tgpig[0] * args.nb0 + tgpig[1] * args.nb1);
dst_ptr[0] = v;
}
template [[host_name("kernel_conv_transpose_1d_f32_f32")]]
kernel void kernel_conv_transpose_1d<float>(
constant ggml_metal_kargs_conv_transpose_1d & args,
device const float * src0,
device const float * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]);
template [[host_name("kernel_conv_transpose_1d_f16_f32")]]
kernel void kernel_conv_transpose_1d<half>(
constant ggml_metal_kargs_conv_transpose_1d & args,
device const half * src0,
device const float * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]);
typedef void (conv_transpose_2d_t)(
constant ggml_metal_kargs_conv_transpose_2d & args,
device const float * src0,
device const float * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]]);
template <typename T>
kernel void kernel_conv_transpose_2d(
constant ggml_metal_kargs_conv_transpose_2d & args,
device const T * src0,
device const float * src1,
device char * dst,
threadgroup float * shared_sum [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t out_x = tgpig[0];
const int64_t out_y = tgpig[1];
const int64_t out_c = tgpig[2];
const int64_t kw = tpitg[0];
const int64_t kh = tpitg[1];
float v = 0.0f;
for (int64_t in_c = 0; in_c < args.IC; in_c++) {
int64_t in_y = out_y - kh;
if (in_y < 0 || in_y % args.s0) continue;
in_y /= args.s0;
if (in_y >= args.IH) continue;
int64_t in_x = out_x - kw;
if (in_x < 0 || in_x % args.s0) continue;
in_x /= args.s0;
if (in_x >= args.IW) continue;
const int64_t input_idx = (args.IW * args.IH) * in_c + (args.IW) * in_y + in_x;
const int64_t kernel_idx = (args.KH * args.KW * args.OC) * in_c + (args.KH * args.KW) * out_c + (args.KW) * kh + kw;
v += (float)src0[kernel_idx] * src1[input_idx];
}
const uint tid = tpitg.y * ntg.x + tpitg.x;
shared_sum[tid] = v;
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tid == 0) {
float total = 0.0f;
const uint num_threads = ntg.x * ntg.y;
for (uint i = 0; i < num_threads; i++) {
total += shared_sum[i];
}
device float * dst_ptr = (device float *) (dst + out_x*args.nb0 + out_y * args.nb1 + out_c*args.nb2);
dst_ptr[0] = total;
}
}
template [[host_name("kernel_conv_transpose_2d_f32_f32")]]
kernel void kernel_conv_transpose_2d<float>(
constant ggml_metal_kargs_conv_transpose_2d & args,
device const float * src0,
device const float * src1,
device char * dst,
threadgroup float * shared_sum [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template [[host_name("kernel_conv_transpose_2d_f16_f32")]]
kernel void kernel_conv_transpose_2d<half>(
constant ggml_metal_kargs_conv_transpose_2d & args,
device const half * src0,
device const float * src1,
device char * dst,
threadgroup float * shared_sum [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
// grid: x = C tile, y = OH, z = OW * N (for channel-contiguous layouts)
template <typename TK>
kernel void kernel_conv_2d_dw_tiled(
constant ggml_metal_kargs_conv_2d_dw & args,
device const char * weights,
device const char * src,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int32_t c = (int32_t)(tgpig.x * ntg.x + tpitg.x);
if (c >= args.C) {
return;
}
const int32_t oh = tgpig.y;
const int32_t own = tgpig.z;
const int32_t ow = own % args.OW;
const int32_t n = own / args.OW;
const int32_t base_y = oh*args.s1 - args.p1;
int32_t ky_start = 0;
if (base_y < 0) {
ky_start = (-base_y + args.d1 - 1)/args.d1;
}
int32_t ky_end = args.KH;
const int32_t y_max = args.IH - 1 - base_y;
if (y_max < 0) {
ky_end = ky_start;
} else if (base_y + (args.KH - 1)*args.d1 >= args.IH) {
ky_end = min(ky_end, y_max/args.d1 + 1);
}
const int32_t base_x = ow*args.s0 - args.p0;
int32_t kx_start = 0;
if (base_x < 0) {
kx_start = (-base_x + args.d0 - 1)/args.d0;
}
int32_t kx_end = args.KW;
const int32_t x_max = args.IW - 1 - base_x;
if (x_max < 0) {
kx_end = kx_start;
} else if (base_x + (args.KW - 1)*args.d0 >= args.IW) {
kx_end = min(kx_end, x_max/args.d0 + 1);
}
float acc = 0.0f;
if (ky_start < ky_end && kx_start < kx_end) {
const uint64_t w_base = (uint64_t) c * args.nb02;
const uint64_t src_base = (uint64_t) n * args.nb13 + (uint64_t) c * args.nb12;
for (int32_t ky = ky_start; ky < ky_end; ++ky) {
const int32_t iy = base_y + ky*args.d1;
const uint64_t src_row = src_base + (uint64_t) iy * args.nb11;
const uint64_t w_row = w_base + (uint64_t) ky * args.nb01;
for (int32_t kx = kx_start; kx < kx_end; ++kx) {
const int32_t ix = base_x + kx*args.d0;
const float x = *(device const float *)(src + src_row + (uint64_t) ix * args.nb10);
const float w = (float)(*(device const TK *)(weights + w_row + (uint64_t) kx * args.nb00));
acc += x * w;
}
}
}
const uint64_t dst_offs =
(uint64_t) n * args.nb3 +
(uint64_t) c * args.nb2 +
(uint64_t) oh * args.nb1 +
(uint64_t) ow * args.nb0;
*(device float *)(dst + dst_offs) = acc;
}
// grid: x = OW tile, y = OH, z = C * N (for spatially-contiguous layouts)
template <typename TK>
kernel void kernel_conv_2d_dw(
constant ggml_metal_kargs_conv_2d_dw & args,
device const char * weights,
device const char * src,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int32_t oh = tgpig.y;
const int32_t cn = tgpig.z;
const int32_t c = cn % args.C;
const int32_t n = cn / args.C;
const int32_t base_y = oh*args.s1 - args.p1;
int32_t ky_start = 0;
if (base_y < 0) {
ky_start = (-base_y + args.d1 - 1)/args.d1;
}
int32_t ky_end = args.KH;
const int32_t y_max = args.IH - 1 - base_y;
if (y_max < 0) {
ky_end = ky_start;
} else if (base_y + (args.KH - 1)*args.d1 >= args.IH) {
ky_end = min(ky_end, y_max/args.d1 + 1);
}
const uint64_t w_base = (uint64_t) c * args.nb02;
const uint64_t src_base = (uint64_t) n * args.nb13 + (uint64_t) c * args.nb12;
const int32_t ow = (int32_t)(tgpig.x * ntg.x + tpitg.x);
if (ow >= args.OW) {
return;
}
float acc = 0.0f;
const int32_t base_x = ow*args.s0 - args.p0;
int32_t kx_start = 0;
if (base_x < 0) {
kx_start = (-base_x + args.d0 - 1)/args.d0;
}
int32_t kx_end = args.KW;
const int32_t x_max = args.IW - 1 - base_x;
if (x_max < 0) {
kx_end = kx_start;
} else if (base_x + (args.KW - 1)*args.d0 >= args.IW) {
kx_end = min(kx_end, x_max/args.d0 + 1);
}
if (ky_start < ky_end && kx_start < kx_end) {
for (int32_t ky = ky_start; ky < ky_end; ++ky) {
const int32_t iy = base_y + ky*args.d1;
const uint64_t src_row = src_base + (uint64_t) iy * args.nb11;
const uint64_t w_row = w_base + (uint64_t) ky * args.nb01;
for (int32_t kx = kx_start; kx < kx_end; ++kx) {
const int32_t ix = base_x + kx*args.d0;
const float x = *(device const float *)(src + src_row + (uint64_t) ix * args.nb10);
const float w = (float)(*(device const TK *)(weights + w_row + (uint64_t) kx * args.nb00));
acc += x * w;
}
}
}
const uint64_t dst_offs =
(uint64_t) n * args.nb3 +
(uint64_t) c * args.nb2 +
(uint64_t) oh * args.nb1 +
(uint64_t) ow * args.nb0;
*(device float *)(dst + dst_offs) = acc;
}
template [[host_name("kernel_conv_2d_dw_f32_f32")]]
kernel void kernel_conv_2d_dw<float>(
constant ggml_metal_kargs_conv_2d_dw & args,
device const char * weights,
device const char * src,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template [[host_name("kernel_conv_2d_dw_f16_f32")]]
kernel void kernel_conv_2d_dw<half>(
constant ggml_metal_kargs_conv_2d_dw & args,
device const char * weights,
device const char * src,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template [[host_name("kernel_conv_2d_dw_tiled_f32_f32")]]
kernel void kernel_conv_2d_dw_tiled<float>(
constant ggml_metal_kargs_conv_2d_dw & args,
device const char * weights,
device const char * src,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template [[host_name("kernel_conv_2d_dw_tiled_f16_f32")]]
kernel void kernel_conv_2d_dw_tiled<half>(
constant ggml_metal_kargs_conv_2d_dw & args,
device const char * weights,
device const char * src,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template <typename T>
kernel void kernel_conv_3d(
constant ggml_metal_kargs_conv_3d & args,
device const char * src0, // Weights [IC * OC, KD, KH, KW]
device const char * src1, // Inputs [IC * N, ID, IH, IW]
device char * dst, // Outputs [OC * N, OD, OH, OW]
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]]) {
// 1. Un-flatten the spatial dimension from Grid X
int64_t spatial_idx = tgpig.x * 32 + tpitg.x;
if (spatial_idx >= args.OW * args.OH * args.OD) {
return; // Thread falls outside the spatial volume
}
int64_t od = spatial_idx / (args.OW * args.OH);
int64_t oh = (spatial_idx / args.OW) % args.OH;
int64_t ow = spatial_idx % args.OW;
// 2. Map Y to Channels, Z to Batch
int64_t oc = tgpig.y;
int64_t batch_idx = tgpig.z;
// 3. Calculate anchor coordinates in the Input volume
int64_t i_w_base = ow * args.s0 - args.p0;
int64_t i_h_base = oh * args.s1 - args.p1;
int64_t i_d_base = od * args.s2 - args.p2;
float sum = 0.0f;
// 4. Gather Loop (Iterate over Input Channels -> Depth -> Height -> Width)
for (int64_t ic = 0; ic < args.IC; ++ic) {
// ggml packs batch and channel together in the 4th dimension
int64_t src_cn_idx = batch_idx * args.IC + ic;
int64_t w_cn_idx = oc * args.IC + ic;
for (int64_t kz = 0; kz < args.KD; ++kz) {
int64_t id = i_d_base + kz * args.d2;
if (id < 0 || id >= args.ID) continue; // Boundary check (Padding)
for (int64_t ky = 0; ky < args.KH; ++ky) {
int64_t ih = i_h_base + ky * args.d1;
if (ih < 0 || ih >= args.IH) continue;
for (int64_t kx = 0; kx < args.KW; ++kx) {
int64_t iw = i_w_base + kx * args.d0;
if (iw < 0 || iw >= args.IW) continue;
// Convert multi-dimensional coordinates to flat byte offsets
int64_t w_idx = kx*args.nb00 + ky*args.nb01 + kz*args.nb02 + w_cn_idx*args.nb03;
int64_t i_idx = iw*args.nb10 + ih*args.nb11 + id*args.nb12 + src_cn_idx*args.nb13;
// Dereference memory and cast weights to f32 if they were f16
float w_val = (float)*(device const T*)((device const char*)src0 + w_idx);
float i_val = *(device const float*)((device const char*)src1 + i_idx);
sum += w_val * i_val;
}
}
}
}
// 5. Write the accumulated value out to RAM
int64_t dst_cn_idx = batch_idx * args.OC + oc;
int64_t d_idx = ow*args.nb0 + oh*args.nb1 + od*args.nb2 + dst_cn_idx*args.nb3;
*(device float*)(dst + d_idx) = sum;
}
// Explicit instantiations so the JIT compiler can find them by name
template [[host_name("kernel_conv_3d_f32_f32")]]
kernel void kernel_conv_3d<float>(
constant ggml_metal_kargs_conv_3d & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]]);
// Explicit instantiation for f16 weights
template [[host_name("kernel_conv_3d_f16_f32")]]
kernel void kernel_conv_3d<half>(
constant ggml_metal_kargs_conv_3d & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]]);
+719
View File
@@ -0,0 +1,719 @@
#pragma once
#include "common.h"
#define GGML_COMMON_DECL_METAL
#define GGML_COMMON_IMPL_METAL
#if defined(GGML_METAL_EMBED_LIBRARY)
__embed_ggml-common.h__
#else
#include "ggml-common.h"
#endif
#define QK_NL 16 // shared by mul_mm and get_rows_q instantiations
// NOTE: this is not dequantizing - we are simply fitting the template
template <typename type4x4>
void dequantize_f32(device const float4x4 * src, short il, thread type4x4 & reg) {
reg = (type4x4)(*src);
}
template <typename type4>
void dequantize_f32_t4(device const float4 * src, short il, thread type4 & reg) {
reg = (type4)(*src);
}
template <typename type4x4>
void dequantize_f16(device const half4x4 * src, short il, thread type4x4 & reg) {
reg = (type4x4)(*src);
}
template <typename type4>
void dequantize_f16_t4(device const half4 * src, short il, thread type4 & reg) {
reg = (type4)(*(src));
}
#if defined(GGML_METAL_HAS_BF16)
template <typename type4x4>
void dequantize_bf16(device const bfloat4x4 * src, short il, thread type4x4 & reg) {
reg = (type4x4)(*src);
}
template <typename type4>
void dequantize_bf16_t4(device const bfloat4 * src, short il, thread type4 & reg) {
reg = (type4)(*(src));
}
#endif
template <typename type4x4>
void dequantize_q1_0(device const block_q1_0 * xb, short il, thread type4x4 & reg) {
device const uint8_t * qs = xb->qs;
const float d = xb->d;
const float neg_d = -d;
const int byte_offset = il * 2; // il*16 bits = il*2 bytes
const uint8_t b0 = qs[byte_offset];
const uint8_t b1 = qs[byte_offset + 1];
float4x4 reg_f;
reg_f[0][0] = select(neg_d, d, bool(b0 & 0x01));
reg_f[0][1] = select(neg_d, d, bool(b0 & 0x02));
reg_f[0][2] = select(neg_d, d, bool(b0 & 0x04));
reg_f[0][3] = select(neg_d, d, bool(b0 & 0x08));
reg_f[1][0] = select(neg_d, d, bool(b0 & 0x10));
reg_f[1][1] = select(neg_d, d, bool(b0 & 0x20));
reg_f[1][2] = select(neg_d, d, bool(b0 & 0x40));
reg_f[1][3] = select(neg_d, d, bool(b0 & 0x80));
reg_f[2][0] = select(neg_d, d, bool(b1 & 0x01));
reg_f[2][1] = select(neg_d, d, bool(b1 & 0x02));
reg_f[2][2] = select(neg_d, d, bool(b1 & 0x04));
reg_f[2][3] = select(neg_d, d, bool(b1 & 0x08));
reg_f[3][0] = select(neg_d, d, bool(b1 & 0x10));
reg_f[3][1] = select(neg_d, d, bool(b1 & 0x20));
reg_f[3][2] = select(neg_d, d, bool(b1 & 0x40));
reg_f[3][3] = select(neg_d, d, bool(b1 & 0x80));
reg = (type4x4) reg_f;
}
template <typename type4>
void dequantize_q1_0_t4(device const block_q1_0 * xb, short il, thread type4 & reg) {
const float d = xb->d;
const float neg_d = -d;
const int base = il * 4;
const uint8_t byte = xb->qs[base / 8];
const int s = base % 8;
float4 reg_f;
reg_f[0] = select(neg_d, d, bool((byte >> (s )) & 1));
reg_f[1] = select(neg_d, d, bool((byte >> (s + 1)) & 1));
reg_f[2] = select(neg_d, d, bool((byte >> (s + 2)) & 1));
reg_f[3] = select(neg_d, d, bool((byte >> (s + 3)) & 1));
reg = (type4) reg_f;
}
template <typename type4x4>
void dequantize_q2_0(device const block_q2_0 * xb, short il, thread type4x4 & reg) {
device const uint8_t * qs = xb->qs;
const float d = xb->d;
const int byte_offset = il * 4; // il*16 elements = il*4 bytes (4 elements per byte)
float4x4 reg_f;
for (int i = 0; i < 4; i++) {
const uint8_t b = qs[byte_offset + i];
reg_f[i][0] = ((float)((b >> 0) & 3) - 1.0f) * d;
reg_f[i][1] = ((float)((b >> 2) & 3) - 1.0f) * d;
reg_f[i][2] = ((float)((b >> 4) & 3) - 1.0f) * d;
reg_f[i][3] = ((float)((b >> 6) & 3) - 1.0f) * d;
}
reg = (type4x4) reg_f;
}
template <typename type4>
void dequantize_q2_0_t4(device const block_q2_0 * xb, short il, thread type4 & reg) {
const float d = xb->d;
const uint8_t b = xb->qs[il];
float4 reg_f;
reg_f[0] = ((float)((b >> 0) & 3) - 1.0f) * d;
reg_f[1] = ((float)((b >> 2) & 3) - 1.0f) * d;
reg_f[2] = ((float)((b >> 4) & 3) - 1.0f) * d;
reg_f[3] = ((float)((b >> 6) & 3) - 1.0f) * d;
reg = (type4) reg_f;
}
template <typename type4x4>
void dequantize_q4_0(device const block_q4_0 * xb, short il, thread type4x4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 1);
const float d1 = il ? (xb->d / 16.h) : xb->d;
const float d2 = d1 / 256.f;
const float md = -8.h * xb->d;
const ushort mask0 = il ? 0x00F0 : 0x000F;
const ushort mask1 = mask0 << 8;
float4x4 reg_f;
for (int i = 0; i < 8; i++) {
reg_f[i/2][2*(i%2) + 0] = d1 * (qs[i] & mask0) + md;
reg_f[i/2][2*(i%2) + 1] = d2 * (qs[i] & mask1) + md;
}
reg = (type4x4) reg_f;
}
template <typename type4>
void dequantize_q4_0_t4(device const block_q4_0 * xb, short il, thread type4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 1);
const float d1 = (il/4) ? (xb->d / 16.h) : xb->d;
const float d2 = d1 / 256.f;
const float md = -8.h * xb->d;
const ushort mask0 = (il/4) ? 0x00F0 : 0x000F;
const ushort mask1 = mask0 << 8;
for (int i = 0; i < 2; i++) {
reg[2*i + 0] = d1 * (qs[2*(il%4) + i] & mask0) + md;
reg[2*i + 1] = d2 * (qs[2*(il%4) + i] & mask1) + md;
}
}
template <typename type4x4>
void dequantize_q4_1(device const block_q4_1 * xb, short il, thread type4x4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 2);
const float d1 = il ? (xb->d / 16.h) : xb->d;
const float d2 = d1 / 256.f;
const float m = xb->m;
const ushort mask0 = il ? 0x00F0 : 0x000F;
const ushort mask1 = mask0 << 8;
float4x4 reg_f;
for (int i = 0; i < 8; i++) {
reg_f[i/2][2*(i%2) + 0] = ((qs[i] & mask0) * d1) + m;
reg_f[i/2][2*(i%2) + 1] = ((qs[i] & mask1) * d2) + m;
}
reg = (type4x4) reg_f;
}
template <typename type4>
void dequantize_q4_1_t4(device const block_q4_1 * xb, short il, thread type4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 2);
const float d1 = (il/4) ? (xb->d / 16.h) : xb->d;
const float d2 = d1 / 256.f;
const float m = xb->m;
const ushort mask0 = (il/4) ? 0x00F0 : 0x000F;
const ushort mask1 = mask0 << 8;
for (int i = 0; i < 2; i++) {
reg[2*i + 0] = d1 * (qs[2*(il%4) + i] & mask0) + m;
reg[2*i + 1] = d2 * (qs[2*(il%4) + i] & mask1) + m;
}
}
template <typename type4x4>
void dequantize_q5_0(device const block_q5_0 * xb, short il, thread type4x4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 3);
const float d = xb->d;
const float md = -16.h * xb->d;
const ushort mask = il ? 0x00F0 : 0x000F;
const uint32_t qh = *((device const uint32_t *)xb->qh);
const int x_mv = il ? 4 : 0;
const int gh_mv = il ? 12 : 0;
const int gh_bk = il ? 0 : 4;
float4x4 reg_f;
for (int i = 0; i < 8; i++) {
// extract the 5-th bits for x0 and x1
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
// combine the 4-bits from qs with the 5th bit
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
reg_f[i/2][2*(i%2) + 0] = d * x0 + md;
reg_f[i/2][2*(i%2) + 1] = d * x1 + md;
}
reg = (type4x4) reg_f;
}
template <typename type4>
void dequantize_q5_0_t4(device const block_q5_0 * xb, short il, thread type4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 3);
const float d = xb->d;
const float md = -16.h * xb->d;
const ushort mask = (il/4) ? 0x00F0 : 0x000F;
const uint32_t qh = *((device const uint32_t *)xb->qh);
const int x_mv = (il/4) ? 4 : 0;
const int gh_mv = (il/4) ? 12 : 0;
const int gh_bk = (il/4) ? 0 : 4;
for (int ii = 0; ii < 2; ii++) {
int i = 2*(il%4) + ii;
// extract the 5-th bits for x0 and x1
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
// combine the 4-bits from qs with the 5th bit
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
reg[2*ii + 0] = d * x0 + md;
reg[2*ii + 1] = d * x1 + md;
}
}
template <typename type4x4>
void dequantize_q5_1(device const block_q5_1 * xb, short il, thread type4x4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 4);
const float d = xb->d;
const float m = xb->m;
const ushort mask = il ? 0x00F0 : 0x000F;
const uint32_t qh = *((device const uint32_t *)xb->qh);
const int x_mv = il ? 4 : 0;
const int gh_mv = il ? 12 : 0;
const int gh_bk = il ? 0 : 4;
float4x4 reg_f;
for (int i = 0; i < 8; i++) {
// extract the 5-th bits for x0 and x1
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
// combine the 4-bits from qs with the 5th bit
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
reg_f[i/2][2*(i%2) + 0] = d * x0 + m;
reg_f[i/2][2*(i%2) + 1] = d * x1 + m;
}
reg = (type4x4) reg_f;
}
template <typename type4>
void dequantize_q5_1_t4(device const block_q5_1 * xb, short il, thread type4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 4);
const float d = xb->d;
const float m = xb->m;
const ushort mask = (il/4) ? 0x00F0 : 0x000F;
const uint32_t qh = *((device const uint32_t *)xb->qh);
const int x_mv = (il/4) ? 4 : 0;
const int gh_mv = (il/4) ? 12 : 0;
const int gh_bk = (il/4) ? 0 : 4;
for (int ii = 0; ii < 2; ii++) {
int i = 2*(il%4) + ii;
// extract the 5-th bits for x0 and x1
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
// combine the 4-bits from qs with the 5th bit
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
reg[2*ii + 0] = d * x0 + m;
reg[2*ii + 1] = d * x1 + m;
}
}
template <typename type4x4>
void dequantize_q8_0(device const block_q8_0 *xb, short il, thread type4x4 & reg) {
device const int8_t * qs = ((device const int8_t *)xb->qs);
const float d = xb->d;
float4x4 reg_f;
for (int i = 0; i < 16; i++) {
reg_f[i/4][i%4] = (qs[i + 16*il] * d);
}
reg = (type4x4) reg_f;
}
template <typename type4>
void dequantize_q8_0_t4(device const block_q8_0 *xb, short il, thread type4 & reg) {
device const int8_t * qs = ((device const int8_t *)xb->qs);
const float d = xb->d;
for (int i = 0; i < 4; i++) {
reg[i] = (qs[4*(il%4) + i + 16*(il/4)] * d);
}
}
template <typename type4x4>
void dequantize_mxfp4(device const block_mxfp4 * xb, short il, thread type4x4 & reg) {
device const uint8_t * q2 = (device const uint8_t *)xb->qs;
const float d = e8m0_to_fp32(xb->e);
const uint8_t shr = il >= 1 ? 4 : 0;
for (int i = 0; i < 4; ++i) {
reg[i][0] = d * kvalues_mxfp4_f[(q2[4*i + 0] >> shr) & 0x0F];
reg[i][1] = d * kvalues_mxfp4_f[(q2[4*i + 1] >> shr) & 0x0F];
reg[i][2] = d * kvalues_mxfp4_f[(q2[4*i + 2] >> shr) & 0x0F];
reg[i][3] = d * kvalues_mxfp4_f[(q2[4*i + 3] >> shr) & 0x0F];
}
}
template <typename type4>
void dequantize_mxfp4_t4(device const block_mxfp4 * xb, short il, thread type4 & reg) {
device const uint8_t * q2 = (device const uint8_t *)xb->qs;
const float d = e8m0_to_fp32(xb->e);
const short il4 = il%4;
const uint8_t shr = il >= 4 ? 4 : 0;
reg[0] = d * kvalues_mxfp4_f[(q2[4*il4 + 0] >> shr) & 0x0F];
reg[1] = d * kvalues_mxfp4_f[(q2[4*il4 + 1] >> shr) & 0x0F];
reg[2] = d * kvalues_mxfp4_f[(q2[4*il4 + 2] >> shr) & 0x0F];
reg[3] = d * kvalues_mxfp4_f[(q2[4*il4 + 3] >> shr) & 0x0F];
}
template <typename type4x4>
void dequantize_q2_K(device const block_q2_K *xb, short il, thread type4x4 & reg) {
const float d = xb->d;
const float min = xb->dmin;
device const uint8_t * q = (device const uint8_t *)xb->qs;
float dl, ml;
uint8_t sc = xb->scales[il];
q = q + 32*(il/8) + 16*(il&1);
il = (il/2)%4;
half coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
uchar mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
dl = d * (sc & 0xF) * coef, ml = min * (sc >> 4);
for (int i = 0; i < 16; ++i) {
reg[i/4][i%4] = dl * (q[i] & mask) - ml;
}
}
template <typename type4x4>
void dequantize_q3_K(device const block_q3_K *xb, short il, thread type4x4 & reg) {
const half d_all = xb->d;
device const uint8_t * q = (device const uint8_t *)xb->qs;
device const uint8_t * h = (device const uint8_t *)xb->hmask;
device const int8_t * scales = (device const int8_t *)xb->scales;
q = q + 32 * (il/8) + 16 * (il&1);
h = h + 16 * (il&1);
uint8_t m = 1 << (il/2);
uint16_t kmask1 = (il/4)>1 ? ((il/4)>2 ? 192 : 48) : \
((il/4)>0 ? 12 : 3);
uint16_t kmask2 = il/8 ? 0xF0 : 0x0F;
uint16_t scale_2 = scales[il%8], scale_1 = scales[8 + il%4];
int16_t dl_int = (il/4)&1 ? (scale_2&kmask2) | ((scale_1&kmask1) << 2)
: (scale_2&kmask2) | ((scale_1&kmask1) << 4);
float dl = il<8 ? d_all * (dl_int - 32.f) : d_all * (dl_int / 16.f - 32.f);
const float ml = 4.f * dl;
il = (il/2) & 3;
const half coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
const uint8_t mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
dl *= coef;
for (int i = 0; i < 16; ++i) {
reg[i/4][i%4] = dl * (q[i] & mask) - (h[i] & m ? 0 : ml);
}
}
static inline uchar2 get_scale_min_k4_just2(int j, int k, device const uchar * q) {
return j < 4 ? uchar2{uchar(q[j+0+k] & 63), uchar(q[j+4+k] & 63)}
: uchar2{uchar((q[j+4+k] & 0xF) | ((q[j-4+k] & 0xc0) >> 2)), uchar((q[j+4+k] >> 4) | ((q[j-0+k] & 0xc0) >> 2))};
}
template <typename type4x4>
void dequantize_q4_K(device const block_q4_K * xb, short il, thread type4x4 & reg) {
device const uchar * q = xb->qs;
short is = (il/4) * 2;
q = q + (il/4) * 32 + 16 * (il&1);
il = il & 3;
const uchar2 sc = get_scale_min_k4_just2(is, il/2, xb->scales);
const float d = il < 2 ? xb->d : xb->d / 16.h;
const float min = xb->dmin;
const float dl = d * sc[0];
const float ml = min * sc[1];
const ushort mask = il < 2 ? 0x0F : 0xF0;
for (int i = 0; i < 16; ++i) {
reg[i/4][i%4] = dl * (q[i] & mask) - ml;
}
}
template <typename type4x4>
void dequantize_q5_K(device const block_q5_K *xb, short il, thread type4x4 & reg) {
device const uint8_t * q = xb->qs;
device const uint8_t * qh = xb->qh;
short is = (il/4) * 2;
q = q + 32 * (il/4) + 16 * (il&1);
qh = qh + 16 * (il&1);
uint8_t ul = 1 << (il/2);
il = il & 3;
const uchar2 sc = get_scale_min_k4_just2(is, il/2, xb->scales);
const float d = il < 2 ? xb->d : xb->d / 16.f;
const float min = xb->dmin;
const float dl = d * sc[0];
const float ml = min * sc[1];
const ushort mask = il<2 ? 0x0F : 0xF0;
const float qh_val = il<2 ? 16.f : 256.f;
for (int i = 0; i < 16; ++i) {
reg[i/4][i%4] = dl * ((q[i] & mask) + (qh[i] & ul ? qh_val : 0)) - ml;
}
}
template <typename type4x4>
void dequantize_q6_K(device const block_q6_K *xb, short il, thread type4x4 & reg) {
const half d_all = xb->d;
device const uint16_t * ql = (device const uint16_t *)xb->ql;
device const uint16_t * qh = (device const uint16_t *)xb->qh;
device const int8_t * scales = (device const int8_t *)xb->scales;
ql = ql + 32*(il/8) + 16*((il/2)&1) + 8*(il&1);
qh = qh + 16*(il/8) + 8*(il&1);
float sc = scales[(il%2) + 2 * ((il/2))];
il = (il/2) & 3;
const uint32_t kmask1 = il>1 ? (il>2 ? 0xC0C0C0C0 : 0x30303030) : (il>0 ? 0x0C0C0C0C : 0x03030303);
const uint32_t kmask2 = il>1 ? 0xF0F0F0F0 : 0x0F0F0F0F;
const float ml = d_all * sc * 32.f;
const float dl0 = d_all * sc;
const float dl1 = dl0 / 256.f;
const float dl2 = dl0 / (256.f * 256.f);
const float dl3 = dl0 / (256.f * 256.f * 256.f);
const uint8_t shr_h = il>2 ? 2 : 0;
const uint8_t shl_h = il>1 ? 0 : (il>0 ? 2 : 4);
const uint8_t shr_l = il>1 ? 4 : 0;
for (int i = 0; i < 4; ++i) {
const uint32_t low = (ql[2*i] | (uint32_t)(ql[2*i+1] << 16)) & kmask2;
const uint32_t high = (qh[2*i] | (uint32_t)(qh[2*i+1] << 16)) & kmask1;
const uint32_t q = ((high << shl_h) >> shr_h) | (low >> shr_l);
reg[i][0] = dl0 * ((half)(q & 0xFF)) - ml;
reg[i][1] = dl1 * ((float)(q & 0xFF00)) - ml;
reg[i][2] = dl2 * ((float)(q & 0xFF0000)) - ml;
reg[i][3] = dl3 * ((float)(q & 0xFF000000)) - ml;
}
}
template <typename type4x4>
void dequantize_iq2_xxs(device const block_iq2_xxs * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
// each block of 32 needs 2 uint32_t's for the quants & scale, so 4 uint16_t's.
device const uint16_t * q2 = xb->qs + 4*ib32;
const uint32_t aux32_g = q2[0] | (q2[1] << 16);
const uint32_t aux32_s = q2[2] | (q2[3] << 16);
thread const uint8_t * aux8 = (thread const uint8_t *)&aux32_g;
const float dl = d * (0.5f + (aux32_s >> 28)) * 0.25f;
constant uint8_t * grid = (constant uint8_t *)(iq2xxs_grid + aux8[2*il+0]);
uint8_t signs = ksigns_iq2xs[(aux32_s >> 14*il) & 127];
for (int i = 0; i < 8; ++i) {
reg[i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
}
grid = (constant uint8_t *)(iq2xxs_grid + aux8[2*il+1]);
signs = ksigns_iq2xs[(aux32_s >> (14*il+7)) & 127];
for (int i = 0; i < 8; ++i) {
reg[2+i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
}
}
template <typename type4x4>
void dequantize_iq2_xs(device const block_iq2_xs * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint16_t * q2 = xb->qs + 4*ib32;
const float dl = d * (0.5f + ((xb->scales[ib32] >> 4*il) & 0xf)) * 0.25f;
constant uint8_t * grid = (constant uint8_t *)(iq2xs_grid + (q2[2*il+0] & 511));
uint8_t signs = ksigns_iq2xs[q2[2*il+0] >> 9];
for (int i = 0; i < 8; ++i) {
reg[i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
}
grid = (constant uint8_t *)(iq2xs_grid + (q2[2*il+1] & 511));
signs = ksigns_iq2xs[q2[2*il+1] >> 9];
for (int i = 0; i < 8; ++i) {
reg[2+i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
}
}
template <typename type4x4>
void dequantize_iq3_xxs(device const block_iq3_xxs * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint8_t * q3 = xb->qs + 8*ib32;
device const uint16_t * gas = (device const uint16_t *)(xb->qs + QK_K/4) + 2*ib32;
const uint32_t aux32 = gas[0] | (gas[1] << 16);
const float dl = d * (0.5f + (aux32 >> 28)) * 0.5f;
constant uint8_t * grid1 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+0]);
constant uint8_t * grid2 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+1]);
uint8_t signs = ksigns_iq2xs[(aux32 >> 14*il) & 127];
for (int i = 0; i < 4; ++i) {
reg[0][i] = dl * grid1[i] * (signs & kmask_iq2xs[i+0] ? -1.f : 1.f);
reg[1][i] = dl * grid2[i] * (signs & kmask_iq2xs[i+4] ? -1.f : 1.f);
}
grid1 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+2]);
grid2 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+3]);
signs = ksigns_iq2xs[(aux32 >> (14*il+7)) & 127];
for (int i = 0; i < 4; ++i) {
reg[2][i] = dl * grid1[i] * (signs & kmask_iq2xs[i+0] ? -1.f : 1.f);
reg[3][i] = dl * grid2[i] * (signs & kmask_iq2xs[i+4] ? -1.f : 1.f);
}
}
template <typename type4x4>
void dequantize_iq3_s(device const block_iq3_s * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint8_t * qs = xb->qs + 8*ib32;
device const uint8_t * signs = xb->signs + 4*ib32 + 2*il;
const uint8_t qh = xb->qh[ib32] >> 4*il;
const float dl = d * (1 + 2*((xb->scales[ib32/2] >> 4*(ib32%2)) & 0xf));
constant uint8_t * grid1 = (constant uint8_t *)(iq3s_grid + (qs[4*il+0] | ((qh << 8) & 256)));
constant uint8_t * grid2 = (constant uint8_t *)(iq3s_grid + (qs[4*il+1] | ((qh << 7) & 256)));
for (int i = 0; i < 4; ++i) {
reg[0][i] = dl * grid1[i] * select(1, -1, signs[0] & kmask_iq2xs[i+0]);
reg[1][i] = dl * grid2[i] * select(1, -1, signs[0] & kmask_iq2xs[i+4]);
}
grid1 = (constant uint8_t *)(iq3s_grid + (qs[4*il+2] | ((qh << 6) & 256)));
grid2 = (constant uint8_t *)(iq3s_grid + (qs[4*il+3] | ((qh << 5) & 256)));
for (int i = 0; i < 4; ++i) {
reg[2][i] = dl * grid1[i] * select(1, -1, signs[1] & kmask_iq2xs[i+0]);
reg[3][i] = dl * grid2[i] * select(1, -1, signs[1] & kmask_iq2xs[i+4]);
}
}
template <typename type4x4>
void dequantize_iq2_s(device const block_iq2_s * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
device const uint8_t * signs = qs + QK_K/8;
const uint8_t qh = xb->qh[ib32] >> 4*il;
const float dl = d * (0.5f + ((xb->scales[ib32] >> 4*il) & 0xf)) * 0.25f;
constant uint8_t * grid1 = (constant uint8_t *)(iq2s_grid + (qs[0] | ((qh << 8) & 0x300)));
constant uint8_t * grid2 = (constant uint8_t *)(iq2s_grid + (qs[1] | ((qh << 6) & 0x300)));
for (int i = 0; i < 8; ++i) {
reg[i/4+0][i%4] = dl * grid1[i] * select(1, -1, signs[0] & kmask_iq2xs[i]);
reg[i/4+2][i%4] = dl * grid2[i] * select(1, -1, signs[1] & kmask_iq2xs[i]);
}
}
template <typename type4x4>
void dequantize_iq1_s(device const block_iq1_s * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const int ib32 = il/2;
il = il%2;
const float d = xb->d;
device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
device const uint16_t * qh = xb->qh;
const float dl = d * (2*((qh[ib32] >> 12) & 7) + 1);
const float ml = dl * (qh[ib32] & 0x8000 ? -1 - IQ1S_DELTA : -1 + IQ1S_DELTA);
const uint16_t h = qh[ib32] >> 6*il;
constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((h << 8) & 0x700)));
constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((h << 5) & 0x700)));
for (int i = 0; i < 4; ++i) {
reg[0][i] = dl * (grid1[i] & 0xf) + ml;
reg[1][i] = dl * (grid1[i] >> 4) + ml;
reg[2][i] = dl * (grid2[i] & 0xf) + ml;
reg[3][i] = dl * (grid2[i] >> 4) + ml;
}
}
template <typename type4x4>
void dequantize_iq1_m(device const block_iq1_m * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const int ib32 = il/2;
il = il%2;
device const uint16_t * sc = (device const uint16_t *)xb->scales;
iq1m_scale_t scale;
scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
const float d = scale.f16;
device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
device const uint8_t * qh = xb->qh + 2*ib32 + il;
const float dl = d * (2*((sc[ib32/2] >> (6*(ib32%2)+3*il)) & 7) + 1);
const float ml1 = dl * (qh[0] & 0x08 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
const float ml2 = dl * (qh[0] & 0x80 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((qh[0] << 8) & 0x700)));
constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((qh[0] << 4) & 0x700)));
for (int i = 0; i < 4; ++i) {
reg[0][i] = dl * (grid1[i] & 0xf) + ml1;
reg[1][i] = dl * (grid1[i] >> 4) + ml1;
reg[2][i] = dl * (grid2[i] & 0xf) + ml2;
reg[3][i] = dl * (grid2[i] >> 4) + ml2;
}
}
template <typename type4x4>
void dequantize_iq4_nl(device const block_iq4_nl * xb, short il, thread type4x4 & reg) {
device const uint16_t * q4 = (device const uint16_t *)xb->qs;
const float d = xb->d;
uint32_t aux32;
thread const uint8_t * q8 = (thread const uint8_t *)&aux32;
for (int i = 0; i < 4; ++i) {
aux32 = ((q4[2*i] | (q4[2*i+1] << 16)) >> 4*il) & 0x0f0f0f0f;
reg[i][0] = d * kvalues_iq4nl_f[q8[0]];
reg[i][1] = d * kvalues_iq4nl_f[q8[1]];
reg[i][2] = d * kvalues_iq4nl_f[q8[2]];
reg[i][3] = d * kvalues_iq4nl_f[q8[3]];
}
}
template <typename type4>
void dequantize_iq4_nl_t4(device const block_iq4_nl * xb, short il, thread type4 & reg) {
device const uint16_t * q4 = (device const uint16_t *)xb->qs;
const float d = xb->d;
uint32_t aux32;
thread const uint8_t * q8 = (thread const uint8_t *)&aux32;
aux32 = ((q4[2*(il%4)] | (q4[2*(il%4)+1] << 16)) >> 4*(il/4)) & 0x0f0f0f0f;
reg[0] = d * kvalues_iq4nl_f[q8[0]];
reg[1] = d * kvalues_iq4nl_f[q8[1]];
reg[2] = d * kvalues_iq4nl_f[q8[2]];
reg[3] = d * kvalues_iq4nl_f[q8[3]];
}
template <typename type4x4>
void dequantize_iq4_xs(device const block_iq4_xs * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint32_t * q4 = (device const uint32_t *)xb->qs + 4*ib32;
const int ls = ((xb->scales_l[ib32/2] >> 4*(ib32%2)) & 0xf) | (((xb->scales_h >> 2*ib32) & 3) << 4);
const float d = (float)xb->d * (ls - 32);
uint32_t aux32;
thread const uint8_t * q8 = (thread const uint8_t *)&aux32;
for (int i = 0; i < 4; ++i) {
aux32 = (q4[i] >> 4*il) & 0x0f0f0f0f;
reg[i][0] = d * kvalues_iq4nl_f[q8[0]];
reg[i][1] = d * kvalues_iq4nl_f[q8[1]];
reg[i][2] = d * kvalues_iq4nl_f[q8[2]];
reg[i][3] = d * kvalues_iq4nl_f[q8[3]];
}
}
File diff suppressed because it is too large Load Diff
@@ -0,0 +1,250 @@
#include "common.h"
constant short FC_gated_delta_net_ne20 [[function_constant(FC_GATED_DELTA_NET + 0)]];
constant short FC_gated_delta_net_ne30 [[function_constant(FC_GATED_DELTA_NET + 1)]];
constant short FC_gated_delta_net_K [[function_constant(FC_GATED_DELTA_NET + 2)]];
#if 1
template<short NSG>
kernel void kernel_gated_delta_net_impl(
constant ggml_metal_kargs_gated_delta_net & args,
device const char * q,
device const char * k,
device const char * v,
device const char * g,
device const char * b,
device const char * s,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
#define S_v FC_gated_delta_net_ne20
#define G FC_gated_delta_net_ne30
#define K FC_gated_delta_net_K
const uint tx = tpitg.x;
const uint ty = tpitg.y;
const uint i23 = tgpig.z; // B (n_seqs)
const uint i21 = tgpig.y; // H (head)
const uint i20 = tgpig.x*NSG + ty; // row within S_v
const uint i01 = i21 % args.ne01;
const uint i11 = i21 % args.ne11;
const float scale = 1.0f / sqrt((float)S_v);
// input state layout [S_v, S_v, H, n_seqs] (s0 only): per-seq stride is H*D.
// state is stored transposed: M[i20][is] = S[is][i20], so row i20 is contiguous
const uint state_in_base = (i23*args.ne21 + i21)*S_v*S_v + i20*S_v;
device const float * s_ptr = (device const float *) (s) + state_in_base;
float ls[NSG];
FOR_UNROLL (short j = 0; j < NSG; j++) {
const short is = tx*NSG + j;
ls[j] = s_ptr[is];
}
device float * dst_attn = (device float *) (dst) + (i23*args.ne22*args.ne21 + i21)*S_v + i20;
device const float * q_ptr = (device const float *) (q + i23*args.nb03 + i01*args.nb01);
device const float * k_ptr = (device const float *) (k + i23*args.nb13 + i11*args.nb11);
device const float * v_ptr = (device const float *) (v + i23*args.nb23 + i21*args.nb21);
device const float * b_ptr = (device const float *) (b) + (i23*args.ne22*args.ne21 + i21);
device const float * g_ptr = (device const float *) (g) + (i23*args.ne22*args.ne21 + i21)*G;
// snapshot slot mapping: slot 0 = most recent state, slot s = s tokens back.
// When n_tokens < K, only slots 0..n_tokens-1 are written; older slots are caller-owned.
// output state base offset: after attention scores
const uint attn_size = args.ne22 * args.ne21 * S_v * args.ne23;
// output state per-slot size: S_v * S_v * H * n_seqs
const uint state_size_per_snap = S_v * S_v * args.ne21 * args.ne23;
// per-(seq,head) offset within a slot
const uint state_out_base = (i23*args.ne21 + i21)*S_v*S_v + i20*S_v;
for (short t = 0; t < args.ne22; t++) {
float s_k = 0.0f;
if (G == 1) {
const float g_exp = exp(g_ptr[0]);
FOR_UNROLL (short j = 0; j < NSG; j++) {
const short is = tx*NSG + j;
ls[j] *= g_exp;
s_k += ls[j]*k_ptr[is];
}
} else {
// KDA
FOR_UNROLL (short j = 0; j < NSG; j++) {
const short is = tx*NSG + j;
ls[j] *= exp(g_ptr[is]);
s_k += ls[j]*k_ptr[is];
}
}
s_k = simd_sum(s_k);
const float d = (v_ptr[i20] - s_k)*b_ptr[0];
float y = 0.0f;
FOR_UNROLL (short j = 0; j < NSG; j++) {
const short is = tx*NSG + j;
ls[j] += k_ptr[is]*d;
y += ls[j]*q_ptr[is];
}
y = simd_sum(y);
if (tx == 0) {
dst_attn[t*args.ne21*S_v] = y*scale;
}
q_ptr += args.ns02;
k_ptr += args.ns12;
v_ptr += args.ns22;
b_ptr += args.ne21;
g_ptr += args.ne21*G;
if (K > 1) {
const int target_slot = (int)args.ne22 - 1 - (int)t;
if (target_slot >= 0 && target_slot < (int)K) {
device float * dst_state = (device float *) (dst) + attn_size + (uint)target_slot * state_size_per_snap + state_out_base;
FOR_UNROLL (short j = 0; j < NSG; j++) {
const short is = tx*NSG + j;
dst_state[is] = ls[j];
}
}
}
}
if (K == 1) {
device float * dst_state = (device float *) (dst) + attn_size + state_out_base;
FOR_UNROLL (short j = 0; j < NSG; j++) {
const short is = tx*NSG + j;
dst_state[is] = ls[j];
}
}
#undef S_v
#undef G
#undef K
}
typedef decltype(kernel_gated_delta_net_impl<4>) kernel_gated_delta_net_t;
template [[host_name("kernel_gated_delta_net_f32_1")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<1>;
template [[host_name("kernel_gated_delta_net_f32_2")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<2>;
template [[host_name("kernel_gated_delta_net_f32_4")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<4>;
#else
// a simplified version of the above
// no performance improvement, so keep the above version for now
template<typename T, short NSG>
kernel void kernel_gated_delta_net_impl(
constant ggml_metal_kargs_gated_delta_net & args,
device const char * q,
device const char * k,
device const char * v,
device const char * g,
device const char * b,
device const char * s,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
#define S_v FC_gated_delta_net_ne20
#define G FC_gated_delta_net_ne30
const uint tx = tpitg.x;
const uint ty = tpitg.y;
const uint i23 = tgpig.z; // B
const uint i21 = tgpig.y; // H
const uint i20 = tgpig.x*NSG + ty;
const uint i01 = i21 % args.ne01;
const uint i11 = i21 % args.ne11;
const float scale = 1.0f / sqrt((float)S_v);
device const float * s_ptr = (device const float *) (s) + (i23*args.ne21 + i21)*S_v*S_v + i20;
float lsf[NSG];
FOR_UNROLL (short j = 0; j < NSG; j++) {
const short is = tx*NSG + j;
lsf[j] = s_ptr[is*S_v];
}
thread T * ls = (thread T *) (lsf);
device float * dst_attn = (device float *) (dst) + (i23*args.ne22*args.ne21 + i21)*S_v + i20;
device const float * q_ptr = (device const float *) (q + i23*args.nb03 + i01*args.nb01);
device const float * k_ptr = (device const float *) (k + i23*args.nb13 + i11*args.nb11);
device const float * v_ptr = (device const float *) (v + i23*args.nb23 + i21*args.nb21);
device const float * b_ptr = (device const float *) (b) + (i23*args.ne22*args.ne21 + i21);
device const float * g_ptr = (device const float *) (g) + (i23*args.ne22*args.ne21 + i21)*G;
for (short t = 0; t < args.ne22; t++) {
device const T * qt_ptr = (device const T *) (q_ptr);
device const T * kt_ptr = (device const T *) (k_ptr);
device const T * gt_ptr = (device const T *) (g_ptr);
if (G == 1) {
*ls *= exp(g_ptr[0]);
} else {
// KDA
*ls *= exp(gt_ptr[tx]);
}
const float s_k = simd_sum(dot(*ls, kt_ptr[tx]));
const float d = (v_ptr[i20] - s_k)*b_ptr[0];
*ls += kt_ptr[tx]*d;
const float y = simd_sum(dot(*ls, qt_ptr[tx]));
if (tx == 0) {
*dst_attn = y*scale;
}
q_ptr += args.ns02;
k_ptr += args.ns12;
v_ptr += args.ns22;
b_ptr += args.ne21;
g_ptr += args.ne21*G;
dst_attn += args.ne21*S_v;
}
device float * dst_state = (device float *) (dst) + args.ne23*args.ne22*args.ne21*S_v + (i23*args.ne21 + i21)*S_v*S_v + i20;
device T * dstt_state = (device T *) (dst_state);
FOR_UNROLL (short j = 0; j < NSG; j++) {
const short is = tx*NSG + j;
dst_state[is*S_v] = lsf[j];
}
#undef S_v
#undef G
}
typedef decltype(kernel_gated_delta_net_impl<float4, 4>) kernel_gated_delta_net_t;
template [[host_name("kernel_gated_delta_net_f32_1")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<float, 1>;
template [[host_name("kernel_gated_delta_net_f32_2")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<float2, 2>;
template [[host_name("kernel_gated_delta_net_f32_4")]] kernel kernel_gated_delta_net_t kernel_gated_delta_net_impl<float4, 4>;
#endif
+595
View File
@@ -0,0 +1,595 @@
#include "common.h"
kernel void kernel_argmax_f32(
constant ggml_metal_kargs_argmax & args,
device const char * src0,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint sgitg[[simdgroup_index_in_threadgroup]],
uint tiisg[[thread_index_in_simdgroup]],
uint ntg[[threads_per_threadgroup]]) {
device const float * x_row = (device const float *) ((device const char *) src0 + tgpig * args.nb01);
float lmax = -INFINITY;
int32_t larg = -1;
for (int i00 = tpitg; i00 < args.ne00; i00 += ntg) {
if (x_row[i00] > lmax) {
lmax = x_row[i00];
larg = i00;
}
}
// find the argmax value in the block
float max_val = simd_max(lmax);
int32_t arg_val = simd_max(select(-1, larg, lmax == max_val));
device int32_t * dst_i32 = (device int32_t *) dst;
threadgroup float * shared_maxval = (threadgroup float *) shmem;
threadgroup int32_t * shared_argmax = (threadgroup int32_t *) shmem + N_SIMDWIDTH;
if (ntg > N_SIMDWIDTH) {
if (sgitg == 0) {
shared_maxval[tiisg] = -INFINITY;
shared_argmax[tiisg] = -1;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shared_maxval[sgitg] = max_val;
shared_argmax[sgitg] = arg_val;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
max_val = shared_maxval[tiisg];
arg_val = shared_argmax[tiisg];
float max_val_reduced = simd_max(max_val);
int32_t arg_val_reduced = simd_max(select(-1, arg_val, max_val == max_val_reduced));
dst_i32[tgpig] = arg_val_reduced;
return;
}
dst_i32[tgpig] = arg_val;
}
kernel void kernel_diag_f32(
constant ggml_metal_kargs_diag & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiitg[[thread_index_in_threadgroup]]) {
constexpr short NW = N_SIMDWIDTH;
const int32_t i3 = tgpig.z;
const int32_t i2 = tgpig.y;
const int32_t i1 = tgpig.x;
device const float * src0_ptr = (device const float *)(src0 + i2*args.nb02 + i3*args.nb03);
device float * dst_ptr = (device float *)(dst + i1*args.nb01 + i2*args.nb2 + i3*args.nb3);
for (int i0 = tiitg; i0 < args.ne0; i0 += NW) {
dst_ptr[i0] = i0 == i1 ? src0_ptr[i0] : 0.0f;
}
}
kernel void kernel_roll_f32(
constant ggml_metal_kargs_roll & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t i3 = tgpig.z;
const int64_t i2 = tgpig.y;
const int64_t i1 = tgpig.x;
device const float * src0_ptr = (device const float *) src0;
device float * dst_ptr = (device float *) dst;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
// apply shifts and wrap around
int64_t i00 = i0 - args.s0;
int64_t i01 = i1 - args.s1;
int64_t i02 = i2 - args.s2;
int64_t i03 = i3 - args.s3;
if (i00 < 0) { i00 += args.ne00; } else if (i00 >= args.ne00) { i00 -= args.ne00; }
if (i01 < 0) { i01 += args.ne01; } else if (i01 >= args.ne01) { i01 -= args.ne01; }
if (i02 < 0) { i02 += args.ne02; } else if (i02 >= args.ne02) { i02 -= args.ne02; }
if (i03 < 0) { i03 += args.ne03; } else if (i03 >= args.ne03) { i03 -= args.ne03; }
int64_t src_idx = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00 + i00;
int64_t dst_idx = i3 *args.ne2 *args.ne1 *args.ne0 + i2 *args.ne1 *args.ne0 + i1 *args.ne0 + i0;
dst_ptr[dst_idx] = src0_ptr[src_idx];
}
}
template <typename T>
kernel void kernel_pad_impl(
constant ggml_metal_kargs_pad & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int32_t i3 = tgpig.z;
const int32_t i2 = tgpig.y;
const int32_t k0 = tgpig.x/args.ne1;
const int32_t i1 = tgpig.x - k0*args.ne1;
const int32_t i03 = i3;
const int32_t i02 = i2;
const int32_t i01 = i1;
device const T * src0_ptr = (device const T *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
device T * dst_ptr = (device T *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1);
for (int32_t l0 = 0; l0 < 1024; l0 += ntg.x) {
const int32_t i0 = k0*1024 + tpitg.x + l0;
if (i0 >= args.ne0) {
break;
}
if (i0 < args.ne00 && i1 < args.ne01 && i2 < args.ne02 && i3 < args.ne03) {
dst_ptr[i0] = src0_ptr[i0];
} else {
dst_ptr[i0] = 0.0f;
}
}
}
typedef decltype(kernel_pad_impl<float>) kernel_pad_t;
template [[host_name("kernel_pad_f32")]] kernel kernel_pad_t kernel_pad_impl<float>;
template [[host_name("kernel_pad_f32_4")]] kernel kernel_pad_t kernel_pad_impl<float4>;
// TODO: this is slow - optimize
kernel void kernel_pad_reflect_1d_f32(
constant ggml_metal_kargs_pad_reflect_1d & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t i3 = tgpig.z;
const int64_t i2 = tgpig.y;
const int64_t i1 = tgpig.x;
const int64_t i03 = i3;
const int64_t i02 = i2;
const int64_t i01 = i1;
device const float * src0_ptr = (device const float *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
device float * dst_ptr = (device float *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1);
if (i1 < args.ne01 && i2 < args.ne02 && i3 < args.ne03) {
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
if (i0 < args.p0) {
dst_ptr[i0] = src0_ptr[args.p0 - i0];
} else if (i0 < args.ne0 - args.p1) {
dst_ptr[i0] = src0_ptr[i0 - args.p0];
} else {
dst_ptr[i0] = src0_ptr[(args.ne0 - args.p1 - args.p0) - (args.p1 + 1 - (args.ne0 - i0)) - 1];
}
}
}
}
kernel void kernel_arange_f32(
constant ggml_metal_kargs_arange & args,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
device float * dst_ptr = (device float *) dst;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
dst_ptr[i0] = args.start + args.step * i0;
}
}
kernel void kernel_timestep_embedding_f32(
constant ggml_metal_kargs_timestep_embedding & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
int i = tgpig.x;
device float * embed_data = (device float *)(dst + i*args.nb1);
int half_ = args.dim / 2;
for (int j = tpitg.x; j < half_; j += ntg.x) {
float timestep = ((device float *)src0)[i];
float freq = (float)exp(-log((float)args.max_period) * j / half_);
float arg = timestep * freq;
embed_data[j ] = cos(arg);
embed_data[j + half_] = sin(arg);
}
if (args.dim % 2 != 0 && tpitg.x == 0) {
embed_data[2 * half_] = 0.f;
}
}
kernel void kernel_opt_step_adamw_f32(
constant ggml_metal_kargs_opt_step_adamw & args,
device float * x,
device const float * g,
device float * g_m,
device float * g_v,
device const float * pars,
uint gid[[thread_position_in_grid]]) {
if (gid >= args.np) {
return;
}
const float alpha = pars[0];
const float beta1 = pars[1];
const float beta2 = pars[2];
const float eps = pars[3];
const float wd = pars[4];
const float beta1h = pars[5];
const float beta2h = pars[6];
const float gi = g[gid];
const float gmi = g_m[gid] * beta1 + gi * (1.0f - beta1);
const float gvi = g_v[gid] * beta2 + gi * gi * (1.0f - beta2);
g_m[gid] = gmi;
g_v[gid] = gvi;
const float mh = gmi * beta1h;
const float vh = sqrt(gvi * beta2h) + eps;
x[gid] = x[gid] * (1.0f - alpha * wd) - alpha * mh / vh;
}
kernel void kernel_opt_step_sgd_f32(
constant ggml_metal_kargs_opt_step_sgd & args,
device float * x,
device const float * g,
device const float * pars,
uint gid[[thread_position_in_grid]]) {
if (gid >= args.np) {
return;
}
x[gid] = x[gid] * (1.0f - pars[0] * pars[1]) - pars[0] * g[gid];
}
template<typename T>
kernel void kernel_memset(
constant ggml_metal_kargs_memset & args,
device T * dst,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = args.val;
}
typedef decltype(kernel_memset<int64_t>) kernel_memset_t;
template [[host_name("kernel_memset_i64")]] kernel kernel_memset_t kernel_memset<int64_t>;
constant short FC_count_equal_nsg [[function_constant(FC_COUNT_EQUAL + 0)]];
template<typename T>
kernel void kernel_count_equal(
constant ggml_metal_kargs_count_equal & args,
device const char * src0,
device const char * src1,
device atomic_int * dst,
threadgroup int32_t * shmem_i32 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const short NSG = FC_count_equal_nsg;
const int i3 = tgpig.z;
const int i2 = tgpig.y;
const int i1 = tgpig.x;
if (i3 >= args.ne03 || i2 >= args.ne02 || i1 >= args.ne01) {
return;
}
int sum = 0;
device const char * base0 = src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03;
device const char * base1 = src1 + i1*args.nb11 + i2*args.nb12 + i3*args.nb13;
for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
const T v0 = *(device const T *)(base0 + i0*args.nb00);
const T v1 = *(device const T *)(base1 + i0*args.nb10);
sum += (v0 == v1);
}
sum = simd_sum(sum);
if (tiisg == 0) {
shmem_i32[sgitg] = sum;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (sgitg == 0) {
float v = 0.0f;
if (tpitg.x < NSG) {
v = shmem_i32[tpitg.x];
}
float total = simd_sum(v);
if (tpitg.x == 0) {
atomic_fetch_add_explicit(dst, (int32_t) total, memory_order_relaxed);
}
}
}
typedef decltype(kernel_count_equal<int32_t>) kernel_count_equal_t;
template [[host_name("kernel_count_equal_i32")]] kernel kernel_count_equal_t kernel_count_equal<int32_t>;
template <typename T>
kernel void kernel_snake(
constant ggml_metal_kargs_snake & args,
device const T * x,
device const float * a,
device const float * inv_b,
device T * dst,
uint tgpig [[threadgroup_position_in_grid]],
uint tpitg [[thread_position_in_threadgroup]],
uint ntg [[threads_per_threadgroup]]) {
const int idx = tgpig * ntg + tpitg;
if (idx >= args.T * args.C) {
return;
}
const int c = idx / args.T; // x is [T, C], a / inv_b collapse to [1, C]
const float xi = float(x[idx]);
const float si = sin(a[c] * xi);
dst[idx] = T(xi + si * si * inv_b[c]);
}
template [[host_name("kernel_snake_f32")]] kernel void kernel_snake<float>(constant ggml_metal_kargs_snake &, device const float *, device const float *, device const float *, device float *, uint, uint, uint);
template [[host_name("kernel_snake_f16")]] kernel void kernel_snake<half>(constant ggml_metal_kargs_snake &, device const half *, device const float *, device const float *, device half *, uint, uint, uint);
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_snake_bf16")]] kernel void kernel_snake<bfloat>(constant ggml_metal_kargs_snake &, device const bfloat *, device const float *, device const float *, device bfloat *, uint, uint, uint);
#endif
template<int N>
kernel void kernel_fwht_f32(
constant ggml_metal_kargs_fwht & args,
device const float * src,
device float * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
constexpr int NW = N_SIMDWIDTH;
constexpr int NE = N / NW;
const float scale = 1.0f / sqrt((float) N);
const int sg_per_tg = ntg.x / NW;
const int64_t r = tgpig.x * sg_per_tg + sgitg;
if (r >= args.nrows) {
return;
}
src += r * N;
dst += r * N;
const int lane = tiisg;
float reg[NE];
for (int i = 0; i < NE; i++) {
reg[i] = src[i*NW + lane]*scale;
}
for (int i = 1; i < NW; i *= 2) {
for (int j = 0; j < NE; j++) {
const float val = reg[j];
const float val2 = simd_shuffle_xor(val, i);
reg[j] = (lane & i) == 0 ? val2 + val : val2 - val;
}
}
for (int i = NW; i < N; i *= 2) {
const int step = i / NW;
for (int j = 0; j < NE; j += (2 * step)) {
for (int k = 0; k < step; k++) {
const float x = reg[j + k ];
const float y = reg[j + k + step];
reg[j + k] = x + y;
reg[j + k + step] = x - y;
}
}
}
for (int i = 0; i < NE; i++) {
dst[i*NW + lane] = reg[i];
}
}
typedef decltype(kernel_fwht_f32<64>) kernel_fwht_t;
template [[host_name("kernel_fwht_f32_64")]] kernel kernel_fwht_t kernel_fwht_f32<64>;
template [[host_name("kernel_fwht_f32_128")]] kernel kernel_fwht_t kernel_fwht_f32<128>;
template [[host_name("kernel_fwht_f32_256")]] kernel kernel_fwht_t kernel_fwht_f32<256>;
template [[host_name("kernel_fwht_f32_512")]] kernel kernel_fwht_t kernel_fwht_f32<512>;
kernel void kernel_dsv4_hc_comb_f32(
constant ggml_metal_kargs_dsv4_hc_comb & args,
device const char * mixes,
device const char * scale,
device const char * base,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
constexpr ushort hc = 4;
constexpr ushort comb_offset = 2*hc;
const int it = tgpig.x*ntg.y + sgitg;
if (it >= args.n_tokens) {
return;
}
float scale_lane = 0.0f;
if (tiisg == 0) {
scale_lane = *(device const float *) (scale + 2*args.nb_s0);
}
const float scale_comb = simd_shuffle(scale_lane, 0);
float v = 0.0f;
if (tiisg < hc*hc) {
v = *(device const float *) (mixes + (comb_offset + tiisg)*args.nb_m0 + it*args.nb_m1)*scale_comb
+ *(device const float *) (base + (comb_offset + tiisg)*args.nb_b0);
}
// Softmax across destinations (the four contiguous lanes for each source).
float vmax = max(v, simd_shuffle_xor(v, 1));
vmax = max(vmax, simd_shuffle_xor(vmax, 2));
v = exp(v - vmax);
float sum = v + simd_shuffle_xor(v, 1);
sum += simd_shuffle_xor(sum, 2);
v = v/sum + args.eps;
// Normalize columns: equal destination indices are four lanes apart.
sum = v + simd_shuffle_xor(v, 4);
sum += simd_shuffle_xor(sum, 8);
v /= sum + args.eps;
for (int i = 1; i < args.n_iter; ++i) {
sum = v + simd_shuffle_xor(v, 1);
sum += simd_shuffle_xor(sum, 2);
v /= sum + args.eps;
sum = v + simd_shuffle_xor(v, 4);
sum += simd_shuffle_xor(sum, 8);
v /= sum + args.eps;
}
if (tiisg < hc*hc) {
const ushort idst = tiisg & 3;
const ushort isrc = tiisg >> 2;
*(device float *) (dst + idst*args.nb_d0 + isrc*args.nb_d1 + it*args.nb_d2) = v;
}
}
kernel void kernel_dsv4_hc_pre_f32(
constant ggml_metal_kargs_dsv4_hc_pre & args,
device const char * x,
device const char * weights,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
constexpr ushort hc = 4;
const int it = tgpig.y;
const int i0 = ((int) tgpig.x*ntg.y + sgitg)*32 + tiisg;
float weight_lane = 0.0f;
if (tiisg < hc) {
weight_lane = *(device const float *) (weights + tiisg*args.nb_w0 + it*args.nb_w1);
}
float w[hc];
FOR_UNROLL (ushort ih = 0; ih < hc; ++ih) {
w[ih] = simd_shuffle(weight_lane, ih);
}
if (i0 >= args.n_embd) {
return;
}
device const char * xb = x + i0*args.nb_x0 + it*args.nb_x2;
float result = 0.0f;
FOR_UNROLL (ushort ih = 0; ih < hc; ++ih) {
result = fma(*(device const float *) (xb + ih*args.nb_x1), w[ih], result);
}
*(device float *) (dst + i0*args.nb_d0 + it*args.nb_d1) = result;
}
kernel void kernel_dsv4_hc_post_f32(
constant ggml_metal_kargs_dsv4_hc_post & args,
device const char * x,
device const char * residual,
device const char * post,
device const char * comb,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
constexpr ushort hc = 4;
const int it = tgpig.y;
const int i0 = ((int) tgpig.x*ntg.y + sgitg)*32 + tiisg;
float coeff_lane = 0.0f;
if (tiisg < hc) {
coeff_lane = *(device const float *) (post + tiisg*args.nb_p0 + it*args.nb_p1);
} else if (tiisg < hc + hc*hc) {
const ushort idx = tiisg - hc;
const ushort idst = idx & 3;
const ushort isrc = idx >> 2;
coeff_lane = *(device const float *) (comb + idst*args.nb_c0 + isrc*args.nb_c1 + it*args.nb_c2);
}
float post_reg[hc];
float comb_reg[hc][hc];
FOR_UNROLL (ushort idst = 0; idst < hc; ++idst) {
post_reg[idst] = simd_shuffle(coeff_lane, idst);
}
FOR_UNROLL (ushort isrc = 0; isrc < hc; ++isrc) {
FOR_UNROLL (ushort idst = 0; idst < hc; ++idst) {
comb_reg[isrc][idst] = simd_shuffle(coeff_lane, hc + idst + hc*isrc);
}
}
if (i0 >= args.n_embd) {
return;
}
const float xv = *(device const float *) (x + i0*args.nb_x0 + it*args.nb_x1);
float result[hc];
FOR_UNROLL (ushort idst = 0; idst < hc; ++idst) {
result[idst] = xv*post_reg[idst];
}
device const char * rb = residual + i0*args.nb_r0 + it*args.nb_r2;
FOR_UNROLL (ushort isrc = 0; isrc < hc; ++isrc) {
const float rv = *(device const float *) (rb + isrc*args.nb_r1);
FOR_UNROLL (ushort idst = 0; idst < hc; ++idst) {
result[idst] = fma(rv, comb_reg[isrc][idst], result[idst]);
}
}
FOR_UNROLL (ushort idst = 0; idst < hc; ++idst) {
*(device float *) (dst + i0*args.nb_d0 + idst*args.nb_d1 + it*args.nb_d2) = result[idst];
}
}
+842
View File
@@ -0,0 +1,842 @@
#include "common.h"
#include "dequantize.h"
constant bool FC_mul_mm_bc_inp [[function_constant(FC_MUL_MM + 0)]];
constant bool FC_mul_mm_bc_out [[function_constant(FC_MUL_MM + 1)]];
constant short FC_mul_mm_ne12 [[function_constant(FC_MUL_MM + 2)]];
constant short FC_mul_mm_ne13 [[function_constant(FC_MUL_MM + 3)]];
constant short FC_mul_mm_r2 [[function_constant(FC_MUL_MM + 4)]];
constant short FC_mul_mm_r3 [[function_constant(FC_MUL_MM + 5)]];
// each block_q contains 16*nl weights
#ifdef GGML_METAL_HAS_TENSOR
template<
typename SA, typename SA_4x4, typename SA_8x8,
typename SB, typename SB_2x4, typename SB_8x8,
typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread SA_4x4 &),
typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm(
constant ggml_metal_kargs_mul_mm & args,
device const char * srcA,
device const char * srcB,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig [[threadgroup_position_in_grid]],
ushort tiitg [[thread_index_in_threadgroup]],
ushort sgitg [[simdgroup_index_in_threadgroup]]) {
(void) sgitg;
// Matrix dimensions: A(M,K) x B(K,N) -> C(M,N)
const int K = args.ne00;
const int M = args.ne0;
const int N = args.ne1;
// Batch dimension handling
const int im = tgpig.z;
const int i12 = im % FC_mul_mm_ne12;
const int i13 = im / FC_mul_mm_ne12;
// Batch offsets for srcA and srcB
const uint64_t offset0 = (i12/FC_mul_mm_r2)*args.nb02 + (i13/FC_mul_mm_r3)*args.nb03;
// Tile dimensions
constexpr int NRB = SZ_SIMDGROUP * N_MM_BLOCK_X * N_MM_SIMD_GROUP_X;
constexpr int NRA = SZ_SIMDGROUP * N_MM_BLOCK_Y * N_MM_SIMD_GROUP_Y;
// Tile offsets in output matrix
const int ra = tgpig.y * NRA;
const int rb = tgpig.x * NRB;
// Threadgroup memory for dequantized A tile only
threadgroup SA * sa = (threadgroup SA *)(shmem);
// Work-item count for A loading
constexpr int A_WORK_ITEMS = NRA * N_MM_NK;
constexpr int NUM_THREADS = N_SIMDWIDTH * N_MM_SIMD_GROUP_X * N_MM_SIMD_GROUP_Y;
// tA wraps threadgroup memory
auto tA = tensor(sa, dextents<int32_t, 2>(N_MM_NK_TOTAL, NRA));
// tB wraps device memory directly
device T1 * ptrB = (device T1 *)(srcB + args.nb12*i12 + args.nb13*i13);
const int strideB = args.nb11 / sizeof(T1);
auto tB = tensor(ptrB, dextents<int32_t, 2>(K, N), array<int, 2>({1, strideB}));
// Configure matmul operation
mpp::tensor_ops::matmul2d<
mpp::tensor_ops::matmul2d_descriptor(
NRB, NRA, N_MM_NK_TOTAL, false, true, true,
mpp::tensor_ops::matmul2d_descriptor::mode::multiply_accumulate),
execution_simdgroups<N_MM_SIMD_GROUP_X * N_MM_SIMD_GROUP_Y>> mm;
auto cT = mm.get_destination_cooperative_tensor<decltype(tB), decltype(tA), float>();
// Accumulate partial results over K dimension
for (int loop_k = 0; loop_k < K; loop_k += N_MM_NK_TOTAL) {
// === PHASE 1: Dequantization of A into threadgroup memory ===
for (int work = tiitg; work < A_WORK_ITEMS; work += NUM_THREADS) {
const int row = work / N_MM_NK;
const int k_chunk = work % N_MM_NK;
const int k_pos = loop_k + k_chunk * 16;
const short k_base = k_chunk * 16;
// Bounds check: skip device read if row is out of matrix bounds
if (ra + row < M) {
if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
// Element-wise reads when K is not aligned (nb01 not aligned for half4x4/float4x4).
// MSL spec Table 2.5: half4x4 requires 8-byte alignment. When K is odd,
// nb01 = K*2 is not 8-byte aligned, so odd-row pointers are misaligned.
// Mirrors the legacy kernel's existing guard.
device const T0 * row_ptr = (device const T0 *)(srcA + args.nb01 * (ra + row) + offset0);
FOR_UNROLL (short i = 0; i < 16; i++) {
sa[row * N_MM_NK_TOTAL + (k_base + i)] = (k_pos + i < K) ? (SA) row_ptr[k_pos + i] : (SA)0;
}
} else {
const int block_idx = k_pos / (16 * nl);
const short il = (k_pos / 16) % nl;
device const block_q * row_ptr = (device const block_q *)(srcA + args.nb01 * (ra + row) + offset0);
SA_4x4 temp_a;
dequantize_func(row_ptr + block_idx, il, temp_a);
FOR_UNROLL (short i = 0; i < 16; i++) {
// Zero-pad A for K positions beyond valid range (handles partial K iterations)
sa[row * N_MM_NK_TOTAL + (k_base + i)] = (k_pos + i < K) ? temp_a[i/4][i%4] : (SA)0;
}
}
} else {
// Zero-pad rows beyond matrix bounds
FOR_UNROLL (short i = 0; i < 16; i++) {
sa[row * N_MM_NK_TOTAL + (k_base + i)] = (SA)0;
}
}
}
threadgroup_barrier(mem_flags::mem_threadgroup);
// === PHASE 2: Tensor matmul ===
auto mA = tA.slice(0, 0);
auto mB = tB.slice(loop_k, rb);
mm.run(mB, mA, cT);
threadgroup_barrier(mem_flags::mem_threadgroup);
}
// Store result tile to output matrix (with batch offset)
// cT.store handles bounds checking via tD's extents (M, N)
device float * dstBatch = (device float *)dst + im * N * M;
auto tD = tensor(dstBatch, dextents<int32_t, 2>(M, N), array<int, 2>({1, M}));
cT.store(tD.slice(ra, rb));
}
#else
template<
typename S0, typename S0_4x4, typename S0_8x8,
typename S1, typename S1_2x4, typename S1_8x8,
typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread S0_4x4 &),
typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm(
constant ggml_metal_kargs_mul_mm & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiitg[[thread_index_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
threadgroup S0 * sa = (threadgroup S0 *)(shmem);
threadgroup S1 * sb = (threadgroup S1 *)(shmem + 4096);
constexpr int NR0 = 64;
constexpr int NR1 = 32;
constexpr int NK = 32;
constexpr int NL0 = NK/16;
constexpr int NL1 = NK/8;
const int im = tgpig.z;
const int r0 = tgpig.y*NR0;
const int r1 = tgpig.x*NR1;
// if this block is of 64x32 shape or smaller
const short nr0 = (args.ne0 - r0 < NR0) ? (args.ne0 - r0) : NR0;
const short nr1 = (args.ne1 - r1 < NR1) ? (args.ne1 - r1) : NR1;
// a thread shouldn't load data outside of the matrix
const short lr0 = ((short)tiitg/NL0) < nr0 ? ((short)tiitg/NL0) : nr0 - 1; // 0 .. 63
const short lr1 = ((short)tiitg/NL1) < nr1 ? ((short)tiitg/NL1) : nr1 - 1; // 0 .. 31
const short il0 = (tiitg % NL0);
short il = il0;
const int i12 = im % FC_mul_mm_ne12;
const int i13 = im / FC_mul_mm_ne12;
const uint64_t offset0 = (i12/FC_mul_mm_r2)*args.nb02 + (i13/FC_mul_mm_r3)*args.nb03;
const short offset1 = il0/nl;
device const block_q * x = (device const block_q *)(src0 + args.nb01*(r0 + lr0) + offset0) + offset1;
const short iy = 8*(tiitg % NL1);
device const T1 * y = (device const T1 *)(src1
+ args.nb13*i13
+ args.nb12*i12
+ args.nb11*(r1 + lr1)
+ args.nb10*iy);
S0_8x8 ma[4];
S1_8x8 mb[2];
simdgroup_float8x8 mc[8];
for (short i = 0; i < 8; i++){
mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
}
for (int loop_k = 0; loop_k < args.ne00; loop_k += NK) {
// load data and store to threadgroup memory
if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
threadgroup_barrier(mem_flags::mem_threadgroup);
// no need for dequantization
for (short i = 0; i < 16; i++) {
const short sx = 2*il0 + i/8;
const short sy = (tiitg/NL0)/8;
//const short lx = i%8;
//const short ly = (tiitg/NL0)%8;
const short lx = (tiitg/NL0)%8;
const short ly = i%8;
const short ib = 8*sx + sy;
*(sa + 64*ib + 8*ly + lx) = loop_k + 16*il + i < args.ne00 ? *((device T0 *) x + i) : 0;
}
} else {
S0_4x4 temp_a;
dequantize_func(x, il, temp_a);
threadgroup_barrier(mem_flags::mem_threadgroup);
FOR_UNROLL (short i = 0; i < 16; i++) {
const short sx = 2*il0 + i/8;
const short sy = (tiitg/NL0)/8;
//const short lx = i%8;
//const short ly = (tiitg/NL0)%8;
const short lx = (tiitg/NL0)%8;
const short ly = i%8;
const short ib = 8*sx + sy;
// NOTE: this is massively slower.. WTF?
//sa[64*ib + 8*ly + lx] = temp_a[i/4][i%4];
*(sa + 64*ib + 8*ly + lx) = temp_a[i/4][i%4];
}
}
if (FC_mul_mm_bc_inp) {
for (short i = 0; i < 8; ++i) {
const short sx = (tiitg%NL1);
const short sy = (tiitg/NL1)/8;
const short lx = i;
const short ly = (tiitg/NL1)%8;
//const short lx = (tiitg/NL1)%8;
//const short ly = i;
const short ib = 4*sx + sy;
*(sb + 64*ib + 8*ly + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
}
} else {
const short sx = (tiitg%NL1);
const short sy = (tiitg/NL1)/8;
//const short dx = sx;
//const short dy = sy;
const short ly = (tiitg/NL1)%8;
const short ib = 4*sx + sy;
*(threadgroup S1_2x4 *)(sb + 64*ib + 8*ly) = (S1_2x4)(*((device T1_2x4 *) y));
}
il = (il + 2 < nl) ? il + 2 : il % 2;
x = (il < 2) ? x + (2 + nl - 1)/nl : x;
y += NK;
threadgroup_barrier(mem_flags::mem_threadgroup);
// load matrices from threadgroup memory and conduct outer products
threadgroup const S0 * lsma = (sa + 4*64*(sgitg%2));
threadgroup const S1 * lsmb = (sb + 2*64*(sgitg/2));
FOR_UNROLL (short ik = 0; ik < NK/8; ik++) {
simdgroup_barrier(mem_flags::mem_none);
FOR_UNROLL (short i = 0; i < 4; i++) {
simdgroup_load(ma[i], lsma + 64*i, 8, 0, false);
}
simdgroup_barrier(mem_flags::mem_none);
FOR_UNROLL (short i = 0; i < 2; i++) {
simdgroup_load(mb[i], lsmb + 64*i, 8, 0, false);
}
simdgroup_barrier(mem_flags::mem_none);
FOR_UNROLL (short i = 0; i < 8; i++){
simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
}
lsma += 8*64;
lsmb += 4*64;
}
}
if (!FC_mul_mm_bc_out || (r0 + NR0 <= args.ne0 && r1 + NR1 <= args.ne1)) {
// if no bounds checks on the output are needed, we can directly write to device memory
device float * C = (device float *) dst +
(r0 + 32*(sgitg & 1)) + \
(r1 + 16*(sgitg >> 1)) * args.ne0 + im*args.ne1*args.ne0;
for (short i = 0; i < 8; i++) {
simdgroup_store(mc[i], C + 8*(i%4) + 8*args.ne0*(i/4), args.ne0, 0, false);
}
} else {
// block is smaller than 64x32, we should avoid writing data outside of the matrix
threadgroup_barrier(mem_flags::mem_threadgroup);
threadgroup float * temp_str = ((threadgroup float *) shmem) + 32*(sgitg&1) + (16*(sgitg >> 1))*NR0;
for (short i = 0; i < 8; i++) {
simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*NR0*(i/4), NR0, 0, false);
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (sgitg == 0) {
for (int j = tiitg; j < nr1; j += NR1) {
device float * D = (device float *) dst + r0 + (r1 + j)*args.ne0 + im*args.ne1*args.ne0;
device float4 * D4 = (device float4 *) D;
threadgroup float * C = temp_str + (j*NR0);
threadgroup float4 * C4 = (threadgroup float4 *) C;
int i = 0;
for (; i < nr0/4; i++) {
*(D4 + i) = *(C4 + i);
}
i *= 4;
for (; i < nr0; i++) {
*(D + i) = *(C + i);
}
}
}
}
}
#endif // GGML_METAL_HAS_TENSOR
template<short ne20> // n_expert_used
kernel void kernel_mul_mm_id_map0(
constant ggml_metal_kargs_mul_mm_id_map0 & args,
device const char * src2,
device char * htpe,
device char * hids,
threadgroup char * shmem [[threadgroup(0)]],
ushort tpitg[[thread_position_in_threadgroup]],
ushort ntg[[threads_per_threadgroup]]) {
const short ide = tpitg; // expert id
uint32_t n_all = 0;
device int32_t * ids_i32 = (device int32_t *) hids + ide*args.ne21;
for (int i21 = 0; i21 < args.ne21; i21 += ntg) { // n_tokens
if (i21 + tpitg < args.ne21) {
device const int32_t * src2_i32 = (device const int32_t *) (src2 + (i21 + tpitg)*args.nb21);
threadgroup uint16_t * sids = (threadgroup uint16_t *) shmem + tpitg*ne20;
#pragma unroll(ne20)
for (short i20 = 0; i20 < ne20; i20++) {
sids[i20] = src2_i32[i20];
}
}
threadgroup_barrier(mem_flags::mem_threadgroup);
for (short t = 0; t < ntg; t++) {
if (i21 + t >= args.ne21) {
break;
}
threadgroup const uint16_t * sids = (threadgroup const uint16_t *) shmem + t*ne20;
short sel = 0;
#pragma unroll(ne20)
for (short i20 = 0; i20 < ne20; i20++) {
sel += (sids[i20] == ide)*(i20 + 1);
}
ids_i32[n_all] = (i21 + t)*ne20 + sel - 1;
n_all += sel > 0;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
}
device uint32_t * tpe_u32 = (device uint32_t *) (htpe);
tpe_u32[ide] = n_all;
}
typedef decltype(kernel_mul_mm_id_map0<1>) kernel_mul_mm_id_map0_t;
template [[host_name("kernel_mul_mm_id_map0_ne20_1" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<1>;
template [[host_name("kernel_mul_mm_id_map0_ne20_2" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<2>;
template [[host_name("kernel_mul_mm_id_map0_ne20_4" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<4>;
template [[host_name("kernel_mul_mm_id_map0_ne20_5" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<5>;
template [[host_name("kernel_mul_mm_id_map0_ne20_6" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<6>;
template [[host_name("kernel_mul_mm_id_map0_ne20_8" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<8>;
template [[host_name("kernel_mul_mm_id_map0_ne20_10")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<10>;
template [[host_name("kernel_mul_mm_id_map0_ne20_16")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<16>;
template [[host_name("kernel_mul_mm_id_map0_ne20_22")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<22>;
template<typename S0, typename S0_4x4, typename S0_8x8, typename S1, typename S1_2x4, typename S1_8x8, typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread S0_4x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm_id(
constant ggml_metal_kargs_mul_mm_id & args,
device const char * src0,
device const char * src1,
device const char * htpe,
device const char * hids,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiitg[[thread_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
threadgroup S0 * sa = (threadgroup S0 *)(shmem);
threadgroup S1 * sb = (threadgroup S1 *)(shmem + 4096);
#ifdef GGML_METAL_HAS_TENSOR
threadgroup float * sc = (threadgroup float *)(shmem);
#endif
constexpr int NR0 = 64;
constexpr int NR1 = 32;
constexpr int NK = 32;
constexpr int NL0 = NK/16;
constexpr int NL1 = NK/8;
const int im = tgpig.z; // expert
const int r0 = tgpig.y*NR0;
const int r1 = tgpig.x*NR1;
device const uint32_t * tpe_u32 = (device const uint32_t *) (htpe);
device const int32_t * ids_i32 = (device const int32_t *) (hids);
const int32_t neh1 = tpe_u32[im];
if (r1 >= neh1) {
return;
}
// if this block is of 64x32 shape or smaller
const short nr0 = (args.ne0 - r0 < NR0) ? (args.ne0 - r0) : NR0;
const short nr1 = ( neh1 - r1 < NR1) ? ( neh1 - r1) : NR1;
// a thread shouldn't load data outside of the matrix
const short lr0 = ((short)tiitg/NL0) < nr0 ? ((short)tiitg/NL0) : nr0 - 1; // 0 .. 63
const short lr1 = ((short)tiitg/NL1) < nr1 ? ((short)tiitg/NL1) : nr1 - 1; // 0 .. 31
const short il0 = (tiitg % NL0);
short il = il0;
const int id = ids_i32[im*args.ne21 + r1 + lr1];
const short i11 = (id % args.ne20) % args.ne11;
const short i12 = (id / args.ne20);
const short i13 = 0;
const uint64_t offset0 = im*args.nb02 + i13*args.nb03;
const short offset1 = il0/nl;
device const block_q * x = (device const block_q *)(src0 + args.nb01*(r0 + lr0) + offset0) + offset1;
const short iy = 8*(tiitg % NL1);
device const T1 * y = (device const T1 *)(src1
+ args.nb13*i13
+ args.nb12*i12
+ args.nb11*i11
+ args.nb10*iy);
#ifndef GGML_METAL_HAS_TENSOR
S0_8x8 ma[4];
S1_8x8 mb[2];
simdgroup_float8x8 mc[8];
for (short i = 0; i < 8; i++){
mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
}
#else
auto tA = tensor<threadgroup S0, dextents<int32_t, 2>, tensor_inline>(sa, dextents<int32_t, 2>(NK, NR0));
auto tB = tensor<threadgroup S1, dextents<int32_t, 2>, tensor_inline>(sb, dextents<int32_t, 2>(NR1, NK ));
mpp::tensor_ops::matmul2d<
mpp::tensor_ops::matmul2d_descriptor(NR1, NR0, NK, false, true, false, mpp::tensor_ops::matmul2d_descriptor::mode::multiply_accumulate),
execution_simdgroups<4>> mm;
auto cT = mm.get_destination_cooperative_tensor<decltype(tA), decltype(tB), float>();
#endif
for (int loop_k = 0; loop_k < args.ne00; loop_k += NK) {
#ifndef GGML_METAL_HAS_TENSOR
// load data and store to threadgroup memory
if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
threadgroup_barrier(mem_flags::mem_threadgroup);
// no need for dequantization
for (short i = 0; i < 16; i++) {
const short sx = 2*il0 + i/8;
const short sy = (tiitg/NL0)/8;
//const short lx = i%8;
//const short ly = (tiitg/NL0)%8;
const short lx = (tiitg/NL0)%8;
const short ly = i%8;
const short ib = 8*sx + sy;
*(sa + 64*ib + 8*ly + lx) = loop_k + 16*il + i < args.ne00 ? (S0) *((device T0 *) x + i) : (S0) 0;
}
} else {
S0_4x4 temp_a;
dequantize_func(x, il, temp_a);
threadgroup_barrier(mem_flags::mem_threadgroup);
FOR_UNROLL (short i = 0; i < 16; i++) {
const short sx = 2*il0 + i/8;
const short sy = (tiitg/NL0)/8;
//const short lx = i%8;
//const short ly = (tiitg/NL0)%8;
const short lx = (tiitg/NL0)%8;
const short ly = i%8;
const short ib = 8*sx + sy;
// NOTE: this is massively slower.. WTF?
//sa[64*ib + 8*ly + lx] = temp_a[i/4][i%4];
*(sa + 64*ib + 8*ly + lx) = temp_a[i/4][i%4];
}
}
if (FC_mul_mm_bc_inp) {
for (short i = 0; i < 8; ++i) {
const short sx = (tiitg%NL1);
const short sy = (tiitg/NL1)/8;
const short lx = i;
const short ly = (tiitg/NL1)%8;
//const short lx = (tiitg/NL1)%8;
//const short ly = i;
const short ib = 4*sx + sy;
*(sb + 64*ib + 8*ly + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
}
} else {
const short sx = (tiitg%NL1);
const short sy = (tiitg/NL1)/8;
//const short dx = sx;
//const short dy = sy;
const short ly = (tiitg/NL1)%8;
const short ib = 4*sx + sy;
*(threadgroup S1_2x4 *)(sb + 64*ib + 8*ly) = (S1_2x4)(*((device T1_2x4 *) y));
}
#else
// load data and store to threadgroup memory
if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
threadgroup_barrier(mem_flags::mem_threadgroup);
// no need for dequantization
for (short i = 0; i < 16; i++) {
const short sx = 2*il0 + i/8;
const short sy = (tiitg/NL0)/8;
const short lx = i%8;
const short ly = (tiitg/NL0)%8;
//const short lx = (tiitg/NL0)%8;
//const short ly = i%8;
*(sa + NK*(8*sy + ly) + 8*sx + lx) = loop_k + 16*il + i < args.ne00 ? *((device T0 *) x + i) : 0;
}
} else {
S0_4x4 temp_a;
dequantize_func(x, il, temp_a);
threadgroup_barrier(mem_flags::mem_threadgroup);
FOR_UNROLL (short i = 0; i < 16; i++) {
const short sx = 2*il0 + i/8;
const short sy = (tiitg/NL0)/8;
const short lx = i%8;
const short ly = (tiitg/NL0)%8;
//const short lx = (tiitg/NL0)%8;
//const short ly = i%8;
*(sa + NK*(8*sy + ly) + 8*sx + lx) = temp_a[i/4][i%4];
}
}
if (FC_mul_mm_bc_inp) {
for (short i = 0; i < 8; ++i) {
const short sx = (tiitg%NL1);
const short sy = (tiitg/NL1)/8;
const short lx = i;
const short ly = (tiitg/NL1)%8;
//const short lx = (tiitg/NL1)%8;
//const short ly = i;
*(sb + NK*(8*sy + ly) + 8*sx + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
}
} else {
const short sx = (tiitg%NL1);
const short sy = (tiitg/NL1)/8;
//const short lx = i;
const short ly = (tiitg/NL1)%8;
//const short lx = (tiitg/NL1)%8;
//const short ly = i;
*(threadgroup S1_2x4 *)(sb + NK*(8*sy + ly) + 8*sx) = (S1_2x4)(*((device T1_2x4 *) y));
}
#endif
il = (il + 2 < nl) ? il + 2 : il % 2;
x = (il < 2) ? x + (2 + nl - 1)/nl : x;
y += NK;
threadgroup_barrier(mem_flags::mem_threadgroup);
#ifndef GGML_METAL_HAS_TENSOR
// load matrices from threadgroup memory and conduct outer products
threadgroup const S0 * lsma = (sa + 4*64*(sgitg%2));
threadgroup const S1 * lsmb = (sb + 2*64*(sgitg/2));
FOR_UNROLL (short ik = 0; ik < NK/8; ik++) {
simdgroup_barrier(mem_flags::mem_none);
FOR_UNROLL (short i = 0; i < 4; i++) {
simdgroup_load(ma[i], lsma + 64*i, 8, 0, false);
}
simdgroup_barrier(mem_flags::mem_none);
FOR_UNROLL (short i = 0; i < 2; i++) {
simdgroup_load(mb[i], lsmb + 64*i, 8, 0, false);
}
simdgroup_barrier(mem_flags::mem_none);
FOR_UNROLL (short i = 0; i < 8; i++){
simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
}
lsma += 8*64;
lsmb += 4*64;
}
#else
auto sA = tA.slice(0, 0);
auto sB = tB.slice(0, 0);
mm.run(sB, sA, cT);
#endif
}
// block is smaller than 64x32, we should avoid writing data outside of the matrix
threadgroup_barrier(mem_flags::mem_threadgroup);
#ifdef GGML_METAL_HAS_TENSOR
auto tC = tensor<threadgroup float, dextents<int32_t, 2>, tensor_inline>(sc, dextents<int32_t, 2>(NR0, NR1));
cT.store(tC);
#else
threadgroup float * temp_str = ((threadgroup float *) shmem) + 32*(sgitg&1) + (16*(sgitg >> 1))*NR0;
for (short i = 0; i < 8; i++) {
simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*NR0*(i/4), NR0, 0, false);
}
#endif
threadgroup_barrier(mem_flags::mem_threadgroup);
for (short j = sgitg; j < nr1; j += 4) {
const int id = ids_i32[im*args.ne21 + r1 + j];
const short ide = id % args.ne20;
const short idt = id / args.ne20;
device float * D = (device float *) dst + r0 + ide*args.ne0 + idt*args.ne1*args.ne0;
device float4 * D4 = (device float4 *) D;
threadgroup float * C = (threadgroup float *) shmem + j*NR0;
threadgroup float4 * C4 = (threadgroup float4 *) C;
int i = tiisg;
for (; i < nr0/4; i += 32) {
*(D4 + i) = *(C4 + i);
}
i = (4*(nr0/4)) + tiisg;
for (; i < nr0; i += 32) {
*(D + i) = *(C + i);
}
}
}
//
// matrix-matrix multiplication
//
typedef decltype(kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, float, float2x4>) mul_mm_t;
template [[host_name("kernel_mul_mm_f32_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_f16_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, half4x4, 1, dequantize_f16, half, half4x4, float, float2x4>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_mul_mm_bf16_f32")]] kernel mul_mm_t kernel_mul_mm<bfloat, bfloat4x4, simdgroup_bfloat8x8, bfloat, bfloat2x4, simdgroup_bfloat8x8, bfloat4x4, 1, dequantize_bf16, bfloat, bfloat4x4, float, float2x4>;
#endif
template [[host_name("kernel_mul_mm_q1_0_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q1_0, 8, dequantize_q1_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q2_0_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_0, 4, dequantize_q2_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q4_0_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_0, 2, dequantize_q4_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q4_1_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_1, 2, dequantize_q4_1, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q5_0_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_0, 2, dequantize_q5_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q5_1_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_1, 2, dequantize_q5_1, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q8_0_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0, 2, dequantize_q8_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_mxfp4_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_mxfp4, 2, dequantize_mxfp4, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q2_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q3_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q3_K, QK_NL, dequantize_q3_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q4_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K, QK_NL, dequantize_q4_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q5_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_K, QK_NL, dequantize_q5_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_q6_K_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q6_K, QK_NL, dequantize_q6_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_iq2_xxs_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_iq2_xs_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xs, QK_NL, dequantize_iq2_xs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_iq3_xxs_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_xxs, QK_NL, dequantize_iq3_xxs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_iq3_s_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_s, QK_NL, dequantize_iq3_s, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_iq2_s_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_s, QK_NL, dequantize_iq2_s, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_iq1_s_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_s, QK_NL, dequantize_iq1_s, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_iq1_m_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_m, QK_NL, dequantize_iq1_m, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_iq4_nl_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_nl, 2, dequantize_iq4_nl, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_iq4_xs_f32")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_xs, QK_NL, dequantize_iq4_xs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_f32_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_f16_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, half4x4, 1, dequantize_f16, half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q1_0_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q1_0, 8, dequantize_q1_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q2_0_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_0, 4, dequantize_q2_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q4_0_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_0, 2, dequantize_q4_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q4_1_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_1, 2, dequantize_q4_1, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q5_0_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_0, 2, dequantize_q5_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q5_1_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_1, 2, dequantize_q5_1, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q8_0_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0, 2, dequantize_q8_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_mxfp4_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_mxfp4, 2, dequantize_mxfp4, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q2_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q3_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q3_K, QK_NL, dequantize_q3_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q4_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K, QK_NL, dequantize_q4_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q5_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_K, QK_NL, dequantize_q5_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_q6_K_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q6_K, QK_NL, dequantize_q6_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_iq2_xxs_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_iq2_xs_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xs, QK_NL, dequantize_iq2_xs, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_iq3_xxs_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_xxs, QK_NL, dequantize_iq3_xxs, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_iq3_s_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_s, QK_NL, dequantize_iq3_s, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_iq2_s_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_s, QK_NL, dequantize_iq2_s, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_iq1_s_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_s, QK_NL, dequantize_iq1_s, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_iq1_m_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_m, QK_NL, dequantize_iq1_m, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_iq4_nl_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_nl, 2, dequantize_iq4_nl, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_iq4_xs_f16")]] kernel mul_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_xs, QK_NL, dequantize_iq4_xs, float, float4x4, half, half2x4>;
//
// indirect matrix-matrix multiplication
//
typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, float, float2x4>) mul_mm_id;
template [[host_name("kernel_mul_mm_id_f32_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_f16_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, half4x4, 1, dequantize_f16, half, half4x4, float, float2x4>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_mul_mm_id_bf16_f32")]] kernel mul_mm_id kernel_mul_mm_id<bfloat, bfloat4x4, simdgroup_bfloat8x8, bfloat, bfloat2x4, simdgroup_bfloat8x8, bfloat4x4, 1, dequantize_bf16, bfloat, bfloat4x4, float, float2x4>;
#endif
template [[host_name("kernel_mul_mm_id_q1_0_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q1_0, 8, dequantize_q1_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q2_0_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_0, 4, dequantize_q2_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q4_0_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_0, 2, dequantize_q4_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q4_1_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_1, 2, dequantize_q4_1, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q5_0_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_0, 2, dequantize_q5_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q5_1_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_1, 2, dequantize_q5_1, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q8_0_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0, 2, dequantize_q8_0, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_mxfp4_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_mxfp4, 2, dequantize_mxfp4, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q3_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q3_K, QK_NL, dequantize_q3_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K, QK_NL, dequantize_q4_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q5_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_K, QK_NL, dequantize_q5_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q6_K_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q6_K, QK_NL, dequantize_q6_K, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xs, QK_NL, dequantize_iq2_xs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq3_xxs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_xxs, QK_NL, dequantize_iq3_xxs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq3_s_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_s, QK_NL, dequantize_iq3_s, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq2_s_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_s, QK_NL, dequantize_iq2_s, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq1_s_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_s, QK_NL, dequantize_iq1_s, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq1_m_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_m, QK_NL, dequantize_iq1_m, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq4_nl_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_nl, 2, dequantize_iq4_nl, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq4_xs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_xs, QK_NL, dequantize_iq4_xs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_f32_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, float4x4, 1, dequantize_f32, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_f16_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, half4x4, 1, dequantize_f16, half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q1_0_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q1_0, 8, dequantize_q1_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q2_0_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_0, 4, dequantize_q2_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q4_0_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_0, 2, dequantize_q4_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q4_1_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_1, 2, dequantize_q4_1, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q5_0_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_0, 2, dequantize_q5_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q5_1_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_1, 2, dequantize_q5_1, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q8_0_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0, 2, dequantize_q8_0, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_mxfp4_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_mxfp4, 2, dequantize_mxfp4, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q3_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q3_K, QK_NL, dequantize_q3_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K, QK_NL, dequantize_q4_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q5_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q5_K, QK_NL, dequantize_q5_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q6_K_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q6_K, QK_NL, dequantize_q6_K, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xs_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xs, QK_NL, dequantize_iq2_xs, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq3_xxs_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_xxs, QK_NL, dequantize_iq3_xxs, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq3_s_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq3_s, QK_NL, dequantize_iq3_s, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq2_s_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_s, QK_NL, dequantize_iq2_s, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq1_s_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_s, QK_NL, dequantize_iq1_s, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq1_m_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq1_m, QK_NL, dequantize_iq1_m, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq4_nl_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_nl, 2, dequantize_iq4_nl, float, float4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq4_xs_f16")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq4_xs, QK_NL, dequantize_iq4_xs, float, float4x4, half, half2x4>;
File diff suppressed because it is too large Load Diff
+308
View File
@@ -0,0 +1,308 @@
#include "common.h"
// F == 1 : norm (no fuse)
// F == 2 : norm + mul
// F == 3 : norm + mul + add
template <typename T, short F>
kernel void kernel_norm_fuse_impl(
constant ggml_metal_kargs_norm & args,
device const char * src0,
device const char * src1_0,
device const char * src1_1,
device char * dst,
threadgroup float * shmem_f32 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
if (sgitg == 0) {
shmem_f32[tiisg] = 0.0f;
}
const int i01 = tgpig.x;
const int i02 = tgpig.y;
const int i03 = tgpig.z;
device const T * x = (device const T *) (src0 + i03*args.nbf3[0] + i02*args.nbf2[0] + i01*args.nbf1[0]);
device const T * f0 = (device const T *) (src1_0 + (i03%args.nef3[1])*args.nbf3[1] + (i02%args.nef2[1])*args.nbf2[1] + (i01%args.nef1[1])*args.nbf1[1]);
device const T * f1 = (device const T *) (src1_1 + (i03%args.nef3[2])*args.nbf3[2] + (i02%args.nef2[2])*args.nbf2[2] + (i01%args.nef1[2])*args.nbf1[2]);
T sumft(0.0f);
float sumf = 0.0f;
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
sumft += x[i00];
}
sumf = dot(sumft, T(1.0f));
sumf = simd_sum(sumf);
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shmem_f32[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sumf = shmem_f32[tiisg];
sumf = simd_sum(sumf);
const float mean = sumf/args.ne00;
device T * y = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1);
sumf = 0.0f;
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
y[i00] = x[i00] - mean;
sumf += dot(y[i00], y[i00]);
}
sumf = simd_sum(sumf);
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shmem_f32[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sumf = shmem_f32[tiisg];
sumf = simd_sum(sumf);
const float variance = sumf/args.ne00;
const float scale = 1.0f/sqrt(variance + args.eps);
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
if (F == 1) {
y[i00] = (y[i00]*scale);
}
if (F == 2) {
y[i00] = (y[i00]*scale)*f0[i00];
}
if (F == 3) {
y[i00] = (y[i00]*scale)*f0[i00] + f1[i00];
}
}
}
typedef decltype(kernel_norm_fuse_impl<float4, 1>) kernel_norm_fuse_t;
template [[host_name("kernel_norm_f32")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float, 1>;
template [[host_name("kernel_norm_mul_f32")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float, 2>;
template [[host_name("kernel_norm_mul_add_f32")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float, 3>;
template [[host_name("kernel_norm_f32_4")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float4, 1>;
template [[host_name("kernel_norm_mul_f32_4")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float4, 2>;
template [[host_name("kernel_norm_mul_add_f32_4")]] kernel kernel_norm_fuse_t kernel_norm_fuse_impl<float4, 3>;
// F == 1 : rms_norm (no fuse)
// F == 2 : rms_norm + mul
// F == 3 : rms_norm + mul + add
template <typename T, short F>
kernel void kernel_rms_norm_fuse_impl(
constant ggml_metal_kargs_norm & args,
device const char * src0,
device const char * src1_0,
device const char * src1_1,
device char * dst,
threadgroup float * shmem_f32 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
if (sgitg == 0) {
shmem_f32[tiisg] = 0.0f;
}
const int i01 = tgpig.x;
const int i02 = tgpig.y;
const int i03 = tgpig.z;
device const T * x = (device const T *) (src0 + i03*args.nbf3[0] + i02*args.nbf2[0] + i01*args.nbf1[0]);
device const T * f0 = (device const T *) (src1_0 + (i03%args.nef3[1])*args.nbf3[1] + (i02%args.nef2[1])*args.nbf2[1] + (i01%args.nef1[1])*args.nbf1[1]);
device const T * f1 = (device const T *) (src1_1 + (i03%args.nef3[2])*args.nbf3[2] + (i02%args.nef2[2])*args.nbf2[2] + (i01%args.nef1[2])*args.nbf1[2]);
float sumf = 0.0f;
// parallel sum
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
sumf += dot(x[i00], x[i00]);
}
sumf = simd_sum(sumf);
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shmem_f32[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sumf = shmem_f32[tiisg];
sumf = simd_sum(sumf);
const float mean = sumf/args.ne00;
const float scale = 1.0f/sqrt(mean + args.eps);
device T * y = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1);
for (int i00 = tpitg.x; i00 < args.ne00_t; i00 += ntg.x) {
if (F == 1) {
y[i00] = (x[i00]*scale);
}
if (F == 2) {
y[i00] = (x[i00]*scale)*f0[i00];
}
if (F == 3) {
y[i00] = (x[i00]*scale)*f0[i00] + f1[i00];
}
}
}
typedef decltype(kernel_rms_norm_fuse_impl<float4, 1>) kernel_rms_norm_fuse_t;
template [[host_name("kernel_rms_norm_f32")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float, 1>;
template [[host_name("kernel_rms_norm_mul_f32")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float, 2>;
template [[host_name("kernel_rms_norm_mul_add_f32")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float, 3>;
template [[host_name("kernel_rms_norm_f32_4")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float4, 1>;
template [[host_name("kernel_rms_norm_mul_f32_4")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float4, 2>;
template [[host_name("kernel_rms_norm_mul_add_f32_4")]] kernel kernel_rms_norm_fuse_t kernel_rms_norm_fuse_impl<float4, 3>;
template <typename T0, typename T>
kernel void kernel_l2_norm_impl(
constant ggml_metal_kargs_l2_norm & args,
device const char * src0,
device char * dst,
threadgroup float * shmem_f32 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig.z;
const int i02 = tgpig.y;
const int i01 = tgpig.x;
if (sgitg == 0) {
shmem_f32[tiisg] = 0.0f;
}
device const T0 * x = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
device T * y = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1);
float sumf = 0.0f;
// parallel sum
for (int i00 = tpitg.x; i00 < args.ne00; i00 += ntg.x) {
sumf += dot(x[i00], x[i00]);
}
sumf = simd_sum(sumf);
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shmem_f32[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sumf = shmem_f32[tiisg];
sumf = simd_sum(sumf);
const float scale = 1.0f/max(sqrt(sumf), args.eps);
for (int i00 = tpitg.x; i00 < args.ne00; i00 += ntg.x) {
y[i00] = x[i00] * scale;
}
}
typedef decltype(kernel_l2_norm_impl<float, float>) kernel_l2_norm_t;
template [[host_name("kernel_l2_norm_f32_f32")]] kernel kernel_l2_norm_t kernel_l2_norm_impl<float, float>;
template [[host_name("kernel_l2_norm_f32_f32_4")]] kernel kernel_l2_norm_t kernel_l2_norm_impl<float4, float4>;
kernel void kernel_group_norm_f32(
constant ggml_metal_kargs_group_norm & args,
device const float * src0,
device float * dst,
threadgroup float * buf [[threadgroup(0)]],
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint sgitg[[simdgroup_index_in_threadgroup]],
uint tiisg[[thread_index_in_simdgroup]],
uint ntg[[threads_per_threadgroup]]) {
const int64_t ne = args.ne00*args.ne01*args.ne02;
const int64_t gs = args.ne00*args.ne01*((args.ne02 + args.ngrp - 1) / args.ngrp);
int start = tgpig * gs;
int end = start + gs;
start += tpitg;
if (end >= ne) {
end = ne;
}
float tmp = 0.0f; // partial sum for thread in warp
for (int j = start; j < end; j += ntg) {
tmp += src0[j];
}
threadgroup_barrier(mem_flags::mem_threadgroup);
tmp = simd_sum(tmp);
if (ntg > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = 0.0f;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = tmp;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
tmp = buf[tiisg];
tmp = simd_sum(tmp);
}
const float mean = tmp / gs;
tmp = 0.0f;
for (int j = start; j < end; j += ntg) {
float xi = src0[j] - mean;
dst[j] = xi;
tmp += xi * xi;
}
tmp = simd_sum(tmp);
if (ntg > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = 0.0f;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = tmp;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
tmp = buf[tiisg];
tmp = simd_sum(tmp);
}
const float variance = tmp / gs;
const float scale = 1.0f/sqrt(variance + args.eps);
for (int j = start; j < end; j += ntg) {
dst[j] *= scale;
}
}
+148
View File
@@ -0,0 +1,148 @@
#include "common.h"
kernel void kernel_pool_2d_max_f32(
constant ggml_metal_kargs_pool_2d & args,
device const float * src0,
device float * dst,
uint gid[[thread_position_in_grid]]) {
if (gid >= args.np) {
return;
}
const int idx = gid;
const int I_HW = args.IH * args.IW;
const int O_HW = args.OH * args.OW;
const int nc = idx / O_HW;
const int cur_oh = idx % O_HW / args.OW;
const int cur_ow = idx % O_HW % args.OW;
device const float * i_ptr = src0 + nc * I_HW;
device float * o_ptr = dst + nc * O_HW;
const int start_h = cur_oh * args.s1 - args.p1;
const int bh = MAX(0, start_h);
const int eh = MIN(args.IH, start_h + args.k1);
const int start_w = cur_ow * args.s0 - args.p0;
const int bw = MAX(0, start_w);
const int ew = MIN(args.IW, start_w + args.k0);
float res = -INFINITY;
for (int i = bh; i < eh; i += 1) {
for (int j = bw; j < ew; j += 1) {
res = MAX(res, i_ptr[i * args.IW + j]);
}
}
o_ptr[cur_oh * args.OW + cur_ow] = res;
}
kernel void kernel_pool_2d_avg_f32(
constant ggml_metal_kargs_pool_2d & args,
device const float * src0,
device float * dst,
uint gid[[thread_position_in_grid]]) {
if (gid >= args.np) {
return;
}
const int idx = gid;
const int I_HW = args.IH * args.IW;
const int O_HW = args.OH * args.OW;
const int nc = idx / O_HW;
const int cur_oh = idx % O_HW / args.OW;
const int cur_ow = idx % O_HW % args.OW;
device const float * i_ptr = src0 + nc * I_HW;
device float * o_ptr = dst + nc * O_HW;
const int start_h = cur_oh * args.s1 - args.p1;
const int bh = MAX(0, start_h);
const int eh = MIN(args.IH, start_h + args.k1);
const int start_w = cur_ow * args.s0 - args.p0;
const int bw = MAX(0, start_w);
const int ew = MIN(args.IW, start_w + args.k0);
// const float scale = 1. / ((eh - bh) * (ew - bw));
const float scale = 1. / (args.k0 * args.k1);
float res = 0;
for (int i = bh; i < eh; i += 1) {
for (int j = bw; j < ew; j += 1) {
float cur = i_ptr[i * args.IW + j];
res += cur * scale;
}
}
o_ptr[cur_oh * args.OW + cur_ow] = res;
}
kernel void kernel_pool_1d_max_f32(
constant ggml_metal_kargs_pool_1d & args,
device const float * src,
device float * dst,
uint gid [[thread_position_in_grid]]
) {
if (gid >= args.np) {
return;
}
const int ow = (int)gid % args.OW;
const int row = (int)gid / args.OW;
const int base = ow * args.s0 - args.p0;
float acc = -INFINITY;
const int src_off = row * args.IW;
const int dst_off = row * args.OW;
for (int ki = 0; ki < args.k0; ++ki) {
int j = base + ki;
if (j < 0 || j >= args.IW){
continue;
}
float v = src[src_off + j];
acc = max(acc, v);
}
dst[dst_off + ow] = acc;
}
kernel void kernel_pool_1d_avg_f32(
constant ggml_metal_kargs_pool_1d & args,
device const float * src,
device float * dst,
uint gid [[thread_position_in_grid]]
) {
if (gid >= args.np) {
return;
}
const int ow = (int)gid % args.OW;
const int row = (int)gid / args.OW;
const int base = ow * args.s0 - args.p0;
float acc = 0.0f;
int cnt = 0;
const int src_off = row * args.IW;
const int dst_off = row * args.OW;
for (int ki = 0; ki < args.k0; ++ki) {
const int j = base + ki;
if (j < 0 || j >= args.IW) {
continue;
}
acc += src[src_off + j];
cnt += 1;
}
dst[dst_off + ow] = (cnt > 0) ? (acc / (float)cnt) : 0.0f;
}
+234
View File
@@ -0,0 +1,234 @@
#pragma once
#include "common.h"
void quantize_q1_0(device const float * src, device block_q1_0 & dst) {
float sum_abs = 0.0f;
for (int j = 0; j < QK1_0; j++) {
sum_abs += fabs(src[j]);
}
dst.d = sum_abs / QK1_0;
for (int j = 0; j < QK1_0 / 8; j++) {
dst.qs[j] = 0;
}
for (int j = 0; j < QK1_0; j++) {
if (src[j] >= 0.0f) {
dst.qs[j / 8] |= (1 << (j % 8));
}
}
}
void quantize_q2_0(device const float * src, device block_q2_0 & dst) {
float amax = 0.0f;
for (int j = 0; j < QK2_0; j++) {
float a = fabs(src[j]);
if (a > amax) amax = a;
}
const float d = amax;
dst.d = d;
const float id = d > 0.0f ? 1.0f / d : 0.0f;
for (int j = 0; j < QK2_0 / 4; j++) {
dst.qs[j] = 0;
}
for (int j = 0; j < QK2_0; j++) {
int q = (int)round(src[j] * id) + 1;
q = max(0, min(3, q));
dst.qs[j / 4] |= (q << (2 * (j % 4)));
}
}
void quantize_q4_0(device const float * src, device block_q4_0 & dst) {
#pragma METAL fp math_mode(safe)
float amax = 0.0f; // absolute max
float max = 0.0f;
for (int j = 0; j < QK4_0; j++) {
const float v = src[j];
if (amax < fabs(v)) {
amax = fabs(v);
max = v;
}
}
const float d = max / -8;
const float id = d ? 1.0f/d : 0.0f;
dst.d = d;
for (int j = 0; j < QK4_0/2; ++j) {
const float x0 = src[0 + j]*id;
const float x1 = src[QK4_0/2 + j]*id;
const uint8_t xi0 = MIN(15, (int8_t)(x0 + 8.5f));
const uint8_t xi1 = MIN(15, (int8_t)(x1 + 8.5f));
dst.qs[j] = xi0;
dst.qs[j] |= xi1 << 4;
}
}
void quantize_q4_1(device const float * src, device block_q4_1 & dst) {
#pragma METAL fp math_mode(safe)
float min = FLT_MAX;
float max = -FLT_MAX;
for (int j = 0; j < QK4_1; j++) {
const float v = src[j];
if (min > v) min = v;
if (max < v) max = v;
}
const float d = (max - min) / ((1 << 4) - 1);
const float id = d ? 1.0f/d : 0.0f;
dst.d = d;
dst.m = min;
for (int j = 0; j < QK4_1/2; ++j) {
const float x0 = (src[0 + j] - min)*id;
const float x1 = (src[QK4_1/2 + j] - min)*id;
const uint8_t xi0 = MIN(15, (int8_t)(x0 + 0.5f));
const uint8_t xi1 = MIN(15, (int8_t)(x1 + 0.5f));
dst.qs[j] = xi0;
dst.qs[j] |= xi1 << 4;
}
}
void quantize_q5_0(device const float * src, device block_q5_0 & dst) {
#pragma METAL fp math_mode(safe)
float amax = 0.0f; // absolute max
float max = 0.0f;
for (int j = 0; j < QK5_0; j++) {
const float v = src[j];
if (amax < fabs(v)) {
amax = fabs(v);
max = v;
}
}
const float d = max / -16;
const float id = d ? 1.0f/d : 0.0f;
dst.d = d;
uint32_t qh = 0;
for (int j = 0; j < QK5_0/2; ++j) {
const float x0 = src[0 + j]*id;
const float x1 = src[QK5_0/2 + j]*id;
const uint8_t xi0 = MIN(31, (int8_t)(x0 + 16.5f));
const uint8_t xi1 = MIN(31, (int8_t)(x1 + 16.5f));
dst.qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_0/2);
}
thread const uint8_t * qh8 = (thread const uint8_t *)&qh;
for (int j = 0; j < 4; ++j) {
dst.qh[j] = qh8[j];
}
}
void quantize_q5_1(device const float * src, device block_q5_1 & dst) {
#pragma METAL fp math_mode(safe)
float max = src[0];
float min = src[0];
for (int j = 1; j < QK5_1; j++) {
const float v = src[j];
min = v < min ? v : min;
max = v > max ? v : max;
}
const float d = (max - min) / 31;
const float id = d ? 1.0f/d : 0.0f;
dst.d = d;
dst.m = min;
uint32_t qh = 0;
for (int j = 0; j < QK5_1/2; ++j) {
const float x0 = (src[0 + j] - min)*id;
const float x1 = (src[QK5_1/2 + j] - min)*id;
const uint8_t xi0 = (uint8_t)(x0 + 0.5f);
const uint8_t xi1 = (uint8_t)(x1 + 0.5f);
dst.qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_1/2);
}
thread const uint8_t * qh8 = (thread const uint8_t *)&qh;
for (int j = 0; j < 4; ++j) {
dst.qh[j] = qh8[j];
}
}
void quantize_q8_0(device const float * src, device block_q8_0 & dst) {
#pragma METAL fp math_mode(safe)
float amax = 0.0f; // absolute max
for (int j = 0; j < QK8_0; j++) {
const float v = src[j];
amax = MAX(amax, fabs(v));
}
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
dst.d = d;
for (int j = 0; j < QK8_0; ++j) {
const float x0 = src[j]*id;
dst.qs[j] = round(x0);
}
}
void quantize_iq4_nl(device const float * src, device block_iq4_nl & dst) {
#pragma METAL fp math_mode(safe)
float amax = 0.0f; // absolute max
float max = 0.0f;
for (int j = 0; j < QK4_NL; j++) {
const float v = src[j];
if (amax < fabs(v)) {
amax = fabs(v);
max = v;
}
}
const float d = max / kvalues_iq4nl_f[0];
const float id = d ? 1.0f/d : 0.0f;
float sumqx = 0, sumq2 = 0;
for (int j = 0; j < QK4_NL/2; ++j) {
const float x0 = src[0 + j]*id;
const float x1 = src[QK4_NL/2 + j]*id;
const uint8_t xi0 = best_index_int8(16, kvalues_iq4nl_f, x0);
const uint8_t xi1 = best_index_int8(16, kvalues_iq4nl_f, x1);
dst.qs[j] = xi0 | (xi1 << 4);
const float v0 = kvalues_iq4nl_f[xi0];
const float v1 = kvalues_iq4nl_f[xi1];
const float w0 = src[0 + j]*src[0 + j];
const float w1 = src[QK4_NL/2 + j]*src[QK4_NL/2 + j];
sumqx += w0*v0*src[j] + w1*v1*src[QK4_NL/2 + j];
sumq2 += w0*v0*v0 + w1*v1*v1;
}
dst.d = sumq2 > 0 ? sumqx/sumq2 : d;
}
+393
View File
@@ -0,0 +1,393 @@
#include "common.h"
#include "dequantize.h"
#include "quantize.h"
template<typename T0, typename T1>
kernel void kernel_cpy_t_t(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int32_t i03 = tgpig[2];
const int32_t i02 = tgpig[1];
const int32_t i01 = ntg[1] == 1 ? tgpig[0]%args.ne01 : tgpig[0]*ntg[1] + tpitg.y;
const int32_t iw0 = ntg[1] == 1 ? tgpig[0]/args.ne01 : 0;
if (i01 >= args.ne01) {
return;
}
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int32_t i3 = n/(args.ne2*args.ne1*args.ne0);
const int32_t i2 = (n - i3*args.ne2*args.ne1*args.ne0)/(args.ne1*args.ne0);
const int32_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0)/args.ne0;
const int32_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0);
device T1 * dst_data = (device T1 *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int32_t i00 = iw0*ntg[0] + tpitg.x; i00 < args.ne00;) {
device const T0 * src = (device T0 *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
dst_data[i00] = (T1) src[0];
break;
}
}
typedef decltype(kernel_cpy_t_t<float, float>) kernel_cpy_t;
template [[host_name("kernel_cpy_f32_f32")]] kernel kernel_cpy_t kernel_cpy_t_t<float, float>;
template [[host_name("kernel_cpy_f32_f16")]] kernel kernel_cpy_t kernel_cpy_t_t<float, half>;
template [[host_name("kernel_cpy_f32_i32")]] kernel kernel_cpy_t kernel_cpy_t_t<float, int32_t>;
template [[host_name("kernel_cpy_i32_f32")]] kernel kernel_cpy_t kernel_cpy_t_t<int32_t, float>;
template [[host_name("kernel_cpy_i32_i32")]] kernel kernel_cpy_t kernel_cpy_t_t<int32_t, int32_t>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_cpy_f32_bf16")]] kernel kernel_cpy_t kernel_cpy_t_t<float, bfloat>;
#endif
template [[host_name("kernel_cpy_f16_f32")]] kernel kernel_cpy_t kernel_cpy_t_t<half, float>;
template [[host_name("kernel_cpy_f16_f16")]] kernel kernel_cpy_t kernel_cpy_t_t<half, half>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_cpy_bf16_f32")]] kernel kernel_cpy_t kernel_cpy_t_t<bfloat, float>;
template [[host_name("kernel_cpy_bf16_bf16")]] kernel kernel_cpy_t kernel_cpy_t_t<bfloat, bfloat>;
#endif
template<short QK,
typename block_q,
void (*quantize_func)(device const float *, device block_q &)>
kernel void kernel_cpy_f32_q(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int32_t i03 = tgpig[2];
const int32_t i02 = tgpig[1];
const int32_t i01 = ntg[1] == 1 ? tgpig[0]%args.ne01 : tgpig[0]*ntg[1] + tpitg.y;
const int32_t iw0 = ntg[1] == 1 ? tgpig[0]/args.ne01 : 0;
if (i01 >= args.ne01) {
return;
}
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int32_t i3 = n / (args.ne2*args.ne1*args.ne0);
const int32_t i2 = (n - i3*args.ne2*args.ne1*args.ne0) / (args.ne1*args.ne0);
const int32_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0) / args.ne0;
const int32_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0)/QK;
device block_q * dst_data = (device block_q *)(dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int32_t i00 = iw0*ntg[0] + tpitg.x; i00 < args.nk0;) {
device const float * src = (device const float *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + (i00*QK)*args.nb00);
quantize_func(src, dst_data[i00]);
break;
}
}
typedef decltype(kernel_cpy_f32_q<QK8_0, block_q8_0, quantize_q8_0>) cpy_f_q_t;
template [[host_name("kernel_cpy_f32_q8_0")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK8_0, block_q8_0, quantize_q8_0>;
template [[host_name("kernel_cpy_f32_q1_0")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK1_0, block_q1_0, quantize_q1_0>;
template [[host_name("kernel_cpy_f32_q2_0")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK2_0, block_q2_0, quantize_q2_0>;
template [[host_name("kernel_cpy_f32_q4_0")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK4_0, block_q4_0, quantize_q4_0>;
template [[host_name("kernel_cpy_f32_q4_1")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK4_1, block_q4_1, quantize_q4_1>;
template [[host_name("kernel_cpy_f32_q5_0")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK5_0, block_q5_0, quantize_q5_0>;
template [[host_name("kernel_cpy_f32_q5_1")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK5_1, block_q5_1, quantize_q5_1>;
template [[host_name("kernel_cpy_f32_iq4_nl")]] kernel cpy_f_q_t kernel_cpy_f32_q<QK4_NL, block_iq4_nl, quantize_iq4_nl>;
template<typename T4x4, typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread T4x4 &)>
kernel void kernel_cpy_q_f32(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int32_t i03 = tgpig[2];
const int32_t i02 = tgpig[1];
const int32_t i01 = ntg[1] == 1 ? tgpig[0]%args.ne01 : tgpig[0]*ntg[1] + tpitg.y;
const int32_t iw0 = ntg[1] == 1 ? tgpig[0]/args.ne01 : 0;
if (i01 >= args.ne01) {
return;
}
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int32_t i3 = n/(args.ne2*args.ne1*args.ne0);
const int32_t i2 = (n - i3*args.ne2*args.ne1*args.ne0)/(args.ne1*args.ne0);
const int32_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0)/args.ne0;
const int32_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0);
device const block_q * src_data = (device const block_q *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
device T4x4 * dst_data = (device T4x4 *)(dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int32_t i00 = iw0*ntg[0] + tpitg.x; i00 < args.nk0;) {
T4x4 temp;
dequantize_func(src_data + i00/nl, i00%nl, temp);
dst_data[i00] = temp;
break;
}
}
typedef decltype(kernel_cpy_q_f32<float4x4, block_q4_0, 2, dequantize_q4_0>) cpy_q_f_t;
template [[host_name("kernel_cpy_q1_0_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q1_0, 8, dequantize_q1_0>;
template [[host_name("kernel_cpy_q2_0_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q2_0, 4, dequantize_q2_0>;
template [[host_name("kernel_cpy_q4_0_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q4_0, 2, dequantize_q4_0>;
template [[host_name("kernel_cpy_q4_1_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q4_1, 2, dequantize_q4_1>;
template [[host_name("kernel_cpy_q5_0_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q5_0, 2, dequantize_q5_0>;
template [[host_name("kernel_cpy_q5_1_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q5_1, 2, dequantize_q5_1>;
template [[host_name("kernel_cpy_q8_0_f32")]] kernel cpy_q_f_t kernel_cpy_q_f32<float4x4, block_q8_0, 2, dequantize_q8_0>;
template [[host_name("kernel_cpy_q1_0_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q1_0, 8, dequantize_q1_0>;
template [[host_name("kernel_cpy_q2_0_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q2_0, 4, dequantize_q2_0>;
template [[host_name("kernel_cpy_q4_0_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q4_0, 2, dequantize_q4_0>;
template [[host_name("kernel_cpy_q4_1_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q4_1, 2, dequantize_q4_1>;
template [[host_name("kernel_cpy_q5_0_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q5_0, 2, dequantize_q5_0>;
template [[host_name("kernel_cpy_q5_1_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q5_1, 2, dequantize_q5_1>;
template [[host_name("kernel_cpy_q8_0_f16")]] kernel cpy_q_f_t kernel_cpy_q_f32<half4x4, block_q8_0, 2, dequantize_q8_0>;
template<typename T>
kernel void kernel_concat(
constant ggml_metal_kargs_concat & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i3 = tgpig.z;
const int i2 = tgpig.y;
const int i1 = ntg.y == 1 ? tgpig.x : tgpig.x*ntg.y + tpitg.y;
if (i1 >= args.ne1) {
return;
}
int o[4] = {0, 0, 0, 0};
o[args.dim] = args.dim == 0 ? args.ne00 : (args.dim == 1 ? args.ne01 : (args.dim == 2 ? args.ne02 : args.ne03));
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
device const T * x;
if (i0 < args.ne00 && i1 < args.ne01 && i2 < args.ne02 && i3 < args.ne03) {
x = (device const T *)(src0 + (i3 )*args.nb03 + (i2 )*args.nb02 + (i1 )*args.nb01 + (i0 )*args.nb00);
} else {
x = (device const T *)(src1 + (i3 - o[3])*args.nb13 + (i2 - o[2])*args.nb12 + (i1 - o[1])*args.nb11 + (i0 - o[0])*args.nb10);
}
device T * y = (device T *)(dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
*y = *x;
}
}
typedef decltype(kernel_concat<float>) kernel_concat_t;
template [[host_name("kernel_concat_f32")]] kernel kernel_concat_t kernel_concat<float>;
template [[host_name("kernel_concat_f16")]] kernel kernel_concat_t kernel_concat<half>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_concat_bf16")]] kernel kernel_concat_t kernel_concat<bfloat>;
#endif
template [[host_name("kernel_concat_i8")]] kernel kernel_concat_t kernel_concat<char>;
template [[host_name("kernel_concat_i16")]] kernel kernel_concat_t kernel_concat<short>;
template [[host_name("kernel_concat_i32")]] kernel kernel_concat_t kernel_concat<int>;
template [[host_name("kernel_concat_i64")]] kernel kernel_concat_t kernel_concat<long>;
template<typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread float4x4 &)>
kernel void kernel_get_rows_q(
constant ggml_metal_kargs_get_rows & args,
device const void * src0,
device const void * src1,
device void * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiitg[[thread_index_in_threadgroup]],
ushort3 ntg [[threads_per_threadgroup]]) {
const int32_t iw0 = tgpig.x/args.ne10;
const int32_t i10 = tgpig.x%args.ne10;
const int32_t i11 = tgpig.y;
const int32_t i12 = tgpig.z;
const int32_t r = ((const device int32_t *) ((const device char *) src1 + i12*args.nb12 + i11*args.nb11 + i10*args.nb10))[0];
const int32_t i02 = i11;
const int32_t i03 = i12;
auto psrc = (device const block_q *) ((const device char *) src0 + i03*args.nb03 + i02*args.nb02 + r*args.nb01);
auto pdst = (device float4x4 *) (( device char *) dst + i12*args.nb3 + i11*args.nb2 + i10*args.nb1);
for (int ind = iw0*ntg.x + tiitg; ind < args.ne00t;) {
float4x4 temp;
dequantize_func(psrc + ind/nl, ind%nl, temp);
pdst[ind] = temp;
break;
}
}
template<typename T0, typename T>
kernel void kernel_get_rows_f(
constant ggml_metal_kargs_get_rows & args,
device const void * src0,
device const void * src1,
device void * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiitg[[thread_index_in_threadgroup]],
ushort3 ntg [[threads_per_threadgroup]]) {
const int32_t iw0 = tgpig.x/args.ne10;
const int32_t i10 = tgpig.x%args.ne10;
const int32_t i11 = tgpig.y;
const int32_t i12 = tgpig.z;
const int32_t r = ((const device int32_t *) ((const device char *) src1 + i12*args.nb12 + i11*args.nb11 + i10*args.nb10))[0];
const int32_t i02 = i11;
const int32_t i03 = i12;
auto psrc = (const device T0 *) ((const device char *) src0 + i03*args.nb03 + i02*args.nb02 + r*args.nb01);
auto pdst = ( device T *) (( device char *) dst + i12*args.nb3 + i11*args.nb2 + i10*args.nb1);
for (int ind = iw0*ntg.x + tiitg; ind < args.ne00t;) {
pdst[ind] = psrc[ind];
break;
}
}
typedef decltype(kernel_get_rows_f<float, float>) get_rows_f_t;
template [[host_name("kernel_get_rows_f32")]] kernel get_rows_f_t kernel_get_rows_f<float, float>;
template [[host_name("kernel_get_rows_f16")]] kernel get_rows_f_t kernel_get_rows_f<half, float>;
template [[host_name("kernel_get_rows_i32")]] kernel get_rows_f_t kernel_get_rows_f<int32_t, int32_t>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_get_rows_bf16")]] kernel get_rows_f_t kernel_get_rows_f<bfloat, float>;
#endif
typedef decltype(kernel_get_rows_q<block_q4_0, 2, dequantize_q4_0>) get_rows_q_t;
template [[host_name("kernel_get_rows_q1_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q1_0, 8, dequantize_q1_0>;
template [[host_name("kernel_get_rows_q2_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q2_0, 4, dequantize_q2_0>;
template [[host_name("kernel_get_rows_q4_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q4_0, 2, dequantize_q4_0>;
template [[host_name("kernel_get_rows_q4_1")]] kernel get_rows_q_t kernel_get_rows_q<block_q4_1, 2, dequantize_q4_1>;
template [[host_name("kernel_get_rows_q5_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q5_0, 2, dequantize_q5_0>;
template [[host_name("kernel_get_rows_q5_1")]] kernel get_rows_q_t kernel_get_rows_q<block_q5_1, 2, dequantize_q5_1>;
template [[host_name("kernel_get_rows_q8_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q8_0, 2, dequantize_q8_0>;
template [[host_name("kernel_get_rows_mxfp4")]] kernel get_rows_q_t kernel_get_rows_q<block_mxfp4, 2, dequantize_mxfp4>;
template [[host_name("kernel_get_rows_q2_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q2_K, QK_NL, dequantize_q2_K>;
template [[host_name("kernel_get_rows_q3_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q3_K, QK_NL, dequantize_q3_K>;
template [[host_name("kernel_get_rows_q4_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q4_K, QK_NL, dequantize_q4_K>;
template [[host_name("kernel_get_rows_q5_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q5_K, QK_NL, dequantize_q5_K>;
template [[host_name("kernel_get_rows_q6_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q6_K, QK_NL, dequantize_q6_K>;
template [[host_name("kernel_get_rows_iq2_xxs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq2_xxs, QK_NL, dequantize_iq2_xxs>;
template [[host_name("kernel_get_rows_iq2_xs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq2_xs, QK_NL, dequantize_iq2_xs>;
template [[host_name("kernel_get_rows_iq3_xxs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq3_xxs, QK_NL, dequantize_iq3_xxs>;
template [[host_name("kernel_get_rows_iq3_s")]] kernel get_rows_q_t kernel_get_rows_q<block_iq3_s, QK_NL, dequantize_iq3_s>;
template [[host_name("kernel_get_rows_iq2_s")]] kernel get_rows_q_t kernel_get_rows_q<block_iq2_s, QK_NL, dequantize_iq2_s>;
template [[host_name("kernel_get_rows_iq1_s")]] kernel get_rows_q_t kernel_get_rows_q<block_iq1_s, QK_NL, dequantize_iq1_s>;
template [[host_name("kernel_get_rows_iq1_m")]] kernel get_rows_q_t kernel_get_rows_q<block_iq1_m, QK_NL, dequantize_iq1_m>;
template [[host_name("kernel_get_rows_iq4_nl")]] kernel get_rows_q_t kernel_get_rows_q<block_iq4_nl, 2, dequantize_iq4_nl>;
template [[host_name("kernel_get_rows_iq4_xs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq4_xs, QK_NL, dequantize_iq4_xs>;
template<typename TS, typename TI, typename block_q, void (*quantize_func)(device const float *, device block_q &)>
kernel void kernel_set_rows_q32(
constant ggml_metal_kargs_set_rows & args,
device const void * src0,
device const void * src1,
device float * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint tiitg[[thread_index_in_threadgroup]],
uint3 tptg [[threads_per_threadgroup]]) {
const int32_t i03 = tgpig.z;
const int32_t i02 = tgpig.y;
const int32_t i12 = i03%args.ne12;
const int32_t i11 = i02%args.ne11;
const int32_t i01 = tgpig.x*tptg.y + tiitg/tptg.x;
if (i01 >= args.ne01) {
return;
}
const int32_t i10 = i01;
const TI i1 = ((const device TI *) ((const device char *) src1 + i10*args.nb10 + i11*args.nb11 + i12*args.nb12))[0];
device block_q * dst_row = ( device block_q *) (( device char *) dst + i1*args.nb1 + i02*args.nb2 + i03*args.nb3);
const device TS * src_row = (const device TS *) ((const device char *) src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
for (int ind = tiitg%tptg.x; ind < args.nk0; ind += tptg.x) {
quantize_func(src_row + 32*ind, dst_row[ind]);
}
}
template<typename TS, typename TI, typename TD>
kernel void kernel_set_rows_f(
constant ggml_metal_kargs_set_rows & args,
device const void * src0,
device const void * src1,
device float * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint tiitg[[thread_index_in_threadgroup]],
uint3 tptg [[threads_per_threadgroup]]) {
const int32_t i03 = tgpig.z;
const int32_t i02 = tgpig.y;
const int32_t i12 = i03%args.ne12;
const int32_t i11 = i02%args.ne11;
const int32_t i01 = tgpig.x*tptg.y + tiitg/tptg.x;
if (i01 >= args.ne01) {
return;
}
const int32_t i10 = i01;
const TI i1 = ((const device TI *) ((const device char *) src1 + i10*args.nb10 + i11*args.nb11 + i12*args.nb12))[0];
device TD * dst_row = ( device TD *) (( device char *) dst + i1*args.nb1 + i02*args.nb2 + i03*args.nb3);
const device TS * src_row = (const device TS *) ((const device char *) src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
for (int ind = tiitg%tptg.x; ind < args.nk0; ind += tptg.x) {
dst_row[ind] = (TD) src_row[ind];
}
}
typedef decltype(kernel_set_rows_f<float, int64_t, float>) set_rows_f_t;
template [[host_name("kernel_set_rows_f32_i64_f32")]] kernel set_rows_f_t kernel_set_rows_f<float, int64_t, float>;
template [[host_name("kernel_set_rows_f32_i32_f32")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t, float>;
template [[host_name("kernel_set_rows_f32_i64_f16")]] kernel set_rows_f_t kernel_set_rows_f<float, int64_t, half>;
template [[host_name("kernel_set_rows_f32_i32_f16")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t, half>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_set_rows_f32_i64_bf16")]] kernel set_rows_f_t kernel_set_rows_f<float, int64_t, bfloat>;
template [[host_name("kernel_set_rows_f32_i32_bf16")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t, bfloat>;
#endif
template [[host_name("kernel_set_rows_f16_i64_f16")]] kernel set_rows_f_t kernel_set_rows_f<half, int64_t, half>;
template [[host_name("kernel_set_rows_f16_i32_f16")]] kernel set_rows_f_t kernel_set_rows_f<half, int32_t, half>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_set_rows_bf16_i64_bf16")]] kernel set_rows_f_t kernel_set_rows_f<bfloat, int64_t, bfloat>;
template [[host_name("kernel_set_rows_bf16_i32_bf16")]] kernel set_rows_f_t kernel_set_rows_f<bfloat, int32_t, bfloat>;
#endif
typedef decltype(kernel_set_rows_q32<float, int64_t, block_q8_0, quantize_q8_0>) set_rows_q32_t;
template [[host_name("kernel_set_rows_f32_i64_q8_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q8_0, quantize_q8_0>;
template [[host_name("kernel_set_rows_f32_i32_q8_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q8_0, quantize_q8_0>;
template [[host_name("kernel_set_rows_f32_i64_q4_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q4_0, quantize_q4_0>;
template [[host_name("kernel_set_rows_f32_i32_q4_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q4_0, quantize_q4_0>;
template [[host_name("kernel_set_rows_f32_i64_q4_1")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q4_1, quantize_q4_1>;
template [[host_name("kernel_set_rows_f32_i32_q4_1")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q4_1, quantize_q4_1>;
template [[host_name("kernel_set_rows_f32_i64_q5_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q5_0, quantize_q5_0>;
template [[host_name("kernel_set_rows_f32_i32_q5_0")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q5_0, quantize_q5_0>;
template [[host_name("kernel_set_rows_f32_i64_q5_1")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_q5_1, quantize_q5_1>;
template [[host_name("kernel_set_rows_f32_i32_q5_1")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_q5_1, quantize_q5_1>;
template [[host_name("kernel_set_rows_f32_i64_iq4_nl")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int64_t, block_iq4_nl, quantize_iq4_nl>;
template [[host_name("kernel_set_rows_f32_i32_iq4_nl")]] kernel set_rows_q32_t kernel_set_rows_q32<float, int32_t, block_iq4_nl, quantize_iq4_nl>;
+228
View File
@@ -0,0 +1,228 @@
#include "common.h"
kernel void kernel_op_sum_f32(
constant ggml_metal_kargs_sum & args,
device const float * src0,
device float * dst,
threadgroup float * shmem_f32 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
if (args.np == 0) {
return;
}
// TODO: become function constant
const uint nsg = (ntg.x + 31) / 32;
float sumf = 0;
for (uint64_t i0 = tpitg.x; i0 < args.np; i0 += ntg.x) {
sumf += src0[i0];
}
sumf = simd_sum(sumf);
if (tiisg == 0) {
shmem_f32[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
float total = 0;
if (sgitg == 0) {
float v = 0;
if (tpitg.x < nsg) {
v = shmem_f32[tpitg.x];
}
total = simd_sum(v);
if (tpitg.x == 0) {
dst[0] = total;
}
}
}
constant short FC_sum_rows_op [[function_constant(FC_SUM_ROWS + 0)]];
template <typename T0, typename T>
kernel void kernel_sum_rows_impl(
constant ggml_metal_kargs_sum_rows & args,
device const char * src0,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
#define FC_OP FC_sum_rows_op
const int i3 = tgpig.z;
const int i2 = tgpig.y;
const int i1 = tgpig.x;
threadgroup T0 * shmem_t = (threadgroup T0 *) shmem;
if (sgitg == 0) {
shmem_t[tiisg] = 0.0f;
}
device const T0 * src_row = (device const T0 *) (src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03);
device T * dst_row = (device T *) (dst + i1*args.nb1 + i2*args.nb2 + i3*args.nb3);
T0 sumf = T0(0.0f);
for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
sumf += src_row[i0];
}
sumf = simd_sum(sumf);
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shmem_t[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sumf = shmem_t[tiisg];
sumf = simd_sum(sumf);
if (tpitg.x == 0) {
if (FC_OP == OP_SUM_ROWS_NUM_MEAN) {
if (is_same<float4, T0>::value) {
dst_row[0] = sum(sumf) / (4*args.ne00);
} else {
dst_row[0] = sum(sumf) / args.ne00;
}
} else {
dst_row[0] = sum(sumf);
}
}
#undef FC_OP
}
typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;
template [[host_name("kernel_sum_rows_f32_f32")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float, float>;
template [[host_name("kernel_sum_rows_f32_f32_4")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float4, float>;
template<typename T>
kernel void kernel_cumsum_blk(
constant ggml_metal_kargs_cumsum_blk & args,
device const char * src0,
device char * tmp,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int ib = tgpig[0]/args.ne01;
const int i00 = ib*ntg.x;
const int i01 = tgpig[0]%args.ne01;
const int i02 = tgpig[1];
const int i03 = tgpig[2];
device const float * src0_row = (device const float *) (src0 +
args.nb01*i01 +
args.nb02*i02 +
args.nb03*i03);
threadgroup float * shmem_f32 = (threadgroup float *) shmem;
float v = 0.0f;
if (i00 + tpitg.x < args.ne00) {
v = src0_row[i00 + tpitg.x];
}
float s = simd_prefix_inclusive_sum(v);
if (tiisg == N_SIMDWIDTH - 1) {
shmem_f32[sgitg] = s;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (sgitg == 0) {
shmem_f32[tiisg] = simd_prefix_exclusive_sum(shmem_f32[tiisg]);
}
threadgroup_barrier(mem_flags::mem_threadgroup);
s += shmem_f32[sgitg];
device float * dst_row = (device float *) dst +
args.ne00*i01 +
args.ne00*args.ne01*i02 +
args.ne00*args.ne01*args.ne02*i03;
if (i00 + tpitg.x < args.ne00) {
dst_row[i00 + tpitg.x] = s;
}
if (args.outb && tpitg.x == ntg.x - 1) {
device float * tmp_row = (device float *) tmp +
args.net0*i01 +
args.net0*args.net1*i02 +
args.net0*args.net1*args.net2*i03;
tmp_row[ib] = s;
}
}
typedef decltype(kernel_cumsum_blk<float>) kernel_cumsum_blk_t;
template [[host_name("kernel_cumsum_blk_f32")]] kernel kernel_cumsum_blk_t kernel_cumsum_blk<float>;
template<typename T>
kernel void kernel_cumsum_add(
constant ggml_metal_kargs_cumsum_add & args,
device const char * tmp,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int ib = tgpig[0]/args.ne01;
if (ib == 0) {
return;
}
const int i00 = ib*ntg.x;
const int i01 = tgpig[0]%args.ne01;
const int i02 = tgpig[1];
const int i03 = tgpig[2];
device const float * tmp_row = (device const float *) (tmp +
args.nbt1*i01 +
args.nbt2*i02 +
args.nbt3*i03);
device float * dst_row = (device float *) dst +
args.ne00*i01 +
args.ne00*args.ne01*i02 +
args.ne00*args.ne01*args.ne02*i03;
if (i00 + tpitg.x < args.ne00) {
dst_row[i00 + tpitg.x] += tmp_row[ib - 1];
}
}
typedef decltype(kernel_cumsum_add<float>) kernel_cumsum_add_t;
template [[host_name("kernel_cumsum_add_f32")]] kernel kernel_cumsum_add_t kernel_cumsum_add<float>;
+318
View File
@@ -0,0 +1,318 @@
#include "common.h"
constant bool FC_rope_is_imrope [[function_constant(FC_ROPE + 0)]];
constant bool FC_rope_is_back [[function_constant(FC_ROPE + 1)]];
static float rope_yarn_ramp(const float low, const float high, const int i0) {
const float y = (i0 / 2 - low) / max(0.001f, high - low);
return 1.0f - min(1.0f, max(0.0f, y));
}
// YaRN algorithm based on LlamaYaRNScaledRotaryEmbedding.py from https://github.com/jquesnelle/yarn
// MIT licensed. Copyright (c) 2023 Jeffrey Quesnelle and Bowen Peng.
static void rope_yarn(
float theta_extrap, float freq_scale, float corr_dims[2], int i0, float ext_factor, float mscale,
thread float * cos_theta, thread float * sin_theta) {
// Get n-d rotational scaling corrected for extrapolation
float theta_interp = freq_scale * theta_extrap;
float theta = theta_interp;
if (ext_factor != 0.0f) {
float ramp_mix = rope_yarn_ramp(corr_dims[0], corr_dims[1], i0) * ext_factor;
theta = theta_interp * (1 - ramp_mix) + theta_extrap * ramp_mix;
// Get n-d magnitude scaling corrected for interpolation
mscale *= 1.0f + 0.1f * log(1.0f / freq_scale);
}
*cos_theta = cos(theta) * mscale;
*sin_theta = sin(theta) * mscale;
if (FC_rope_is_back) {
*sin_theta *= -1.0f;
}
}
// Apparently solving `n_rot = 2pi * x * base^((2 * max_pos_emb) / n_dims)` for x, we get
// `corr_fac(n_rot) = n_dims * log(max_pos_emb / (n_rot * 2pi)) / (2 * log(base))`
static float rope_yarn_corr_factor(int n_dims, int n_ctx_orig, float n_rot, float base) {
return n_dims * log(n_ctx_orig / (n_rot * 2 * M_PI_F)) / (2 * log(base));
}
static void rope_yarn_corr_dims(
int n_dims, int n_ctx_orig, float freq_base, float beta_fast, float beta_slow, float dims[2]
) {
// start and end correction dims
dims[0] = max(0.0f, floor(rope_yarn_corr_factor(n_dims, n_ctx_orig, beta_fast, freq_base)));
dims[1] = min(n_dims - 1.0f, ceil(rope_yarn_corr_factor(n_dims, n_ctx_orig, beta_slow, freq_base)));
}
template<typename T>
kernel void kernel_rope_norm(
constant ggml_metal_kargs_rope & args,
device const char * src0,
device const char * src1,
device const char * src2,
device char * dst,
ushort tiitg[[thread_index_in_threadgroup]],
ushort3 tptg [[threads_per_threadgroup]],
uint3 tgpig[[threadgroup_position_in_grid]]) {
const int i3 = tgpig[2];
const int i2 = tgpig[1];
const int i1 = tgpig[0];
float corr_dims[2];
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
device const int32_t * pos = (device const int32_t *) src1;
const float theta_base = (float) pos[i2];
const float inv_ndims = -1.f/args.n_dims;
float cos_theta;
float sin_theta;
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
if (i0 < args.n_dims) {
const int ic = i0/2;
const float theta = theta_base * pow(args.freq_base, inv_ndims*i0);
const float freq_factor = args.src2 ? ((device const float *) src2)[ic] : 1.0f;
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
const float x0 = src[0];
const float x1 = src[1];
dst_data[0] = x0*cos_theta - x1*sin_theta;
dst_data[1] = x0*sin_theta + x1*cos_theta;
} else {
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
dst_data[0] = src[0];
dst_data[1] = src[1];
}
}
}
template<typename T>
kernel void kernel_rope_neox(
constant ggml_metal_kargs_rope & args,
device const char * src0,
device const char * src1,
device const char * src2,
device char * dst,
ushort tiitg[[thread_index_in_threadgroup]],
ushort3 tptg [[threads_per_threadgroup]],
uint3 tgpig[[threadgroup_position_in_grid]]) {
const int i3 = tgpig[2];
const int i2 = tgpig[1];
const int i1 = tgpig[0];
float corr_dims[2];
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
device const int32_t * pos = (device const int32_t *) src1;
const float theta_base = (float) pos[i2];
const float inv_ndims = -1.f/args.n_dims;
float cos_theta;
float sin_theta;
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
if (i0 < args.n_dims) {
const int ic = i0/2;
const float theta = theta_base * pow(args.freq_base, inv_ndims*i0);
const float freq_factor = args.src2 ? ((device const float *) src2)[ic] : 1.0f;
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + ic*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + ic*args.nb0);
const float x0 = src[0];
const float x1 = src[args.n_dims/2];
dst_data[0] = x0*cos_theta - x1*sin_theta;
dst_data[args.n_dims/2] = x0*sin_theta + x1*cos_theta;
} else {
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
dst_data[0] = src[0];
dst_data[1] = src[1];
}
}
}
template<typename T>
kernel void kernel_rope_multi(
constant ggml_metal_kargs_rope & args,
device const char * src0,
device const char * src1,
device const char * src2,
device char * dst,
ushort tiitg[[thread_index_in_threadgroup]],
ushort3 tptg [[threads_per_threadgroup]],
uint3 tgpig[[threadgroup_position_in_grid]]) {
const int i3 = tgpig[2];
const int i2 = tgpig[1];
const int i1 = tgpig[0];
float corr_dims[2];
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
device const int32_t * pos = (device const int32_t *) src1;
const float inv_ndims = -1.f/args.n_dims;
float cos_theta;
float sin_theta;
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
if (i0 < args.n_dims) {
const int ic = i0/2;
// mrope theta calculations
// note: the rest is the same as kernel_rope_neox
const int sect_dims = args.sect_0 + args.sect_1 + args.sect_2 + args.sect_3;
const int sec_w01 = args.sect_0 + args.sect_1; // end of section 1
const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
const int sector = ic % sect_dims;
float theta_base;
if (FC_rope_is_imrope) {
if (sector % 3 == 1 && sector < 3 * args.sect_1) { // h
theta_base = (float) pos[i2 + args.ne02 * 1];
} else if (sector % 3 == 2 && sector < 3 * args.sect_2) { // w
theta_base = (float) pos[i2 + args.ne02 * 2];
} else if (sector % 3 == 0 && sector < 3 * args.sect_0) { // t
theta_base = (float) pos[i2 + args.ne02 * 0];
} else { // e
theta_base = (float) pos[i2 + args.ne02 * 3];
}
} else {
if (sector < args.sect_0) {
theta_base = (float) pos[i2];
} else if (sector < sec_w01) {
theta_base = (float) pos[i2 + args.ne02 * 1];
} else if (sector < sec_w012) {
theta_base = (float) pos[i2 + args.ne02 * 2];
} else {
theta_base = (float) pos[i2 + args.ne02 * 3];
}
}
// end of mrope
const float theta = theta_base * pow(args.freq_base, inv_ndims*i0);
const float freq_factor = args.src2 ? ((device const float *) src2)[ic] : 1.0f;
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + ic*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + ic*args.nb0);
const float x0 = src[0];
const float x1 = src[args.n_dims/2];
dst_data[0] = x0*cos_theta - x1*sin_theta;
dst_data[args.n_dims/2] = x0*sin_theta + x1*cos_theta;
} else {
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
dst_data[0] = src[0];
dst_data[1] = src[1];
}
}
}
template<typename T>
kernel void kernel_rope_vision(
constant ggml_metal_kargs_rope & args,
device const char * src0,
device const char * src1,
device const char * src2,
device char * dst,
ushort tiitg[[thread_index_in_threadgroup]],
ushort3 tptg [[threads_per_threadgroup]],
uint3 tgpig[[threadgroup_position_in_grid]]) {
const int i3 = tgpig[2];
const int i2 = tgpig[1];
const int i1 = tgpig[0];
float corr_dims[2];
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
device const int32_t * pos = (device const int32_t *) src1;
const float inv_ndims = -1.f/args.n_dims;
float cos_theta;
float sin_theta;
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
if (i0 < 2*args.n_dims) { // different from kernel_rope_multi
const int ic = i0/2;
// mrope theta calculations (only support 2 dimensions)
const int sect_dims = args.sect_0 + args.sect_1;
const int sector = ic % sect_dims;
float p;
float theta_base;
if (sector < args.sect_1) {
p = (float) sector;
theta_base = (float) pos[i2];
} else {
p = (float) sector - args.sect_0;
theta_base = (float) pos[i2 + args.ne02];
}
const float theta = theta_base * pow(args.freq_base, 2.0f * inv_ndims * p);
// end of mrope
const float freq_factor = args.src2 ? ((device const float *) src2)[ic] : 1.0f;
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + ic*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + ic*args.nb0);
const float x0 = src[0];
const float x1 = src[args.n_dims]; // different from kernel_rope_multi
dst_data[0] = x0*cos_theta - x1*sin_theta;
dst_data[args.n_dims] = x0*sin_theta + x1*cos_theta; // different from kernel_rope_multi
} else {
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
dst_data[0] = src[0];
dst_data[1] = src[1];
}
}
}
typedef decltype(kernel_rope_norm<float>) kernel_rope_norm_t;
typedef decltype(kernel_rope_neox<float>) kernel_rope_neox_t;
typedef decltype(kernel_rope_multi<float>) kernel_rope_multi_t;
typedef decltype(kernel_rope_vision<float>) kernel_rope_vision_t;
template [[host_name("kernel_rope_norm_f32")]] kernel kernel_rope_norm_t kernel_rope_norm<float>;
template [[host_name("kernel_rope_norm_f16")]] kernel kernel_rope_norm_t kernel_rope_norm<half>;
template [[host_name("kernel_rope_neox_f32")]] kernel kernel_rope_neox_t kernel_rope_neox<float>;
template [[host_name("kernel_rope_neox_f16")]] kernel kernel_rope_neox_t kernel_rope_neox<half>;
template [[host_name("kernel_rope_multi_f32")]] kernel kernel_rope_multi_t kernel_rope_multi<float>;
template [[host_name("kernel_rope_multi_f16")]] kernel kernel_rope_multi_t kernel_rope_multi<half>;
template [[host_name("kernel_rope_vision_f32")]] kernel kernel_rope_vision_t kernel_rope_vision<float>;
template [[host_name("kernel_rope_vision_f16")]] kernel kernel_rope_vision_t kernel_rope_vision<half>;
+223
View File
@@ -0,0 +1,223 @@
#include "common.h"
template<typename T>
kernel void kernel_soft_max(
constant ggml_metal_kargs_soft_max & args,
device const char * src0,
device const char * src1,
device const char * src2,
device char * dst,
threadgroup float * buf [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint sgitg[[simdgroup_index_in_threadgroup]],
uint tiisg[[thread_index_in_simdgroup]],
uint3 tptg[[threads_per_threadgroup]]) {
const int32_t i03 = tgpig.z;
const int32_t i02 = tgpig.y;
const int32_t i01 = tgpig.x;
const int32_t i13 = i03%args.ne13;
const int32_t i12 = i02%args.ne12;
const int32_t i11 = i01;
device const float * psrc0 = (device const float *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
device const T * pmask = src1 != src0 ? (device const T * ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
device const float * psrc2 = src2 != src0 ? (device const float *) (src2) : nullptr;
device float * pdst = (device float *) (dst + i01*args.nb1 + i02*args.nb2 + i03*args.nb3);
float slope = 1.0f;
// ALiBi
if (args.max_bias > 0.0f) {
const int32_t h = i02;
const float base = h < args.n_head_log2 ? args.m0 : args.m1;
const int exp = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;
slope = pow(base, exp);
}
// parallel max
float lmax = psrc2 ? psrc2[i02] : -INFINITY;
for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
}
// find the max value in the block
float max_val = simd_max(lmax);
if (tptg.x > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = -INFINITY;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = max_val;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
max_val = buf[tiisg];
max_val = simd_max(max_val);
}
// parallel sum
float lsum = 0.0f;
for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
const float exp_psrc0 = exp((psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f)) - max_val);
lsum += exp_psrc0;
pdst[i00] = exp_psrc0;
}
// This barrier fixes a failing test
// ref: https://github.com/ggml-org/ggml/pull/621#discussion_r1425156335
threadgroup_barrier(mem_flags::mem_none);
float sum = simd_sum(lsum);
if (tptg.x > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = 0.0f;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = sum;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sum = buf[tiisg];
sum = simd_sum(sum);
}
if (psrc2) {
sum += exp(psrc2[i02] - max_val);
}
const float inv_sum = 1.0f/sum;
for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
pdst[i00] *= inv_sum;
}
}
template<typename T>
kernel void kernel_soft_max_4(
constant ggml_metal_kargs_soft_max & args,
device const char * src0,
device const char * src1,
device const char * src2,
device char * dst,
threadgroup float * buf [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint sgitg[[simdgroup_index_in_threadgroup]],
uint tiisg[[thread_index_in_simdgroup]],
uint3 tptg[[threads_per_threadgroup]]) {
const int32_t i03 = tgpig.z;
const int32_t i02 = tgpig.y;
const int32_t i01 = tgpig.x;
const int32_t i13 = i03%args.ne13;
const int32_t i12 = i02%args.ne12;
const int32_t i11 = i01;
device const float4 * psrc4 = (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
device const T * pmask = src1 != src0 ? (device const T * ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
device const float * psrc2 = src2 != src0 ? (device const float * ) (src2) : nullptr;
device float4 * pdst4 = (device float4 *) (dst + i01*args.nb1 + i02*args.nb2 + i03*args.nb3);
float slope = 1.0f;
if (args.max_bias > 0.0f) {
const int32_t h = i02;
const float base = h < args.n_head_log2 ? args.m0 : args.m1;
const int exp = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;
slope = pow(base, exp);
}
// parallel max
float4 lmax4 = psrc2 ? psrc2[i02] : -INFINITY;
for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
lmax4 = fmax(lmax4, psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f)));
}
const float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3]));
float max_val = simd_max(lmax);
if (tptg.x > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = -INFINITY;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = max_val;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
max_val = buf[tiisg];
max_val = simd_max(max_val);
}
// parallel sum
float4 lsum4 = 0.0f;
for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
const float4 exp_psrc4 = exp((psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f))) - max_val);
lsum4 += exp_psrc4;
pdst4[i00] = exp_psrc4;
}
const float lsum = lsum4[0] + lsum4[1] + lsum4[2] + lsum4[3];
// This barrier fixes a failing test
// ref: https://github.com/ggml-org/ggml/pull/621#discussion_r1425156335
threadgroup_barrier(mem_flags::mem_none);
float sum = simd_sum(lsum);
if (tptg.x > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = 0.0f;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = sum;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sum = buf[tiisg];
sum = simd_sum(sum);
}
if (psrc2) {
sum += exp(psrc2[i02] - max_val);
}
const float inv_sum = 1.0f/sum;
for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
pdst4[i00] *= inv_sum;
}
}
typedef decltype(kernel_soft_max<float>) kernel_soft_max_t;
typedef decltype(kernel_soft_max_4<float4>) kernel_soft_max_4_t;
template [[host_name("kernel_soft_max_f16")]] kernel kernel_soft_max_t kernel_soft_max<half>;
template [[host_name("kernel_soft_max_f32")]] kernel kernel_soft_max_t kernel_soft_max<float>;
template [[host_name("kernel_soft_max_f16_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<half4>;
template [[host_name("kernel_soft_max_f32_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<float4>;
@@ -0,0 +1,75 @@
#include "common.h"
constant short FC_solve_tri_nsg [[function_constant(FC_SOLVE_TRI + 0)]];
constant short FC_solve_tri_n [[function_constant(FC_SOLVE_TRI + 1)]];
constant short FC_solve_tri_k [[function_constant(FC_SOLVE_TRI + 2)]];
kernel void kernel_solve_tri_f32(
constant ggml_metal_kargs_solve_tri & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
ushort3 tgpig[[threadgroup_position_in_grid]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
constexpr short NW = N_SIMDWIDTH;
const short NSG = FC_solve_tri_nsg;
const short N = FC_solve_tri_n;
const short K = FC_solve_tri_k;
const short NP = PAD2(N, NW);
const int32_t i03 = tgpig.z;
const int32_t i02 = tgpig.y;
const int32_t i01 = tgpig.x*NSG + sgitg;
threadgroup float * sh0 = (threadgroup float *) shmem;
device const float * src0_ptr = (device const float *)(src0 + i02 * args.nb02 + i03 * args.nb03) + sgitg*N;
device const float * src1_ptr = (device const float *)(src1 + i02 * args.nb12 + i03 * args.nb13) + i01;
device float * dst_ptr = (device float *)(dst + i02 * args.nb2 + i03 * args.nb3) + i01;
for (short rr = 0; rr < N; rr += NSG) {
threadgroup_barrier(mem_flags::mem_threadgroup);
{
threadgroup float * sh0_cur = sh0 + sgitg*NP;
for (short t = 0; t*NW < N; ++t) {
const short idx = t*NW + tiisg;
sh0_cur[idx] = src0_ptr[idx];
}
src0_ptr += NSG*N;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (i01 >= args.ne10) {
continue;
}
for (short ir = 0; ir < NSG && rr + ir < N; ++ir) {
const short r = rr + ir;
threadgroup float * sh0_cur = sh0 + ir*NP;
float sum = 0.0f;
for (short t = 0; t*NW < r; ++t) {
const short idx = t*NW + tiisg;
sum += sh0_cur[idx] * dst_ptr[idx*K] * (idx < r);
}
sum = simd_sum(sum);
if (tiisg == 0) {
const float diag = sh0_cur[r];
dst_ptr[r*K] = (src1_ptr[r*K] - sum) / diag;
}
}
}
}
+279
View File
@@ -0,0 +1,279 @@
#include "common.h"
// ref: ggml.c:ggml_compute_forward_ssm_conv_f32
kernel void kernel_ssm_conv_f32_f32(
constant ggml_metal_kargs_ssm_conv & args,
device const void * src0,
device const void * src1,
device float * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t ir = tgpig.x;
const int64_t i2 = tgpig.y;
const int64_t i3 = tgpig.z;
const int64_t nc = args.ne10;
//const int64_t ncs = args.ne00;
//const int64_t nr = args.ne01;
//const int64_t n_t = args.ne1;
//const int64_t n_s = args.ne2;
device const float * s = (device const float *) ((device const char *) src0 + ir*args.nb01 + i2*args.nb00 + i3*args.nb02);
device const float * c = (device const float *) ((device const char *) src1 + ir*args.nb11);
device float * x = (device float *) ((device char *) dst + ir*args.nb0 + i2*args.nb1 + i3*args.nb2);
float sumf = 0.0f;
for (int64_t i0 = 0; i0 < nc; ++i0) {
sumf += s[i0] * c[i0];
}
x[0] = sumf;
}
kernel void kernel_ssm_conv_f32_f32_4(
constant ggml_metal_kargs_ssm_conv & args,
device const void * src0,
device const void * src1,
device float * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t ir = tgpig.x;
const int64_t i2 = tgpig.y;
const int64_t i3 = tgpig.z;
const int64_t nc = args.ne10;
//const int64_t ncs = args.ne00;
//const int64_t nr = args.ne01;
//const int64_t n_t = args.ne1;
//const int64_t n_s = args.ne2;
device const float4 * s = (device const float4 *) ((device const char *) src0 + ir*args.nb01 + i2*args.nb00 + i3*args.nb02);
device const float4 * c = (device const float4 *) ((device const char *) src1 + ir*args.nb11);
device float * x = (device float *) ((device char *) dst + ir*args.nb0 + i2*args.nb1 + i3*args.nb2);
float sumf = 0.0f;
for (int64_t i0 = 0; i0 < nc/4; ++i0) {
sumf += dot(s[i0], c[i0]);
}
x[0] = sumf;
}
constant short FC_ssm_conv_bs [[function_constant(FC_SSM_CONV + 0)]];
// Batched version: each threadgroup processes multiple tokens for better efficiency
// Thread layout: each thread handles one token, threadgroup covers BATCH_SIZE tokens
kernel void kernel_ssm_conv_f32_f32_batched(
constant ggml_metal_kargs_ssm_conv & args,
device const void * src0,
device const void * src1,
device float * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
// tgpig.x = row index (ir)
// tgpig.y = batch of tokens (i2_base / BATCH_SIZE)
// tgpig.z = sequence index (i3)
// tpitg.x = thread within batch (0..BATCH_SIZE-1)
const short BATCH_SIZE = FC_ssm_conv_bs;
const int64_t ir = tgpig.x;
const int64_t i2_base = tgpig.y * BATCH_SIZE;
const int64_t i3 = tgpig.z;
const int64_t i2_off = tpitg.x;
const int64_t i2 = i2_base + i2_off;
const int64_t nc = args.ne10; // conv kernel size (typically 4)
const int64_t n_t = args.ne1; // number of tokens
// Bounds check for partial batches at the end
if (i2 >= n_t) {
return;
}
// Load conv weights (shared across all tokens for this row)
device const float * c = (device const float *) ((device const char *) src1 + ir*args.nb11);
// Load source for this specific token
device const float * s = (device const float *) ((device const char *) src0 + ir*args.nb01 + i2*args.nb00 + i3*args.nb02);
// Output location for this token
device float * x = (device float *) ((device char *) dst + ir*args.nb0 + i2*args.nb1 + i3*args.nb2);
float sumf = 0.0f;
for (int64_t i0 = 0; i0 < nc; ++i0) {
sumf += s[i0] * c[i0];
}
x[0] = sumf;
}
kernel void kernel_ssm_conv_f32_f32_batched_4(
constant ggml_metal_kargs_ssm_conv & args,
device const void * src0,
device const void * src1,
device float * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
// tgpig.x = row index (ir)
// tgpig.y = batch of tokens (i2_base / BATCH_SIZE)
// tgpig.z = sequence index (i3)
// tpitg.x = thread within batch (0..BATCH_SIZE-1)
const short BATCH_SIZE = FC_ssm_conv_bs;
const int64_t ir = tgpig.x;
const int64_t i2_base = tgpig.y * BATCH_SIZE;
const int64_t i3 = tgpig.z;
const int64_t i2_off = tpitg.x;
const int64_t i2 = i2_base + i2_off;
const int64_t nc = args.ne10; // conv kernel size (typically 4)
const int64_t n_t = args.ne1; // number of tokens
// Bounds check for partial batches at the end
if (i2 >= n_t) {
return;
}
// Load conv weights (shared across all tokens for this row)
device const float4 * c = (device const float4 *) ((device const char *) src1 + ir*args.nb11);
// Load source for this specific token
device const float4 * s = (device const float4 *) ((device const char *) src0 + ir*args.nb01 + i2*args.nb00 + i3*args.nb02);
// Output location for this token
device float * x = (device float *) ((device char *) dst + ir*args.nb0 + i2*args.nb1 + i3*args.nb2);
float sumf = 0.0f;
for (int64_t i0 = 0; i0 < nc/4; ++i0) {
sumf += dot(s[i0], c[i0]);
}
x[0] = sumf;
}
// ref: ggml.c:ggml_compute_forward_ssm_scan_f32, Mamba-2 part
// Optimized version: reduces redundant memory loads by having one thread load shared values
kernel void kernel_ssm_scan_f32(
constant ggml_metal_kargs_ssm_scan & args,
device const void * src0,
device const void * src1,
device const void * src2,
device const void * src3,
device const void * src4,
device const void * src5,
device const void * src6,
device float * dst,
threadgroup float * shared [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgptg[[simdgroups_per_threadgroup]],
uint3 tgpg[[threadgroups_per_grid]]) {
constexpr short NW = N_SIMDWIDTH;
// Shared memory layout:
// [0..sgptg*NW-1]: partial sums for reduction (existing)
// [sgptg*NW..sgptg*NW+sgptg-1]: pre-computed x_dt values for each token in batch
// [sgptg*NW+sgptg..sgptg*NW+2*sgptg-1]: pre-computed dA values for each token in batch
threadgroup float * shared_sums = shared;
threadgroup float * shared_x_dt = shared + sgptg * NW;
threadgroup float * shared_dA = shared + sgptg * NW + sgptg;
shared_sums[tpitg.x] = 0.0f;
const int32_t i0 = tpitg.x;
const int32_t i1 = tgpig.x;
const int32_t ir = tgpig.y; // current head
const int32_t i3 = tgpig.z; // current seq
const int32_t nc = args.d_state;
const int32_t nr = args.d_inner;
const int32_t nh = args.n_head;
const int32_t ng = args.n_group;
const int32_t n_t = args.n_seq_tokens;
const int32_t s_off = args.s_off;
device const int32_t * ids = (device const int32_t *) src6;
device const float * s0_buff = (device const float *) ((device const char *) src0 + ir*args.nb02 + ids[i3]*args.nb03);
device float * s_buff = (device float *) ((device char *) dst + ir*args.nb02 + i3*args.nb03 + s_off);
const int32_t i = i0 + i1*nc;
const int32_t g = ir / (nh / ng); // repeat_interleave
float s0 = s0_buff[i];
float s = 0.0f;
device const float * A = (device const float *) ((device const char *) src3 + ir*args.nb31); // {ne30, nh}
const float A0 = A[i0%args.ne30];
device const float * x = (device const float *)((device const char *) src1 + i1*args.nb10 + ir*args.nb11 + i3*args.nb13); // {dim, nh, nt, ns}
device const float * dt = (device const float *)((device const char *) src2 + ir*args.nb20 + i3*args.nb22); // {nh, nt, ns}
device const float * B = (device const float *)((device const char *) src4 + g*args.nb41 + i3*args.nb43); // {d_state, ng, nt, ns}
device const float * C = (device const float *)((device const char *) src5 + g*args.nb51 + i3*args.nb53); // {d_state, ng, nt, ns}
device float * y = dst + (i1 + ir*(nr) + i3*(n_t*nh*nr)); // {dim, nh, nt, ns}
for (int i2 = 0; i2 < n_t; i2 += sgptg) {
threadgroup_barrier(mem_flags::mem_threadgroup);
// Pre-compute x_dt and dA for this batch of tokens
// Only first sgptg threads do the loads and expensive math
if (i0 < sgptg && i2 + i0 < n_t) {
// ns12 and ns21 are element strides (nb12/nb10, nb21/nb20)
device const float * x_t = x + i0 * args.ns12;
device const float * dt_t = dt + i0 * args.ns21;
const float dt0 = dt_t[0];
const float dtsp = dt0 <= 20.0f ? log(1.0f + exp(dt0)) : dt0;
shared_x_dt[i0] = x_t[0] * dtsp;
shared_dA[i0] = dtsp; // Store dtsp, compute exp(dtsp * A0) per-thread since A0 varies
}
threadgroup_barrier(mem_flags::mem_threadgroup);
for (int t = 0; t < sgptg && i2 + t < n_t; t++) {
const float x_dt = shared_x_dt[t];
const float dA = exp(shared_dA[t] * A0);
s = (s0 * dA) + (B[i0] * x_dt);
const float sumf = simd_sum(s * C[i0]);
if (tiisg == 0) {
shared_sums[t*NW + sgitg] = sumf;
}
// recurse
s0 = s;
B += args.ns42;
C += args.ns52;
}
// Advance pointers for next batch
x += sgptg * args.ns12;
dt += sgptg * args.ns21;
threadgroup_barrier(mem_flags::mem_threadgroup);
const float sumf = simd_sum(shared_sums[sgitg*NW + tiisg]);
if (tiisg == 0 && i2 + sgitg < n_t) {
y[sgitg*nh*nr] = sumf;
}
y += sgptg*nh*nr;
}
s_buff[i] = s;
}
+69
View File
@@ -0,0 +1,69 @@
#include "common.h"
template<uint32_t ttype>
bool _ggml_vec_tri_cmp(const int i, const int r);
template<>
bool _ggml_vec_tri_cmp</* GGML_TRI_TYPE_LOWER */ 3>(const int i, const int r) {
return i < r;
}
template<>
bool _ggml_vec_tri_cmp</* GGML_TRI_TYPE_LOWER_DIAG */ 2>(const int i, const int r) {
return i <= r;
}
template<>
bool _ggml_vec_tri_cmp</* GGML_TRI_TYPE_UPPER */ 1>(const int i, const int r) {
return i > r;
}
template<>
bool _ggml_vec_tri_cmp</* GGML_TRI_TYPE_UPPER_DIAG */ 0>(const int i, const int r) {
return i >= r;
}
template<typename T, int ttype>
kernel void kernel_tri(
constant ggml_metal_kargs_tri & args,
device const char * src0,
device const char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i3 = tgpig.z;
const int i2 = tgpig.y;
const int i1 = tgpig.x;
if (i3 >= args.ne03 || i2 >= args.ne02 || i1 >= args.ne01) {
return;
}
device const T * src_row = (device const T *) ((device const char *) src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03);
device T * dst_row = (device T *) ((device char *) dst + i1*args.nb1 + i2*args.nb2 + i3*args.nb3);
// Each thread is a single element of the row if ne00 < max threads per
// threadgroup, so this will loop once for each index that this thread is
// responsible for
for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
// Use the comparison as a mask for branchless
dst_row[i0] = static_cast<T>(_ggml_vec_tri_cmp<ttype>(i0, i1)) * src_row[i0];
}
}
typedef decltype(kernel_tri<float, 0>) kernel_tri_t;
template [[host_name("kernel_tri_f32_0")]] kernel kernel_tri_t kernel_tri<float, 0>;
template [[host_name("kernel_tri_f32_1")]] kernel kernel_tri_t kernel_tri<float, 1>;
template [[host_name("kernel_tri_f32_2")]] kernel kernel_tri_t kernel_tri<float, 2>;
template [[host_name("kernel_tri_f32_3")]] kernel kernel_tri_t kernel_tri<float, 3>;
template [[host_name("kernel_tri_f16_0")]] kernel kernel_tri_t kernel_tri<half, 0>;
template [[host_name("kernel_tri_f16_1")]] kernel kernel_tri_t kernel_tri<half, 1>;
template [[host_name("kernel_tri_f16_2")]] kernel kernel_tri_t kernel_tri<half, 2>;
template [[host_name("kernel_tri_f16_3")]] kernel kernel_tri_t kernel_tri<half, 3>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_tri_bf16_0")]] kernel kernel_tri_t kernel_tri<bfloat, 0>;
template [[host_name("kernel_tri_bf16_1")]] kernel kernel_tri_t kernel_tri<bfloat, 1>;
template [[host_name("kernel_tri_bf16_2")]] kernel kernel_tri_t kernel_tri<bfloat, 2>;
template [[host_name("kernel_tri_bf16_3")]] kernel kernel_tri_t kernel_tri<bfloat, 3>;
#endif
+374
View File
@@ -0,0 +1,374 @@
#include "common.h"
constant short FC_unary_op [[function_constant(FC_UNARY + 0)]];
constant bool FC_unary_cnt[[function_constant(FC_UNARY + 1)]];
template <typename T0, typename T, typename TC>
kernel void kernel_unary_impl(
constant ggml_metal_kargs_unary & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
#define FC_OP FC_unary_op
#define FC_CNT FC_unary_cnt
device const T0 * src0_ptr;
device T * dst_ptr;
int i0;
if (FC_CNT) {
i0 = tgpig.x;
src0_ptr = (device const T0 *) (src0);
dst_ptr = (device T *) (dst);
} else {
const int i03 = tgpig.z;
const int i02 = tgpig.y;
const int k0 = tgpig.x/args.ne01;
const int i01 = tgpig.x - k0*args.ne01;
i0 = k0*ntg.x + tpitg.x;
src0_ptr = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
dst_ptr = (device T *) (dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1 );
}
{
//threadgroup_barrier(mem_flags::mem_none);
if (!FC_CNT) {
if (i0 >= args.ne0) {
return;
}
}
const TC x = (TC) src0_ptr[i0];
if (FC_OP == OP_UNARY_NUM_SCALE) {
dst_ptr[i0] = (T) (args.scale * x + args.bias);
}
if (FC_OP == OP_UNARY_NUM_FILL) {
dst_ptr[i0] = (T) args.val;
}
if (FC_OP == OP_UNARY_NUM_CLAMP) {
dst_ptr[i0] = (T) clamp(x, args.min, args.max);
}
if (FC_OP == OP_UNARY_NUM_SQR) {
dst_ptr[i0] = (T) (x * x);
}
if (FC_OP == OP_UNARY_NUM_SQRT) {
dst_ptr[i0] = (T) sqrt(x);
}
if (FC_OP == OP_UNARY_NUM_SIN) {
dst_ptr[i0] = (T) sin(x);
}
if (FC_OP == OP_UNARY_NUM_COS) {
dst_ptr[i0] = (T) cos(x);
}
if (FC_OP == OP_UNARY_NUM_LOG) {
dst_ptr[i0] = (T) log(x);
}
if (FC_OP == OP_UNARY_NUM_LEAKY_RELU) {
dst_ptr[i0] = (T) (TC(x > 0)*x + TC(x <= 0)*(x * args.slope));
}
if (FC_OP == OP_UNARY_NUM_TANH) {
dst_ptr[i0] = (T) precise::tanh(x);
}
if (FC_OP == OP_UNARY_NUM_RELU) {
dst_ptr[i0] = (T) fmax(0, x);
}
if (FC_OP == OP_UNARY_NUM_SIGMOID) {
dst_ptr[i0] = (T) (1 / (1 + exp(-x)));
}
if (FC_OP == OP_UNARY_NUM_GELU) {
dst_ptr[i0] = (T) (0.5*x*(1 + precise::tanh(SQRT_2_OVER_PI*x*(1 + GELU_COEF_A*x*x))));
}
if (FC_OP == OP_UNARY_NUM_GELU_ERF) {
dst_ptr[i0] = (T) (0.5*x*(1 + erf_approx(SQRT_2_INV*x)));
}
if (FC_OP == OP_UNARY_NUM_GELU_QUICK) {
dst_ptr[i0] = (T) (x * (1/(1 + exp(GELU_QUICK_COEF*x))));
}
if (FC_OP == OP_UNARY_NUM_SILU) {
dst_ptr[i0] = (T) (x / (1 + exp(-x)));
}
if (FC_OP == OP_UNARY_NUM_ELU) {
dst_ptr[i0] = (T) elu_approx(x);
}
if (FC_OP == OP_UNARY_NUM_NEG) {
dst_ptr[i0] = (T) -x;
}
if (FC_OP == OP_UNARY_NUM_ABS) {
dst_ptr[i0] = (T) fabs(x);
}
if (FC_OP == OP_UNARY_NUM_SGN) {
dst_ptr[i0] = T(x > 0) - T(x < 0);
}
if (FC_OP == OP_UNARY_NUM_STEP) {
dst_ptr[i0] = T(x > 0);
}
if (FC_OP == OP_UNARY_NUM_HARDSWISH) {
dst_ptr[i0] = (T) (x * fmax(0, fmin(1, x/6 + 0.5)));
}
if (FC_OP == OP_UNARY_NUM_HARDSIGMOID) {
dst_ptr[i0] = (T) fmax(0, fmin(1, x/6 + 0.5));
}
if (FC_OP == OP_UNARY_NUM_EXP) {
dst_ptr[i0] = (T) exp(x);
}
if (FC_OP == OP_UNARY_NUM_SOFTPLUS) {
dst_ptr[i0] = (T) select(log(1 + exp(x)), x, x > 20);
}
if (FC_OP == OP_UNARY_NUM_EXPM1) {
// TODO: precise implementation
dst_ptr[i0] = (T) (exp(x) - 1);
}
if (FC_OP == OP_UNARY_NUM_FLOOR) {
dst_ptr[i0] = (T) floor(x);
}
if (FC_OP == OP_UNARY_NUM_CEIL) {
dst_ptr[i0] = (T) ceil(x);
}
if (FC_OP == OP_UNARY_NUM_ROUND) {
dst_ptr[i0] = (T) round(x);
}
if (FC_OP == OP_UNARY_NUM_TRUNC) {
dst_ptr[i0] = (T) trunc(x);
}
if (FC_OP == OP_UNARY_NUM_XIELU) {
const TC xi = x;
const TC gate = TC(xi > TC(0.0f));
const TC clamped = fmin(xi, TC(args.val));
const TC y_pos = TC(args.scale) * xi * xi + TC(args.bias) * xi;
const TC y_neg = (exp(clamped) - TC(1.0f) - xi) * TC(args.slope) + TC(args.bias) * xi;
dst_ptr[i0] = (T) (gate * y_pos + (TC(1.0f) - gate) * y_neg);
}
}
#undef FC_OP
#undef FC_CNT
}
typedef decltype(kernel_unary_impl<float, float, float>) kernel_unary_t;
template [[host_name("kernel_unary_f32_f32")]] kernel kernel_unary_t kernel_unary_impl<float, float, float>;
template [[host_name("kernel_unary_f32_f32_4")]] kernel kernel_unary_t kernel_unary_impl<float4, float4, float4>;
template [[host_name("kernel_unary_f16_f16")]] kernel kernel_unary_t kernel_unary_impl<half, half, float>;
template [[host_name("kernel_unary_f16_f16_4")]] kernel kernel_unary_t kernel_unary_impl<half4, half4, float4>;
kernel void kernel_silu_back_f32(
constant ggml_metal_kargs_silu_back & args,
device const float * dy,
device const float * x,
device float * dx,
uint gid [[thread_position_in_grid]]) {
if (gid >= args.ne) {
return;
}
const float s = 1.0f / (1.0f + exp(-x[gid]));
dx[gid] = dy[gid] * s * (1.0f + x[gid] * (1.0f - s));
}
template<typename T>
kernel void kernel_reglu(
constant ggml_metal_kargs_glu & args,
device const char * src0,
device const char * src1,
device char * dst,
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint ntg[[threads_per_threadgroup]]) {
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
const float x0 = src0_row[i0];
const float x1 = src1_row[i0];
dst_row[i0] = (T)(x0*x1*(x0 > 0.0f));
}
}
typedef decltype(kernel_reglu<float>) kernel_reglu_t;
template [[host_name("kernel_reglu_f32")]] kernel kernel_reglu_t kernel_reglu<float>;
template [[host_name("kernel_reglu_f16")]] kernel kernel_reglu_t kernel_reglu<half>;
template<typename T>
kernel void kernel_geglu(
constant ggml_metal_kargs_glu & args,
device const char * src0,
device const char * src1,
device char * dst,
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint ntg[[threads_per_threadgroup]]) {
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
const float x0 = src0_row[i0];
const float x1 = src1_row[i0];
const float gelu = 0.5f*x0*(1.0f + precise::tanh(SQRT_2_OVER_PI*x0*(1.0f + GELU_COEF_A*x0*x0)));
dst_row[i0] = (T)(gelu*x1);
}
}
typedef decltype(kernel_geglu<float>) kernel_geglu_t;
template [[host_name("kernel_geglu_f32")]] kernel kernel_geglu_t kernel_geglu<float>;
template [[host_name("kernel_geglu_f16")]] kernel kernel_geglu_t kernel_geglu<half>;
template<typename T>
kernel void kernel_swiglu(
constant ggml_metal_kargs_glu & args,
device const char * src0,
device const char * src1,
device char * dst,
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint ntg[[threads_per_threadgroup]]) {
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
const float x0 = src0_row[i0];
const float x1 = src1_row[i0];
const float silu = x0 / (1.0f + exp(-x0));
dst_row[i0] = (T)(silu*x1);
}
}
typedef decltype(kernel_swiglu<float>) kernel_swiglu_t;
template [[host_name("kernel_swiglu_f32")]] kernel kernel_swiglu_t kernel_swiglu<float>;
template [[host_name("kernel_swiglu_f16")]] kernel kernel_swiglu_t kernel_swiglu<half>;
template<typename T>
kernel void kernel_swiglu_oai(
constant ggml_metal_kargs_glu & args,
device const char * src0,
device const char * src1,
device char * dst,
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint ntg[[threads_per_threadgroup]]) {
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
float x0 = src0_row[i0];
float x1 = src1_row[i0];
x0 = min(x0, args.limit);
x1 = max(min(x1, args.limit), -args.limit);
float out_glu = x0 / (1.0f + exp(-x0 * args.alpha));
out_glu = out_glu * (1.0f + x1);
dst_row[i0] = (T)out_glu;
}
}
typedef decltype(kernel_swiglu_oai<float>) kernel_swiglu_oai_t;
template [[host_name("kernel_swiglu_oai_f32")]] kernel kernel_swiglu_oai_t kernel_swiglu_oai<float>;
template [[host_name("kernel_swiglu_oai_f16")]] kernel kernel_swiglu_oai_t kernel_swiglu_oai<half>;
template<typename T>
kernel void kernel_geglu_erf(
constant ggml_metal_kargs_glu & args,
device const char * src0,
device const char * src1,
device char * dst,
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint ntg[[threads_per_threadgroup]]) {
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
const float x0 = src0_row[i0];
const float x1 = src1_row[i0];
const float gelu_erf = 0.5f*x0*(1.0f+erf_approx<float>(x0*SQRT_2_INV));
dst_row[i0] = (T)(gelu_erf*x1);
}
}
typedef decltype(kernel_geglu_erf<float>) kernel_geglu_erf_t;
template [[host_name("kernel_geglu_erf_f32")]] kernel kernel_geglu_erf_t kernel_geglu_erf<float>;
template [[host_name("kernel_geglu_erf_f16")]] kernel kernel_geglu_erf_t kernel_geglu_erf<half>;
template<typename T>
kernel void kernel_geglu_quick(
constant ggml_metal_kargs_glu & args,
device const char * src0,
device const char * src1,
device char * dst,
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint ntg[[threads_per_threadgroup]]) {
device const T * src0_row = (device const T *) ((device const char *) src0 + tgpig*args.nb01) + args.i00;
device const T * src1_row = (device const T *) ((device const char *) src1 + tgpig*args.nb11) + args.i10;
device T * dst_row = (device T *) ((device char *) dst + tgpig*args.nb1);
for (int i0 = tpitg; i0 < args.ne0; i0 += ntg) {
const float x0 = src0_row[i0];
const float x1 = src1_row[i0];
const float gelu_quick = x0*(1.0f/(1.0f+exp(GELU_QUICK_COEF*x0)));
dst_row[i0] = (T)(gelu_quick*x1);
}
}
typedef decltype(kernel_geglu_quick<float>) kernel_geglu_quick_t;
template [[host_name("kernel_geglu_quick_f32")]] kernel kernel_geglu_quick_t kernel_geglu_quick<float>;
template [[host_name("kernel_geglu_quick_f16")]] kernel kernel_geglu_quick_t kernel_geglu_quick<half>;
+179
View File
@@ -0,0 +1,179 @@
#include "common.h"
constant bool FC_upscale_aa [[function_constant(FC_UPSCALE + 0)]];
kernel void kernel_upscale_nearest_f32(
constant ggml_metal_kargs_upscale & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t i3 = tgpig.z;
const int64_t i2 = tgpig.y;
const int64_t i1 = tgpig.x;
const int64_t i03 = i3/args.sf3;
const int64_t i02 = i2/args.sf2;
const int64_t i01 = i1/args.sf1;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const int64_t i00 = i0/args.sf0;
device const float * src0_ptr = (device const float *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
device float * dst_ptr = (device float *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
dst_ptr[0] = src0_ptr[0];
}
}
static inline float bilinear_tri(float x) {
return MAX(0.0f, 1.0f - fabs(x));
}
kernel void kernel_upscale_bilinear_f32(
constant ggml_metal_kargs_upscale & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t i3 = tgpig.z;
const int64_t i2 = tgpig.y;
const int64_t i1 = tgpig.x;
const int64_t i03 = i3 / args.sf3;
const int64_t i02 = i2 / args.sf2;
const float f01 = ((float)i1 + args.poffs) / args.sf1 - args.poffs;
const int64_t i01 = MAX(0, MIN(args.ne01 - 1, (int64_t)floor(f01)));
const int64_t i01p = MAX(0, MIN(args.ne01 - 1, i01 + 1));
const float fd1 = MAX(0.0f, MIN(1.0f, f01 - (float)i01));
src0 += i03*args.nb03 + i02*args.nb02;
device float * dst_ptr = (device float *)(dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1);
if (FC_upscale_aa) {
const float support0 = MAX(1.0f, 1.0f / args.sf0);
const float invscale0 = 1.0f / support0;
const float support1 = MAX(1.0f, 1.0f / args.sf1);
const float invscale1 = 1.0f / support1;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const float f00 = ((float)i0 + args.poffs) / args.sf0 - args.poffs;
int64_t x_min = MAX((int64_t)0, (int64_t)floor(f00 - support0 + args.poffs));
int64_t x_max = MIN(args.ne00, (int64_t)ceil (f00 + support0 + args.poffs));
int64_t y_min = MAX((int64_t)0, (int64_t)floor(f01 - support1 + args.poffs));
int64_t y_max = MIN(args.ne01, (int64_t)ceil (f01 + support1 + args.poffs));
float sum = 0.0f;
float wsum = 0.0f;
for (int64_t sy = y_min; sy < y_max; ++sy) {
const float wy = MAX(0.0f, 1.0f - fabs((float)sy - f01) * invscale1);
for (int64_t sx = x_min; sx < x_max; ++sx) {
const float wx = MAX(0.0f, 1.0f - fabs((float)sx - f00) * invscale0);
const float w = wx * wy;
device const float * src_ptr = (device const float *)(src0 + sy*args.nb01 + sx*args.nb00);
sum += (*src_ptr) * w;
wsum += w;
}
}
const float v = (wsum > 0.0f) ? (sum / wsum) : 0.0f;
dst_ptr[i0] = v;
}
} else {
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const float f00 = ((float)i0 + args.poffs) / args.sf0 - args.poffs;
const int64_t i00 = MAX(0, MIN(args.ne00 - 1, (int64_t)floor(f00)));
const int64_t i00p = MAX(0, MIN(args.ne00 - 1, i00 + 1));
const float fd0 = MAX(0.0f, MIN(1.0f, f00 - (float)i00));
device const float * src00 = (device const float *)(src0 + i01*args.nb01 + i00*args.nb00);
device const float * src10 = (device const float *)(src0 + i01*args.nb01 + i00p*args.nb00);
device const float * src01 = (device const float *)(src0 + i01p*args.nb01 + i00*args.nb00);
device const float * src11 = (device const float *)(src0 + i01p*args.nb01 + i00p*args.nb00);
const float v =
(*src00) * (1.0f - fd0) * (1.0f - fd1) +
(*src10) * fd0 * (1.0f - fd1) +
(*src01) * (1.0f - fd0) * fd1 +
(*src11) * fd0 * fd1;
dst_ptr[i0] = v;
}
}
}
static inline float bicubic_weight1(float x) {
const float a = -0.75f;
return ((a + 2) * x - (a + 3)) * x * x + 1;
}
static inline float bicubic_weight2(float x) {
const float a = -0.75f;
return ((a * x - 5 * a) * x + 8 * a) * x - 4 * a;
}
kernel void kernel_upscale_bicubic_f32(
constant ggml_metal_kargs_upscale & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t i3 = tgpig.z;
const int64_t i2 = tgpig.y;
const int64_t i1 = tgpig.x;
const int64_t i03 = i3 / args.sf3;
const int64_t i02 = i2 / args.sf2;
const float f01 = ((float)i1 + args.poffs) / args.sf1 - args.poffs;
const int64_t i01 = (int64_t)floor(f01);
const float fd1 = f01 - (float)i01;
const float w_y0 = bicubic_weight2(fd1 + 1.0f);
const float w_y1 = bicubic_weight1(fd1);
const float w_y2 = bicubic_weight1(1.0f - fd1);
const float w_y3 = bicubic_weight2(2.0f - fd1);
const device const char * src_slice = src0 + i03 * args.nb03 + i02 * args.nb02;
device float * dst_ptr = (device float *)(dst + i3 * args.nb3 + i2 * args.nb2 + i1 * args.nb1);
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const float f00 = ((float)i0 + args.poffs) / args.sf0 - args.poffs;
const int64_t i00 = (int64_t)floor(f00);
const float fd0 = f00 - (float)i00;
const float w_x0 = bicubic_weight2(fd0 + 1.0f);
const float w_x1 = bicubic_weight1(fd0);
const float w_x2 = bicubic_weight1(1.0f - fd0);
const float w_x3 = bicubic_weight2(2.0f - fd0);
float sum = 0.0f;
for (int dy = -1; dy <= 2; ++dy) {
const int64_t iy = MAX(0, MIN(args.ne01 - 1, i01 + dy));
const float wy = (dy == -1) ? w_y0 : (dy == 0) ? w_y1 : (dy == 1) ? w_y2 : w_y3;
for (int dx = -1; dx <= 2; ++dx) {
const int64_t ix = MAX(0, MIN(args.ne00 - 1, i00 + dx));
const float wx = (dx == -1) ? w_x0 : (dx == 0) ? w_x1 : (dx == 1) ? w_x2 : w_x3;
device const float * src_ptr = (device const float *)(src_slice + iy * args.nb01 + ix * args.nb00);
sum += (*src_ptr) * wx * wy;
}
}
dst_ptr[i0] = sum;
}
}
+179
View File
@@ -0,0 +1,179 @@
#include "common.h"
kernel void kernel_rwkv_wkv6_f32(
device const float * k,
device const float * v,
device const float * r,
device const float * tf,
device const float * td,
device const float * state_in,
device float * dst,
constant uint & B,
constant uint & T,
constant uint & C,
constant uint & H,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const uint head_size = 64; // TODO: support head_size = 128
const uint batch_id = tgpig.x / H;
const uint head_id = tgpig.x % H;
const uint tid = tpitg.x;
if (batch_id >= B || head_id >= H) {
return;
}
const uint state_size = C * head_size;
const uint n_seq_tokens = T / B;
threadgroup float _k[head_size];
threadgroup float _r[head_size];
threadgroup float _tf[head_size];
threadgroup float _td[head_size];
float state[head_size];
for (uint i = 0; i < head_size; i++) {
state[i] = state_in[batch_id * state_size + head_id * head_size * head_size
+ i * head_size + tid];
}
threadgroup_barrier(mem_flags::mem_threadgroup);
_tf[tid] = tf[head_id * head_size + tid];
threadgroup_barrier(mem_flags::mem_threadgroup);
const uint start_t = batch_id * n_seq_tokens * C + head_id * head_size + tid;
const uint end_t = (batch_id + 1) * n_seq_tokens * C + head_id * head_size + tid;
for (uint t = start_t; t < end_t; t += C) {
threadgroup_barrier(mem_flags::mem_threadgroup);
_k[tid] = k[t];
_r[tid] = r[t];
_td[tid] = td[t];
threadgroup_barrier(mem_flags::mem_threadgroup);
const float v_val = v[t];
float y = 0.0;
for (uint j = 0; j < head_size; j += 4) {
float4 k_vec = float4(_k[j], _k[j+1], _k[j+2], _k[j+3]);
float4 r_vec = float4(_r[j], _r[j+1], _r[j+2], _r[j+3]);
float4 tf_vec = float4(_tf[j], _tf[j+1], _tf[j+2], _tf[j+3]);
float4 td_vec = float4(_td[j], _td[j+1], _td[j+2], _td[j+3]);
float4 s_vec = float4(state[j], state[j+1], state[j+2], state[j+3]);
float4 kv = k_vec * v_val;
float4 temp = tf_vec * kv + s_vec;
y += dot(r_vec, temp);
s_vec = s_vec * td_vec + kv;
state[j] = s_vec[0];
state[j+1] = s_vec[1];
state[j+2] = s_vec[2];
state[j+3] = s_vec[3];
}
dst[t] = y;
}
for (uint i = 0; i < head_size; i++) {
dst[T * C + batch_id * state_size + head_id * head_size * head_size
+ i * head_size + tid] = state[i];
}
}
kernel void kernel_rwkv_wkv7_f32(
device const float * r,
device const float * w,
device const float * k,
device const float * v,
device const float * a,
device const float * b,
device const float * state_in,
device float * dst,
constant uint & B,
constant uint & T,
constant uint & C,
constant uint & H,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const uint head_size = 64; // TODO: support head_size = 128
const uint batch_id = tgpig.x / H;
const uint head_id = tgpig.x % H;
const uint tid = tpitg.x;
if (batch_id >= B || head_id >= H) {
return;
}
const uint state_size = C * head_size;
const uint n_seq_tokens = T / B;
threadgroup float _r[head_size];
threadgroup float _w[head_size];
threadgroup float _k[head_size];
threadgroup float _a[head_size];
threadgroup float _b[head_size];
float state[head_size];
for (uint i = 0; i < head_size; i++) {
state[i] = state_in[batch_id * state_size + head_id * head_size * head_size
+ tid * head_size + i];
}
const uint start_t = batch_id * n_seq_tokens * C + head_id * head_size + tid;
const uint end_t = (batch_id + 1) * n_seq_tokens * C + head_id * head_size + tid;
for (uint t = start_t; t < end_t; t += C) {
threadgroup_barrier(mem_flags::mem_threadgroup);
_r[tid] = r[t];
_w[tid] = w[t];
_k[tid] = k[t];
_a[tid] = a[t];
_b[tid] = b[t];
threadgroup_barrier(mem_flags::mem_threadgroup);
const float v_val = v[t];
float y = 0.0, sa = 0.0;
float4 sa_vec(0.0);
for (uint j = 0; j < head_size; j += 4) {
float4 a_vec = float4(_a[j], _a[j+1], _a[j+2], _a[j+3]);
float4 s_vec = float4(state[j], state[j+1], state[j+2], state[j+3]);
sa_vec += a_vec * s_vec;
}
sa = sa_vec[0] + sa_vec[1] + sa_vec[2] + sa_vec[3];
for (uint j = 0; j < head_size; j += 4) {
float4 r_vec = float4(_r[j], _r[j+1], _r[j+2], _r[j+3]);
float4 w_vec = float4(_w[j], _w[j+1], _w[j+2], _w[j+3]);
float4 k_vec = float4(_k[j], _k[j+1], _k[j+2], _k[j+3]);
float4 b_vec = float4(_b[j], _b[j+1], _b[j+2], _b[j+3]);
float4 s_vec = float4(state[j], state[j+1], state[j+2], state[j+3]);
float4 kv = k_vec * v_val;
s_vec = s_vec * w_vec + kv + sa * b_vec;
y += dot(s_vec, r_vec);
state[j] = s_vec[0];
state[j+1] = s_vec[1];
state[j+2] = s_vec[2];
state[j+3] = s_vec[3];
}
dst[t] = y;
}
for (uint i = 0; i < head_size; i++) {
dst[T * C + batch_id * state_size + head_id * head_size * head_size
+ tid * head_size + i] = state[i];
}
}
+2 -3
View File
@@ -1425,7 +1425,7 @@ extern "C" {
/// NOTE: Avoid using on the full vocabulary as searching for repeated tokens can become slow. For example, apply top-k or top-p sampling first.
LLAMA_API struct llama_sampler * llama_sampler_init_penalties(
int32_t n_vocab,
int32_t penalty_last_n, // last n tokens to penalize (0 = disable penalty, -1 = context size)
int32_t penalty_last_n, // last n tokens to penalize (0 = disable penalty)
float penalty_repeat, // must be > 0.0, 1.0 = disabled
float penalty_freq, // must be finite, 0.0 = disabled
float penalty_present); // must be finite, 0.0 = disabled
@@ -1433,11 +1433,10 @@ extern "C" {
/// @details DRY sampler, designed by p-e-w, as described in: https://github.com/oobabooga/text-generation-webui/pull/5677, porting Koboldcpp implementation authored by pi6am: https://github.com/LostRuins/koboldcpp/pull/982
LLAMA_API struct llama_sampler * llama_sampler_init_dry(
const struct llama_vocab * vocab,
int32_t n_ctx_train,
float dry_multiplier,
float dry_base,
int32_t dry_allowed_length,
int32_t dry_penalty_last_n,
int32_t dry_penalty_last_n, // last n tokens to penalize (0 = disable penalty)
const char ** seq_breakers,
size_t num_breakers);
+3 -3
View File
@@ -123,15 +123,15 @@ function(npm_build out_var)
endif()
if(need_install)
message(STATUS "UI: running npm install")
message(STATUS "UI: running npm ci")
execute_process(
COMMAND ${NPM_EXECUTABLE} install
COMMAND ${NPM_EXECUTABLE} ci
WORKING_DIRECTORY "${WORK_DIR}"
RESULT_VARIABLE rc
ERROR_VARIABLE err
)
if(NOT rc EQUAL 0)
message(STATUS "UI: npm install failed (${rc})")
message(STATUS "UI: npm ci failed (${rc})")
message(STATUS " stderr: ${err}")
return()
endif()
+8 -12
View File
@@ -3078,8 +3078,6 @@ struct llama_sampler * llama_sampler_init_top_n_sigma(float n) {
// DRY
struct llama_sampler_dry {
int32_t total_context_size;
const float dry_multiplier;
const float dry_base;
const int32_t dry_allowed_length;
@@ -3155,8 +3153,7 @@ static void llama_sampler_dry_apply(struct llama_sampler * smpl, llama_token_dat
return;
}
int32_t effective_dry_penalty_last_n = (ctx->dry_penalty_last_n == -1) ? ctx->total_context_size : std::max(ctx->dry_penalty_last_n, 0);
int last_n_repeat = std::min(std::min((int)ctx->last_tokens.size(), effective_dry_penalty_last_n), ctx->total_context_size);
int last_n_repeat = std::min((int) ctx->last_tokens.size(), ctx->dry_penalty_last_n);
if (last_n_repeat <= ctx->dry_allowed_length) {
return;
@@ -3369,7 +3366,7 @@ static struct llama_sampler * llama_sampler_dry_clone(const struct llama_sampler
llama_vocab dummy_vocab;
// dummy vocab is passed because it is only needed for raw sequence breaker processing, which we have already done and will simply be copying
auto * result = llama_sampler_init_dry(&dummy_vocab, ctx->total_context_size, ctx->dry_multiplier, ctx->dry_base, ctx->dry_allowed_length, ctx->dry_penalty_last_n, NULL, 0);
auto * result = llama_sampler_init_dry(&dummy_vocab, ctx->dry_multiplier, ctx->dry_base, ctx->dry_allowed_length, ctx->dry_penalty_last_n, NULL, 0);
// Copy the state, including the processed breakers
{
@@ -3400,8 +3397,8 @@ static struct llama_sampler_i llama_sampler_dry_i = {
/* .backend_set_input = */ nullptr,
};
struct llama_sampler * llama_sampler_init_dry(const struct llama_vocab * vocab, int32_t n_ctx_train, float dry_multiplier, float dry_base, int32_t dry_allowed_length, int32_t dry_penalty_last_n, const char** seq_breakers, size_t num_breakers) {
int32_t effective_dry_penalty_last_n = (dry_penalty_last_n == -1) ? n_ctx_train : std::max(dry_penalty_last_n, 0);
struct llama_sampler * llama_sampler_init_dry(const struct llama_vocab * vocab, float dry_multiplier, float dry_base, int32_t dry_allowed_length, int32_t dry_penalty_last_n, const char** seq_breakers, size_t num_breakers) {
dry_penalty_last_n = std::max(dry_penalty_last_n, 0);
std::unordered_multimap<llama_token, std::vector<llama_token>> processed_breakers;
const int MAX_CHAR_LEN = 40;
const int MAX_SEQ_LEN = 20;
@@ -3438,23 +3435,22 @@ struct llama_sampler * llama_sampler_init_dry(const struct llama_vocab * vocab,
return llama_sampler_init(
/* .iface = */ &llama_sampler_dry_i,
/* .ctx = */ new llama_sampler_dry {
/* .total_context_size = */ n_ctx_train,
/* .dry_multiplier = */ dry_multiplier,
/* .dry_base = */ dry_base,
/* .dry_allowed_length = */ dry_allowed_length,
/* .dry_penalty_last_n = */ dry_penalty_last_n,
/* .dry_processed_breakers = */ std::move(processed_breakers),
/* .dry_repeat_count = */ dry_enabled ? std::vector<int>(effective_dry_penalty_last_n, 0) : std::vector<int>{},
/* .dry_repeat_count = */ dry_enabled ? std::vector<int>(dry_penalty_last_n, 0) : std::vector<int>{},
/* .dry_max_token_repeat = */ {},
/* .last_tokens = */ dry_enabled ? ring_buffer<llama_token>(effective_dry_penalty_last_n) : ring_buffer<llama_token>(0),
/* .last_tokens = */ dry_enabled ? ring_buffer<llama_token>(dry_penalty_last_n) : ring_buffer<llama_token>(0),
}
);
}
// wrapper for test-sampling.cpp
struct llama_sampler * llama_sampler_init_dry_testing(int32_t context_size, float dry_multiplier, float dry_base, int32_t dry_allowed_length, int32_t dry_penalty_last_n, const std::vector<std::vector<llama_token>>& seq_breakers) {
struct llama_sampler * llama_sampler_init_dry_testing(float dry_multiplier, float dry_base, int32_t dry_allowed_length, int32_t dry_penalty_last_n, const std::vector<std::vector<llama_token>>& seq_breakers) {
llama_vocab dummy_vocab;
auto * result = llama_sampler_init_dry(&dummy_vocab, context_size, dry_multiplier, dry_base, dry_allowed_length, dry_penalty_last_n, NULL, 0);
auto * result = llama_sampler_init_dry(&dummy_vocab, dry_multiplier, dry_base, dry_allowed_length, dry_penalty_last_n, NULL, 0);
auto * ctx = (llama_sampler_dry *) result->ctx;
// Process the token-based sequence breakers
-1
View File
@@ -34,7 +34,6 @@ struct llama_sampler_chain {
};
struct llama_sampler * llama_sampler_init_dry_testing(
int32_t context_size,
float dry_multiplier,
float dry_base,
int32_t dry_allowed_length,
+8
View File
@@ -101,6 +101,14 @@ static void test(void) {
{
common_params penalty_params;
assert(penalty_params.sampling.penalty_last_n == 64);
assert(penalty_params.sampling.dry_penalty_last_n == 64);
argv = {"binary_name", "--repeat-last-n", "-1"};
assert(false == common_params_parse(argv.size(), list_str_to_char(argv).data(), penalty_params, LLAMA_EXAMPLE_COMMON));
argv = {"binary_name", "--dry-penalty-last-n", "-1"};
assert(false == common_params_parse(argv.size(), list_str_to_char(argv).data(), penalty_params, LLAMA_EXAMPLE_COMMON));
argv = {"binary_name", "--repeat-penalty", "0"};
assert(false == common_params_parse(argv.size(), list_str_to_char(argv).data(), penalty_params, LLAMA_EXAMPLE_COMMON));
+2 -2
View File
@@ -10,7 +10,7 @@
#include <string>
#include <vector>
extern struct llama_sampler * llama_sampler_init_dry_testing(int32_t context_size, float dry_multiplier, float dry_base, int32_t dry_allowed_length, int32_t dry_penalty_last_n, const std::vector<std::vector<llama_token>>& seq_breakers);
extern struct llama_sampler * llama_sampler_init_dry_testing(float dry_multiplier, float dry_base, int32_t dry_allowed_length, int32_t dry_penalty_last_n, const std::vector<std::vector<llama_token>>& seq_breakers);
static void dump(const llama_token_data_array * cur_p) {
for (size_t i = 0; i < cur_p->size; i++) {
@@ -168,7 +168,7 @@ static void test_dry(
sampler_tester tester(probs, expected_probs);
auto * sampler = llama_sampler_init_dry_testing(1024, dry_multiplier, dry_base, dry_allowed_length, dry_penalty_last_n, seq_breakers);
auto * sampler = llama_sampler_init_dry_testing(dry_multiplier, dry_base, dry_allowed_length, dry_penalty_last_n, seq_breakers);
for (size_t i = 0; i < last_tokens.size(); i++) {
llama_sampler_accept(sampler, last_tokens[i]);
+2 -2
View File
@@ -116,14 +116,14 @@
| `--xtc-probability N` | xtc probability (default: 0.00, 0.0 = disabled) |
| `--xtc-threshold N` | xtc threshold (default: 0.10, 1.0 = disabled) |
| `--typical, --typical-p N` | locally typical sampling, parameter p (default: 1.00, 1.0 = disabled) |
| `--repeat-last-n N` | last n tokens to consider for penalize (default: 64, 0 = disabled, -1 = ctx_size) |
| `--repeat-last-n N` | last n tokens to consider for penalize (default: 64, 0 = disabled) |
| `--repeat-penalty N` | penalize repeat sequence of tokens (default: 1.00, 1.0 = disabled) |
| `--presence-penalty N` | repeat alpha presence penalty (default: 0.00, 0.0 = disabled) |
| `--frequency-penalty N` | repeat alpha frequency penalty (default: 0.00, 0.0 = disabled) |
| `--dry-multiplier N` | set DRY sampling multiplier (default: 0.00, 0.0 = disabled) |
| `--dry-base N` | set DRY sampling base value (default: 1.75) |
| `--dry-allowed-length N` | set allowed length for DRY sampling (default: 2) |
| `--dry-penalty-last-n N` | set DRY penalty for the last n tokens (default: -1, 0 = disable, -1 = context size) |
| `--dry-penalty-last-n N` | set DRY penalty for the last n tokens (default: 64, 0 = disable) |
| `--dry-sequence-breaker STRING` | add sequence breaker for DRY sampling, clearing out default breakers ('\n', ':', '"', '*') in the process; use "none" to not use any sequence breakers |
| `--adaptive-target N` | adaptive-p: select tokens near this probability (valid range 0.0 to 1.0; negative = disabled) (default: -1.00)<br/>[(more info)](https://github.com/ggml-org/llama.cpp/pull/17927) |
| `--adaptive-decay N` | adaptive-p: decay rate for target adaptation over time. lower values are more reactive, higher values are more stable.<br/>(valid range 0.0 to 0.99) (default: 0.90) |
+7 -7
View File
@@ -199,14 +199,14 @@ llama-completion.exe -m models\gemma-1.1-7b-it.Q4_K_M.gguf --ignore-eos -n -1
| `--xtc-probability N` | xtc probability (default: 0.00, 0.0 = disabled) |
| `--xtc-threshold N` | xtc threshold (default: 0.10, 1.0 = disabled) |
| `--typical, --typical-p N` | locally typical sampling, parameter p (default: 1.00, 1.0 = disabled) |
| `--repeat-last-n N` | last n tokens to consider for penalize (default: 64, 0 = disabled, -1 = ctx_size) |
| `--repeat-last-n N` | last n tokens to consider for penalize (default: 64, 0 = disabled) |
| `--repeat-penalty N` | penalize repeat sequence of tokens (default: 1.00, 1.0 = disabled) |
| `--presence-penalty N` | repeat alpha presence penalty (default: 0.00, 0.0 = disabled) |
| `--frequency-penalty N` | repeat alpha frequency penalty (default: 0.00, 0.0 = disabled) |
| `--dry-multiplier N` | set DRY sampling multiplier (default: 0.00, 0.0 = disabled) |
| `--dry-base N` | set DRY sampling base value (default: 1.75) |
| `--dry-allowed-length N` | set allowed length for DRY sampling (default: 2) |
| `--dry-penalty-last-n N` | set DRY penalty for the last n tokens (default: -1, 0 = disable, -1 = context size) |
| `--dry-penalty-last-n N` | set DRY penalty for the last n tokens (default: 64, 0 = disable) |
| `--dry-sequence-breaker STRING` | add sequence breaker for DRY sampling, clearing out default breakers ('\n', ':', '"', '*') in the process; use "none" to not use any sequence breakers |
| `--adaptive-target N` | adaptive-p: select tokens near this probability (valid range 0.0 to 1.0; negative = disabled) (default: -1.00)<br/>[(more info)](https://github.com/ggml-org/llama.cpp/pull/17927) |
| `--adaptive-decay N` | adaptive-p: decay rate for target adaptation over time. lower values are more reactive, higher values are more stable.<br/>(valid range 0.0 to 0.99) (default: 0.90) |
@@ -388,11 +388,11 @@ Example usage: `--temp 0`
### Repeat Penalty
- `--repeat-penalty N`: Control the repetition of token sequences in the generated text default: 1.0, 1.0 = disabled).
- `--repeat-last-n N`: Last n tokens to consider for penalizing repetition (default: 64, 0 = disabled, -1 = ctx-size).
- `--repeat-last-n N`: Last n tokens to consider for penalizing repetition (default: 64, 0 = disabled).
The `repeat-penalty` option helps prevent the model from generating repetitive or monotonous text. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. The default value is 1.
The `repeat-last-n` option controls the number of tokens in the history to consider for penalizing repetition. A larger value will look further back in the generated text to prevent repetitions, while a smaller value will only consider recent tokens. A value of 0 disables the penalty, and a value of -1 sets the number of tokens considered equal to the context size (`ctx-size`).
The `repeat-last-n` option controls the number of tokens in the history to consider for penalizing repetition. A larger value will look further back in the generated text to prevent repetitions, while a smaller value will only consider recent tokens. A value of 0 disables the penalty.
### DRY Repetition Penalty
@@ -401,7 +401,7 @@ DRY (Don't Repeat Yourself) sampling is an effective technique for reducing repe
- `--dry-multiplier N`: Set the DRY sampling multiplier (default: 0.0, 0.0 = disabled).
- `--dry-base N`: Set the DRY sampling base value (default: 1.75).
- `--dry-allowed-length N`: Set the allowed length for DRY sampling (default: 2).
- `--dry-penalty-last-n N`: Set DRY penalty for the last n tokens (default: -1, 0 = disable, -1 = context size).
- `--dry-penalty-last-n N`: Set DRY penalty for the last n tokens (default: 64, 0 = disable).
- `--dry-sequence-breaker STRING`: Add a sequence breaker for DRY sampling. Can be used more than once to add multiple sequence breakers. Using this clears out the default breakers, which consist of: `['\n', ':', '"', '*']`. If the string `"none"` is supplied, no sequence breakers are used.
The `dry-multiplier` option controls the strength of the DRY sampling effect. A value of 0.0 disables DRY sampling, while higher values increase its influence. A typical recommended value is 0.8.
@@ -410,13 +410,13 @@ The `dry-base` option sets the base value for the exponential penalty calculatio
The `dry-allowed-length` option sets the maximum length of repeated sequences that will not be penalized. Repetitions shorter than or equal to this length are not penalized, allowing for natural repetitions of short phrases or common words.
The `dry-penalty-last-n` option controls how many recent tokens to consider when applying the DRY penalty. A value of -1 considers the entire context. Use a positive value to limit the consideration to a specific number of recent tokens.
The `dry-penalty-last-n` option controls how many recent tokens to consider when applying the DRY penalty. A value of 0 disables the penalty. Use a positive value to limit the consideration to a specific number of recent tokens.
The `dry-sequence-breaker` option adds a single sequence breaker and can be used more than once to specify multiple sequence breakers. Sequence breakers interrupt sequence matching and break the input into parts where matching can be applied.
DRY sampling provides more nuanced control over text generation, particularly for reducing long-range repetitions and maintaining global coherence.
Example usage: `--dry-multiplier 0.8 --dry-base 1.75 --dry-allowed-length 2 --dry-penalty-last-n -1 --dry-sequence-breaker "—" --dry-sequence-breaker "##"`
Example usage: `--dry-multiplier 0.8 --dry-base 1.75 --dry-allowed-length 2 --dry-penalty-last-n 64 --dry-sequence-breaker "—" --dry-sequence-breaker "##"`
### Top-K Sampling
+20
View File
@@ -47,6 +47,7 @@ struct split_params {
std::string output;
bool no_tensor_first_split = false;
bool dry_run = false;
bool delete_splits = false;
};
static void split_print_usage(const char * executable) {
@@ -65,6 +66,7 @@ static void split_print_usage(const char * executable) {
printf(" --split-max-size N(M|G) max size per split\n");
printf(" --no-tensor-first-split do not add tensors to the first split (disabled by default)\n");
printf(" --dry-run only print out a split plan and exit, without writing any new files\n");
printf(" --delete-splits delete the split files during merge to free up disk space WARNING: this option is unsafe and will leave you in an unrecoverable state if something fails during the merge\n");
printf("\n");
}
@@ -147,6 +149,9 @@ static void split_params_parse_ex(int argc, const char ** argv, split_params & p
}
params.mode = MODE_SIZE;
params.n_bytes_split = split_str_to_n_bytes(argv[arg_idx]);
} else if (arg == "--delete-splits") {
arg_found = true;
params.delete_splits = true;
}
if (!arg_found) {
@@ -509,6 +514,7 @@ static void gguf_merge(const split_params & split_params) {
}
// Write tensors data
bool merge_error = false;
for (int i_split = 0; i_split < n_split; i_split++) {
llama_split_path(split_path, sizeof(split_path), split_prefix, i_split, n_split);
std::ifstream f_input(split_path, std::ios::binary);
@@ -554,6 +560,16 @@ static void gguf_merge(const split_params & split_params) {
ggml_free(ctx_meta);
f_input.close();
fprintf(stderr, "\033[3Ddone\n");
if (!split_params.dry_run && split_params.delete_splits) {
int delete_result = std::remove(split_path);
if (delete_result != 0) {
merge_error = true;
fprintf(stderr, "error: failed to delete %s\n", split_path);
} else {
fprintf(stderr, "%s: deleted file %s\n", __func__, split_path);
}
}
}
if (!split_params.dry_run) {
@@ -568,6 +584,10 @@ static void gguf_merge(const split_params & split_params) {
fprintf(stderr, "%s: %s merged from %d split with %d tensors.\n",
__func__, split_params.output.c_str(), n_split, total_tensors);
if (merge_error) {
exit(EXIT_FAILURE);
}
}
int main(int argc, const char ** argv) {
+22 -2
View File
@@ -66,12 +66,12 @@ echo PASS
echo
# 5. Merge
#$SPLIT --merge $WORK_PATH/ggml-model-split-32-tensors-00001-of-00012.gguf $WORK_PATH/ggml-model-merge-2.gguf
#$SPLIT --merge $WORK_PATH/ggml-model-split-32-tensors-00001-of-00011.gguf $WORK_PATH/ggml-model-merge-2.gguf
#echo PASS
#echo
# 5b. Test the merged model is loading properly
#$MAIN -no-cnv --model $WORK_PATH/ggml-model-merge-2.gguf --n-predict 32
#$MAIN -no-cnv --model $WORK_PATH/ggml-model-merge-2.gguf -p "I believe the meaning of life is" --n-predict 32
#echo PASS
#echo
@@ -85,5 +85,25 @@ $MAIN -no-cnv --model $WORK_PATH/ggml-model-split-500M-00001-of-00002.gguf -p "I
echo PASS
echo
# 7. Merge with delete splits
#for i in $(seq -w 1 11); do
# cp "$WORK_PATH/ggml-model-split-32-tensors-000${i}-of-00011.gguf" "$WORK_PATH/ggml-model-split-32-tensors-copy-000${i}-of-00011.gguf"
#done
#$SPLIT --merge --delete-splits $WORK_PATH/ggml-model-split-32-tensors-copy-00001-of-00011.gguf $WORK_PATH/ggml-model-merge-3.gguf
#echo PASS
#echo
# 7b. Test the merged model is loading properly
#$MAIN -no-cnv --model $WORK_PATH/ggml-model-merge-3.gguf -p "I believe the meaning of life is" --n-predict 32
#echo PASS
#echo
# 7c. Test the files were deleted
#for i in $(seq -w 1 11); do
# test ! -f "$WORK_PATH/ggml-model-split-32-tensors-copy-000${i}-of-00011.gguf"
#done
#echo PASS
#echo
# Clean up
rm -f $WORK_PATH/ggml-model-split*.gguf $WORK_PATH/ggml-model-merge*.gguf
+2 -4
View File
@@ -556,10 +556,8 @@ bool mtmd_audio_preprocessor_whisper::preprocess(const float * s
}
std::vector<float> smpl;
// if input is too short, pad with zeros
// this is to avoid potential issues with stage1/2 padding in log_mel_spectrogram
// TODO: maybe handle this better
size_t min_samples = (size_t) hparams.audio_sample_rate * (hparams.audio_chunk_len + 1); // +1 second margin
// reflection padding needs one sample plus half an FFT window
size_t min_samples = (size_t) hparams.audio_n_fft / 2 + 1;
if (n_samples < min_samples) {
smpl.resize(min_samples, 0.0f);
std::memcpy(smpl.data(), samples, n_samples * sizeof(float));
+1 -1
View File
@@ -215,7 +215,7 @@ def run_mtmd_cli(spec: "ModelSpec", model_path, mmproj_path, image_path, bin_pat
"--dry-multiplier", "0.8",
"--dry-base", "1.75",
"--dry-allowed-length", "2",
"--dry-penalty-last-n", "-1",
"--dry-penalty-last-n", "64",
"--dry-sequence-breaker", "none",
]
if spec.n_ctx is not None:
+5 -5
View File
@@ -133,14 +133,14 @@ For the full list of features, please refer to [server's changelog](https://gith
| `--xtc-probability N` | xtc probability (default: 0.00, 0.0 = disabled) |
| `--xtc-threshold N` | xtc threshold (default: 0.10, 1.0 = disabled) |
| `--typical, --typical-p N` | locally typical sampling, parameter p (default: 1.00, 1.0 = disabled) |
| `--repeat-last-n N` | last n tokens to consider for penalize (default: 64, 0 = disabled, -1 = ctx_size) |
| `--repeat-last-n N` | last n tokens to consider for penalize (default: 64, 0 = disabled) |
| `--repeat-penalty N` | penalize repeat sequence of tokens (default: 1.00, 1.0 = disabled) |
| `--presence-penalty N` | repeat alpha presence penalty (default: 0.00, 0.0 = disabled) |
| `--frequency-penalty N` | repeat alpha frequency penalty (default: 0.00, 0.0 = disabled) |
| `--dry-multiplier N` | set DRY sampling multiplier (default: 0.00, 0.0 = disabled) |
| `--dry-base N` | set DRY sampling base value (default: 1.75) |
| `--dry-allowed-length N` | set allowed length for DRY sampling (default: 2) |
| `--dry-penalty-last-n N` | set DRY penalty for the last n tokens (default: -1, 0 = disable, -1 = context size) |
| `--dry-penalty-last-n N` | set DRY penalty for the last n tokens (default: 64, 0 = disable) |
| `--dry-sequence-breaker STRING` | add sequence breaker for DRY sampling, clearing out default breakers ('\n', ':', '"', '*') in the process; use "none" to not use any sequence breakers |
| `--adaptive-target N` | adaptive-p: select tokens near this probability (valid range 0.0 to 1.0; negative = disabled) (default: -1.00)<br/>[(more info)](https://github.com/ggml-org/llama.cpp/pull/17927) |
| `--adaptive-decay N` | adaptive-p: decay rate for target adaptation over time. lower values are more reactive, higher values are more stable.<br/>(valid range 0.0 to 0.99) (default: 0.90) |
@@ -476,7 +476,7 @@ These words will not be included in the completion, so make sure to add them to
`repeat_penalty`: Control the repetition of token sequences in the generated text. Default: `1.1`
`repeat_last_n`: Last n tokens to consider for penalizing repetition. Default: `64`, where `0` is disabled and `-1` is ctx-size.
`repeat_last_n`: Last n tokens to consider for penalizing repetition. Default: `64`, where `0` is disabled.
`presence_penalty`: Repeat alpha presence penalty. Default: `0.0`, which is disabled.
@@ -488,7 +488,7 @@ These words will not be included in the completion, so make sure to add them to
`dry_allowed_length`: Tokens that extend repetition beyond this receive exponentially increasing penalty: multiplier * base ^ (length of repeating sequence before token - allowed length). Default: `2`
`dry_penalty_last_n`: How many tokens to scan for repetitions. Default: `-1`, where `0` is disabled and `-1` is context size.
`dry_penalty_last_n`: How many tokens to scan for repetitions. Default: `64`, where `0` is disabled.
`dry_sequence_breakers`: Specify an array of sequence breakers for DRY sampling. Only a JSON array of strings is accepted. Default: `['\n', ':', '"', '*']`
@@ -796,7 +796,7 @@ By default, it is read-only. To make POST request to change global properties, y
"dry_multiplier": 0.0,
"dry_base": 1.75,
"dry_allowed_length": 2,
"dry_penalty_last_n": -1,
"dry_penalty_last_n": 64,
"dry_sequence_breakers": [
"\n",
":",
+1 -3
View File
@@ -1807,8 +1807,7 @@ private:
// initialize samplers
if (task.need_sampling()) {
try {
slot.smpl.reset(common_sampler_init(
model_tgt, task.params.sampling, (int32_t) llama_n_ctx(ctx_tgt)));
slot.smpl.reset(common_sampler_init(model_tgt, task.params.sampling));
} catch (std::exception & e) {
std::string err_msg = std::string("Failed to initialize samplers: ") + e.what();
send_error(task, err_msg, ERROR_TYPE_INVALID_REQUEST);
@@ -4148,7 +4147,6 @@ std::unique_ptr<server_res_generator> server_routes::handle_completions_impl(
task.params = server_schema::eval_llama_cmpl_schema(
ctx_server.vocab,
params,
meta->slot_n_ctx,
meta->logit_bias_eog,
data);
+4 -14
View File
@@ -124,8 +124,8 @@ std::vector<std::unique_ptr<field>> make_llama_cmpl_schema(const common_params &
->set_desc("Dynamic temperature exponent, controls how entropy maps to temperature"));
add((new field_num("repeat_last_n", params.sampling.penalty_last_n))
->set_hard_limits(-1, INT32_MAX)
->set_desc("Last n tokens to consider for penalizing repetition (0 = disabled, -1 = ctx-size)"));
->set_hard_limits(0, INT32_MAX)
->set_desc("Last n tokens to consider for penalizing repetition (0 = disabled)"));
add((new field_num("repeat_penalty", params.sampling.penalty_repeat))
->set_desc("Control the repetition of token sequences in the generated text (1.0 = disabled)"));
@@ -151,8 +151,8 @@ std::vector<std::unique_ptr<field>> make_llama_cmpl_schema(const common_params &
->set_desc("Tokens that extend repetition beyond this length receive exponentially increasing penalty: multiplier * base ^ (sequence_length - allowed_length)"));
add((new field_num("dry_penalty_last_n", params.sampling.dry_penalty_last_n))
->set_hard_limits(-1, INT32_MAX)
->set_desc("How many tokens to scan for repetitions (0 = disabled, -1 = context size)"));
->set_hard_limits(0, INT32_MAX)
->set_desc("How many tokens to scan for repetitions (0 = disabled)"));
add((new field_num("mirostat", params.sampling.mirostat))
->set_limits(0, 2)
@@ -515,7 +515,6 @@ std::vector<std::unique_ptr<field>> make_llama_cmpl_schema(const common_params &
task_params eval_llama_cmpl_schema(
const llama_vocab * vocab,
const common_params & params_base,
const int n_ctx_slot,
const std::vector<llama_logit_bias> & logit_bias_eog,
const json & data) {
task_params params;
@@ -549,15 +548,6 @@ task_params eval_llama_cmpl_schema(
// post-processing
{
if (params.sampling.penalty_last_n == -1) {
// note: should be the slot's context and not the full context, but it's ok
params.sampling.penalty_last_n = n_ctx_slot;
}
if (params.sampling.dry_penalty_last_n == -1) {
params.sampling.dry_penalty_last_n = n_ctx_slot;
}
// if "reasoning_format" is not provided, its handler will not be called, we will need to handle it here
auto reasoning_format = params.chat_parser_params.reasoning_format;
params.chat_parser_params.reasoning_in_content = params.stream && (reasoning_format == COMMON_REASONING_FORMAT_DEEPSEEK_LEGACY);
-1
View File
@@ -98,7 +98,6 @@ std::vector<std::unique_ptr<field>> make_llama_cmpl_schema(
task_params eval_llama_cmpl_schema(
const llama_vocab * vocab,
const common_params & params_base,
const int n_ctx_slot,
const std::vector<llama_logit_bias> & logit_bias_eog,
const json & data);
+244 -68
View File
@@ -10,17 +10,67 @@
#include <ctime>
#include <atomic>
#include <cstring>
#include <cstdlib>
#include <algorithm>
#include <unordered_set>
#include <tuple>
#include <functional>
#include <memory>
#if defined(_WIN32)
# ifndef NOMINMAX
# define NOMINMAX
# endif
# include <windows.h>
#endif
namespace fs = std::filesystem;
//
// internal helpers
//
#if defined(_WIN32)
// A chunk can end in the middle of a multi-byte sequence, so the incomplete
// tail is dropped before validating what precedes it.
static bool is_utf8_text(const std::string & text) {
return is_valid_utf8(text.substr(0, validate_utf8(text)));
}
// A child process writes its output in the OEM code page, which is not UTF-8
// on a western Windows install, so accented text reaches the JSON layer as
// invalid bytes and is replaced there. Text that already decodes as UTF-8 is
// returned untouched, so a child that emits UTF-8 is never decoded twice.
// run() spawns without a console, so the console code page does not apply.
static std::string console_output_to_utf8(const std::string & text) {
if (text.empty() || is_utf8_text(text)) {
return text;
}
const UINT cp = GetOEMCP();
// fail rather than emit replacement characters when the code page is wrong
const int wide_len = MultiByteToWideChar(cp, MB_ERR_INVALID_CHARS, text.data(), (int) text.size(), nullptr, 0);
if (wide_len <= 0) {
return text;
}
std::wstring wide(wide_len, L'\0');
MultiByteToWideChar(cp, MB_ERR_INVALID_CHARS, text.data(), (int) text.size(), wide.data(), wide_len);
const int utf8_len = WideCharToMultiByte(CP_UTF8, 0, wide.data(), wide_len, nullptr, 0, nullptr, nullptr);
if (utf8_len <= 0) {
return text;
}
std::string utf8(utf8_len, '\0');
WideCharToMultiByte(CP_UTF8, 0, wide.data(), wide_len, utf8.data(), utf8_len, nullptr, nullptr);
return utf8;
}
#else
static std::string console_output_to_utf8(const std::string & text) {
return text;
}
#endif
json server_tool::to_json() const {
return {
{"display_name", display_name},
@@ -34,7 +84,40 @@ json server_tool::to_json() const {
}
static constexpr size_t SERVER_TOOL_GIT_LS_FILES_MAX_OUTPUT = 8 * 1024 * 1024; // 8 MB
static constexpr int SERVER_TOOL_GIT_LS_FILES_TIMEOUT = 15; // seconds
// budget for one listing call, shared by the git and walker paths
static constexpr int SERVER_TOOL_LIST_ENTRIES_TIMEOUT = 15; // seconds
// entry kinds a directory listing may return
enum class list_kind {
files, // regular files only
dirs, // directories only
all, // both
};
// home directory, read once at first use (getenv is not thread safe against setenv)
static const std::string & home_dir() {
static const std::string home = [] {
const char * h = getenv("HOME");
#ifdef _WIN32
if (h == nullptr) h = getenv("USERPROFILE");
#endif
return h ? std::string(h) : std::string();
}();
return home;
}
static std::string expand_home(const std::string & path) {
if (path.empty() || path[0] != '~') return path;
if (path.size() > 1 && path[1] != '/' && path[1] != '\\') return path;
const std::string & home = home_dir();
if (home.empty()) return path;
return home + path.substr(1);
}
// depth of a '/'-separated relative path: "a/b/c" is 3
static int entry_depth(const std::string & rel) {
return 1 + (int) std::count(rel.begin(), rel.end(), '/');
}
class tools_io {
public:
@@ -51,8 +134,17 @@ public:
virtual bool file_size(const std::string & path, uintmax_t & out_size) const = 0;
virtual bool read_file(const std::string & path, std::string & out) const = 0;
virtual bool write_file(const std::string & path, const std::string & content) const = 0;
// paths relative to `base`, '/'-separated; sets `err` if `base` isn't a directory
virtual std::vector<std::string> list_files(const std::string & base, std::string & err) const = 0;
// resolve `path` against the IO's working directory; absolute paths are returned unchanged
virtual std::string resolve(const std::string & path) const = 0;
struct list_entry {
std::string rel; // '/'-separated, relative to `base`
bool is_dir = false;
};
// entries relative to `base`; sets `err` if `base` isn't a directory
// max_depth == 0 means unlimited, 1 means direct children of `base` only
// `base` must already be resolved (absolute); `caller_path` is the path the
// caller passed, used only for error messages
virtual std::vector<list_entry> list_entries(const std::string & base, const std::string & caller_path, int max_depth, list_kind kind, std::string & err, bool & truncated) const = 0;
// on_chunk, if set, is called with each chunk of output as it is read (before truncation cuts in);
// returning false terminates the process early (e.g. the client disconnected)
virtual exec_result run(
@@ -67,6 +159,22 @@ public:
// cwd, if non-empty, is used to resolve relative paths and as the working directory for run()
explicit tools_io_basic(std::string cwd = "") : cwd(std::move(cwd)) {}
// expands a leading `~`, then resolves `path` against `cwd` (or the server
// working directory when `cwd` is unset); the result is always absolute
std::string resolve(const std::string & path) const override {
std::string p = expand_home(path);
if (fs::path(p).is_absolute()) {
return p;
}
if (cwd.empty()) {
std::error_code ec;
fs::path cur = fs::current_path(ec);
if (ec) return p;
return (cur / p).string();
}
return (fs::path(cwd) / p).string();
}
bool is_directory(const std::string & path) const override {
std::error_code ec;
return fs::is_directory(resolve(path), ec) && !ec;
@@ -105,34 +213,41 @@ public:
return (bool) f;
}
std::vector<std::string> list_files(const std::string & base, std::string & err) const override {
std::vector<list_entry> list_entries(const std::string & base, const std::string & caller_path, int max_depth, list_kind kind, std::string & err, bool & truncated) const override {
err.clear();
std::string abs_base = resolve(base);
if (!is_directory(base)) {
err = "path does not exist or is not a directory: " + base;
truncated = false;
std::error_code ec;
if (!fs::is_directory(base, ec) || ec) {
err = "path does not exist or is not a directory: " + caller_path;
return {};
}
auto res = run(
{"git", "-C", abs_base, "ls-files", "--cached", "--others", "--exclude-standard"},
SERVER_TOOL_GIT_LS_FILES_MAX_OUTPUT, SERVER_TOOL_GIT_LS_FILES_TIMEOUT);
const auto deadline = std::chrono::steady_clock::now() + std::chrono::seconds(SERVER_TOOL_LIST_ENTRIES_TIMEOUT);
if (res.exit_code == 0 && !res.timed_out) {
std::vector<std::string> result;
std::istringstream iss(res.output);
std::string line;
while (std::getline(iss, line)) {
if (!line.empty() && line.back() == '\r') line.pop_back();
if (line.empty()) continue;
std::replace(line.begin(), line.end(), '\\', '/');
if (is_regular_file((fs::path(base) / line).string())) {
result.push_back(line);
// git ls-files cannot list directories; use the walker when they are requested
if (kind == list_kind::files) {
auto res = run(
{"git", "-C", base, "ls-files", "--cached", "--others", "--exclude-standard"},
SERVER_TOOL_GIT_LS_FILES_MAX_OUTPUT, SERVER_TOOL_LIST_ENTRIES_TIMEOUT);
if (res.exit_code == 0 && !res.timed_out) {
std::vector<list_entry> result;
std::istringstream iss(res.output);
std::string line;
while (std::getline(iss, line)) {
if (!line.empty() && line.back() == '\r') line.pop_back();
if (line.empty()) continue;
std::replace(line.begin(), line.end(), '\\', '/');
if (max_depth > 0 && entry_depth(line) > max_depth) continue;
if (is_regular_file((fs::path(base) / line).string())) {
result.push_back({line, false});
}
}
return result;
}
return result;
}
return list_files_fallback(abs_base);
return list_entries_fallback(base, max_depth, kind, deadline, truncated);
}
exec_result run(
@@ -179,14 +294,14 @@ public:
size_t len = strlen(buf);
if (output.size() + len <= max_output) {
output.append(buf, len);
if (on_chunk && !on_chunk(std::string(buf, len))) {
if (on_chunk && !on_chunk(console_output_to_utf8(std::string(buf, len)))) {
proc.terminate();
break;
}
} else {
size_t remaining = max_output - output.size();
output.append(buf, remaining);
if (on_chunk && remaining > 0) on_chunk(std::string(buf, remaining));
if (on_chunk && remaining > 0) on_chunk(console_output_to_utf8(std::string(buf, remaining)));
truncated = true;
}
}
@@ -200,7 +315,7 @@ public:
res.exit_code = proc.join();
res.output = output;
res.output = console_output_to_utf8(output);
res.timed_out = timed_out.load();
if (truncated) {
res.output += "\n[output truncated]";
@@ -211,14 +326,6 @@ public:
private:
std::string cwd;
// resolves `path` against `cwd` if `path` is relative and `cwd` is set; otherwise returns `path` unchanged
std::string resolve(const std::string & path) const {
if (cwd.empty() || fs::path(path).is_absolute()) {
return path;
}
return (fs::path(cwd) / path).string();
}
static const std::unordered_set<std::string> & junk_dir_names() {
static const std::unordered_set<std::string> names = {
".git", ".svn", ".hg", "node_modules", "__pycache__",
@@ -227,28 +334,50 @@ private:
return names;
}
std::vector<std::string> list_files_fallback(const std::string & base) const {
std::vector<std::string> result;
std::vector<list_entry> list_entries_fallback(const std::string & base, int max_depth, list_kind kind,
std::chrono::steady_clock::time_point deadline, bool & truncated) const {
std::vector<list_entry> result;
std::error_code ec;
std::vector<std::pair<fs::path, fs::path>> stack;
stack.emplace_back(fs::path(base), fs::path());
std::vector<std::tuple<fs::path, fs::path, int>> stack;
stack.emplace_back(fs::path(base), fs::path(), 0);
while (!stack.empty()) {
auto [dir, rel_dir] = stack.back();
auto [dir, rel_dir, depth] = stack.back();
stack.pop_back();
for (const auto & entry : fs::directory_iterator(dir, fs::directory_options::skip_permission_denied, ec)) {
// the throwing increment would escape the tool on a directory that
// goes away mid walk, so step the iterator explicitly
fs::directory_iterator it(dir, fs::directory_options::skip_permission_denied, ec);
for (const fs::directory_iterator end; it != end; it.increment(ec)) {
if (ec) break;
if (std::chrono::steady_clock::now() >= deadline) {
truncated = true;
return result;
}
const fs::directory_entry & entry = *it;
std::string fname = entry.path().filename().string();
std::error_code tec;
if (entry.is_directory(tec)) {
std::string rel = (rel_dir / fname).string();
std::replace(rel.begin(), rel.end(), '\\', '/');
if (kind == list_kind::dirs || kind == list_kind::all) {
result.push_back({rel, true});
}
// junk directories stay selectable but are never walked: they
// hold nothing worth searching and can be enormous
if (junk_dir_names().count(fname) > 0) continue;
stack.emplace_back(entry.path(), rel_dir / fname);
// do not descend into symlinks: a link can point back to an
// ancestor and loop forever
if (!entry.is_symlink(tec) && (max_depth == 0 || depth + 1 < max_depth)) {
stack.emplace_back(entry.path(), rel_dir / fname, depth + 1);
}
} else if (entry.is_regular_file(tec)) {
std::string rel = (rel_dir / fname).string();
std::replace(rel.begin(), rel.end(), '\\', '/');
result.push_back(rel);
if (kind == list_kind::files || kind == list_kind::all) {
result.push_back({rel, false});
}
}
}
}
@@ -363,6 +492,9 @@ struct server_tool_read_file : server_tool {
//
static constexpr size_t SERVER_TOOL_FILE_SEARCH_MAX_RESULTS = 100;
static constexpr const char * SERVER_TOOL_FILE_SEARCH_TYPE_FILE = "file";
static constexpr const char * SERVER_TOOL_FILE_SEARCH_TYPE_DIR = "dir";
static constexpr const char * SERVER_TOOL_FILE_SEARCH_TYPE_ALL = "all";
struct server_tool_file_glob_search : server_tool {
server_tool_file_glob_search() {
@@ -382,13 +514,18 @@ struct server_tool_file_glob_search : server_tool {
"and common junk directories (.git, node_modules, build, dist, etc.) otherwise. "
"A pattern with no '/' (e.g. \"*.cpp\") matches the file's basename at any depth. "
"A pattern containing '/' matches the full relative path; unless already anchored with "
"\"**/\" or a leading '/', it is automatically prefixed with \"**/\"."},
"\"**/\" or a leading '/', it is automatically prefixed with \"**/\". "
"Use type=\"dir\" or \"all\" to also list directories; directory entries are suffixed with '/' in the output. "
"Note: directory listings do not apply .gitignore filtering."},
{"parameters", {
{"type", "object"},
{"properties", {
{"path", {{"type", "string"}, {"description", "Base directory to search in"}}},
{"include", {{"type", "string"}, {"description", "Glob pattern for files to include (e.g. \"*.cpp\" or \"src/**/*.cpp\"). Default: **"}}},
{"exclude", {{"type", "string"}, {"description", "Glob pattern for files to exclude"}}},
{"path", {{"type", "string"}, {"description", "Base directory to search in"}}},
{"include", {{"type", "string"}, {"description", "Glob pattern for files to include (e.g. \"*.cpp\" or \"src/**/*.cpp\"). Default: **"}}},
{"exclude", {{"type", "string"}, {"description", "Glob pattern for files to exclude"}}},
{"type", {{"type", "string"}, {"description", "Entry type to return: \"file\" (default), \"dir\" or \"all\""}}},
{"max_depth", {{"type", "integer"}, {"description", "Maximum depth to descend into subdirectories (default: 0 = unlimited; 1 = direct children only)"}}},
{"limit", {{"type", "integer"}, {"description", string_format("Maximum number of results to return (default %zu; values below 1 fall back to the default)", SERVER_TOOL_FILE_SEARCH_MAX_RESULTS)}}},
}},
{"required", json::array({"path"})},
}},
@@ -397,30 +534,56 @@ struct server_tool_file_glob_search : server_tool {
}
json invoke(json params, server_tool::stream *) const override {
std::string base = params.at("path").get<std::string>();
std::string include = json_value(params, "include", std::string("**"));
std::string exclude = json_value(params, "exclude", std::string(""));
auto io = make_tools_io(params);
std::string base = io->resolve(params.at("path").get<std::string>());
// normalize to forward slashes so the web UI (which assumes '/') can
// join the relative entries into absolute paths on Windows too
std::replace(base.begin(), base.end(), '\\', '/');
std::string include = json_value(params, "include", std::string("**"));
std::string exclude = json_value(params, "exclude", std::string(""));
std::string type = json_value(params, "type", std::string("file"));
int max_depth = std::max(0, json_value(params, "max_depth", 0));
int limit = json_value(params, "limit", (int) SERVER_TOOL_FILE_SEARCH_MAX_RESULTS);
if (limit < 1) limit = SERVER_TOOL_FILE_SEARCH_MAX_RESULTS;
limit = std::min(limit, (int) SERVER_TOOL_FILE_SEARCH_MAX_RESULTS);
list_kind kind;
if (type == SERVER_TOOL_FILE_SEARCH_TYPE_FILE) {
kind = list_kind::files;
} else if (type == SERVER_TOOL_FILE_SEARCH_TYPE_DIR) {
kind = list_kind::dirs;
} else if (type == SERVER_TOOL_FILE_SEARCH_TYPE_ALL) {
kind = list_kind::all;
} else {
return {{"error", "invalid type: " + type + " (expected \"file\", \"dir\" or \"all\")"}};
}
std::string err;
auto files = io->list_files(base, err);
bool truncated = false;
auto entries = io->list_entries(base, params.at("path").get<std::string>(), max_depth, kind, err, truncated);
if (!err.empty()) {
return {{"error", err}};
}
std::vector<std::string> matches;
for (const auto & rel : files) {
if (!path_glob_match(include, rel)) continue;
if (!exclude.empty() && path_glob_match(exclude, rel)) continue;
matches.push_back(rel);
std::vector<tools_io::list_entry> matches;
for (const auto & entry : entries) {
if (!path_glob_match(include, entry.rel)) continue;
if (!exclude.empty() && path_glob_match(exclude, entry.rel)) continue;
matches.push_back(entry);
}
size_t total = matches.size();
size_t shown = std::min(total, SERVER_TOOL_FILE_SEARCH_MAX_RESULTS);
size_t shown = std::min(total, (size_t) limit);
std::ostringstream output_text;
json entries_json = json::array();
for (size_t i = 0; i < shown; i++) {
output_text << matches[i] << "\n";
output_text << matches[i].rel << (matches[i].is_dir ? "/" : "") << "\n";
entries_json.push_back({
{"path", matches[i].rel},
{"type", matches[i].is_dir ? "dir" : "file"},
});
}
output_text << "\n---\nTotal matches: " << total << "\n";
@@ -429,8 +592,16 @@ struct server_tool_file_glob_search : server_tool {
"[%zu results limit reached (%zu total matches). Refine the glob pattern to narrow the search.]\n",
shown, total);
}
if (truncated) {
output_text << "[search timed out, results truncated]\n";
}
return {{"plain_text_response", output_text.str()}};
// `base` is always absolute (resolve falls back to the server cwd), so
// API clients (e.g. the web UI picker) can join the relative entries
// into absolute paths. `plain_text_response` is what the model sees;
// `entries` is the same data as structured JSON for the UI picker,
// which reads `entries`/`base` instead of re-parsing the text.
return {{"plain_text_response", output_text.str()}, {"entries", entries_json}, {"base", base}};
}
};
@@ -513,18 +684,20 @@ struct server_tool_grep_search : server_tool {
// collect (absolute_path, display_path) pairs to search
std::vector<std::pair<std::string, std::string>> files;
if (io->is_regular_file(path)) {
files.emplace_back(path, path);
} else if (io->is_directory(path)) {
const std::string abs_path = io->resolve(path);
if (io->is_regular_file(abs_path)) {
files.emplace_back(abs_path, path);
} else if (io->is_directory(abs_path)) {
std::string err;
auto candidates = io->list_files(path, err);
bool truncated = false;
auto candidates = io->list_entries(abs_path, path, 0, list_kind::files, err, truncated);
if (!err.empty()) {
return {{"error", err}};
}
for (const auto & rel : candidates) {
if (!path_glob_match(include, rel)) continue;
if (!exclude.empty() && path_glob_match(exclude, rel)) continue;
files.emplace_back((fs::path(path) / rel).string(), rel);
for (const auto & entry : candidates) {
if (!path_glob_match(include, entry.rel)) continue;
if (!exclude.empty() && path_glob_match(exclude, entry.rel)) continue;
files.emplace_back((fs::path(abs_path) / entry.rel).string(), entry.rel);
}
} else {
return {{"error", "path does not exist: " + path}};
@@ -1094,6 +1267,9 @@ struct server_tool_get_datetime : server_tool {
// get_info: returns runtime info (OS name/version and cwd)
//
static constexpr size_t SERVER_TOOL_GET_INFO_MAX_OUTPUT = 4096;
static constexpr int SERVER_TOOL_GET_INFO_TIMEOUT = 5; // seconds
struct server_tool_get_info : server_tool {
server_tool_get_info() {
name = "get_info";
@@ -1119,9 +1295,9 @@ struct server_tool_get_info : server_tool {
auto io = make_tools_io(params);
#ifdef _WIN32
auto res = io->run({"cmd", "/c", "ver"}, 4096, 5);
auto res = io->run({"cmd", "/c", "ver"}, SERVER_TOOL_GET_INFO_MAX_OUTPUT, SERVER_TOOL_GET_INFO_TIMEOUT);
#else
auto res = io->run({"uname", "-a"}, 4096, 5);
auto res = io->run({"uname", "-a"}, SERVER_TOOL_GET_INFO_MAX_OUTPUT, SERVER_TOOL_GET_INFO_TIMEOUT);
#endif
// "ver" prints a blank line before the version, so the output is stripped on both ends;
// a failed spawn or a timeout leaves a diagnostic in res.output, which is not an OS name
@@ -164,3 +164,101 @@ def test_tools_builtin_edit_file_rejects_overlapping_edits():
finally:
if os.path.exists(log_path):
os.remove(log_path)
def test_tools_builtin_file_glob_search_type_dir(tmp_path):
global server
server.start()
(tmp_path / "project-alpha" / "src").mkdir(parents=True)
(tmp_path / "project-alpha" / "README.md").write_text("alpha")
(tmp_path / "project-alpha" / "src" / "main.cpp").write_text("int main() {}")
(tmp_path / "project-beta").mkdir()
(tmp_path / "project-beta" / "notes.txt").write_text("beta")
res = call_tool("file_glob_search", {"path": str(tmp_path), "type": "dir"})
text = res["plain_text_response"]
assert "project-alpha/" in text
assert "project-beta/" in text
assert "project-alpha/src/" in text
assert "README.md" not in text
types = {e["path"]: e["type"] for e in res["entries"]}
assert types["project-alpha"] == "dir"
assert types["project-alpha/src"] == "dir"
res_all = call_tool("file_glob_search", {"path": str(tmp_path), "type": "all", "include": "*proj*"})
paths = [e["path"] for e in res_all["entries"]]
assert "project-alpha" in paths
assert "project-beta" in paths
def test_tools_builtin_file_glob_search_max_depth_and_limit(tmp_path):
global server
server.start()
(tmp_path / "a" / "b" / "c").mkdir(parents=True)
(tmp_path / "top.txt").write_text("top")
(tmp_path / "a" / "mid.txt").write_text("mid")
(tmp_path / "a" / "b" / "deep.txt").write_text("deep")
res = call_tool("file_glob_search", {"path": str(tmp_path), "max_depth": 1})
assert "top.txt" in res["plain_text_response"]
assert "mid.txt" not in res["plain_text_response"]
res = call_tool("file_glob_search", {"path": str(tmp_path), "max_depth": 2})
assert "mid.txt" in res["plain_text_response"]
assert "deep.txt" not in res["plain_text_response"]
res = call_tool("file_glob_search", {"path": str(tmp_path), "limit": 1})
assert len(res["entries"]) == 1
assert "Total matches: 3" in res["plain_text_response"]
def test_tools_builtin_file_glob_search_rejects_invalid_type(tmp_path):
global server
server.start()
err = call_tool_expect_error("file_glob_search", {"path": str(tmp_path), "type": "bogus"})
assert "invalid type" in err
def test_tools_builtin_cwd_header_overrides_model_param(tmp_path):
global server
server.start()
workdir = tmp_path / "workdir"
workdir.mkdir()
(workdir / "marker.txt").write_text("marker")
# a model-provided "cwd" in the params is overridden by the x-tool-cwd header
res = call_tool("read_file", {"path": "marker.txt", "cwd": "/definitely/not/a/real/path"},
headers={"x-tool-cwd": str(workdir)})
assert "marker" in res["plain_text_response"]
def test_tools_builtin_cwd_relative_paths(tmp_path):
global server
server.start()
workdir = tmp_path / "workdir"
workdir.mkdir()
(workdir / "rel.txt").write_text("relative-content")
headers = {"x-tool-cwd": str(workdir)}
# relative paths in file tools resolve against the header cwd
res = call_tool("read_file", {"path": "rel.txt"}, headers=headers)
assert "relative-content" in res["plain_text_response"]
res = call_tool("write_file", {"path": "sub/out.txt", "content": "written"}, headers=headers)
assert (workdir / "sub" / "out.txt").read_text() == "written"
res = call_tool("file_glob_search", {"path": ".", "include": "*.txt"}, headers=headers)
assert "rel.txt" in res["plain_text_response"]
# absolute paths are unaffected by the cwd
other = tmp_path / "other"
other.mkdir()
(other / "abs.txt").write_text("absolute-content")
res = call_tool("read_file", {"path": str(other / "abs.txt")}, headers=headers)
assert "absolute-content" in res["plain_text_response"]
+2 -1
View File
@@ -11,7 +11,8 @@ const config: StorybookConfig = {
'@chromatic-com/storybook',
'@storybook/addon-vitest',
'@storybook/addon-a11y',
'@storybook/addon-docs'
'@storybook/addon-docs',
'@storybook/addon-mcp'
],
framework: '@storybook/sveltekit',
viteFinal: async (config) => {
-12
View File
@@ -1,12 +0,0 @@
import * as a11yAddonAnnotations from '@storybook/addon-a11y/preview';
import { setProjectAnnotations } from '@storybook/sveltekit';
import * as previewAnnotations from './preview';
import { beforeAll } from 'vitest';
const project = setProjectAnnotations([a11yAddonAnnotations, previewAnnotations]);
beforeAll(async () => {
if (project.beforeAll) {
await project.beforeAll();
}
});
+1 -1
View File
@@ -89,7 +89,7 @@ Llama UI supports two server operation modes:
```bash
cd tools/ui
npm install
npm ci
```
### 2. Start llama-server
+877 -592
View File
File diff suppressed because it is too large Load Diff
+21 -18
View File
@@ -27,20 +27,20 @@
"cleanup": "rm -rf .svelte-kit build node_modules test-results dist dev-dist debug-storybook.log static/pwa-*.png static/maskable-icon-*.png static/apple-touch-icon-*.png static/apple-splash-*.png static/favicon*.ico"
},
"devDependencies": {
"@chromatic-com/storybook": "5.0.0",
"@chromatic-com/storybook": "5.2.1",
"@eslint/compat": "1.4.1",
"@eslint/js": "9.39.2",
"@internationalized/date": "3.12.2",
"@lucide/svelte": "1.25.0",
"@modelcontextprotocol/sdk": "1.26.0",
"@modelcontextprotocol/sdk": "1.30.0",
"@playwright/test": "1.56.1",
"@storybook/addon-a11y": "10.2.4",
"@storybook/addon-docs": "10.2.4",
"@storybook/addon-svelte-csf": "5.0.10",
"@storybook/addon-vitest": "10.2.4",
"@storybook/sveltekit": "10.2.4",
"@storybook/addon-a11y": "10.5.6",
"@storybook/addon-docs": "10.5.6",
"@storybook/addon-svelte-csf": "5.1.2",
"@storybook/addon-vitest": "10.5.6",
"@storybook/sveltekit": "10.5.6",
"@sveltejs/adapter-static": "3.0.10",
"@sveltejs/kit": "2.60.1",
"@sveltejs/kit": "2.70.2",
"@sveltejs/vite-plugin-svelte": "6.2.1",
"@tailwindcss/forms": "0.5.10",
"@tailwindcss/typography": "0.5.16",
@@ -48,16 +48,16 @@
"@types/node": "24.13.0",
"@vite-pwa/assets-generator": "1.0.2",
"@vite-pwa/sveltekit": "1.1.0",
"@vitest/browser": "4.1.8",
"@vitest/browser-playwright": "4.1.8",
"@vitest/coverage-v8": "4.1.8",
"@vitest/browser": "4.1.10",
"@vitest/browser-playwright": "4.1.10",
"@vitest/coverage-v8": "4.1.10",
"bits-ui": "2.18.1",
"clsx": "2.1.1",
"dexie": "4.4.3",
"dompurify": "3.4.11",
"dompurify": "3.4.13",
"eslint": "9.39.4",
"eslint-config-prettier": "10.1.8",
"eslint-plugin-storybook": "10.4.2",
"eslint-plugin-storybook": "10.5.6",
"eslint-plugin-svelte": "3.19.0",
"fflate": "0.8.3",
"globals": "16.5.0",
@@ -82,7 +82,7 @@
"remark-math": "6.0.0",
"remark-rehype": "11.1.2",
"sass": "1.100.0",
"storybook": "10.4.2",
"storybook": "10.5.6",
"svelte": "5.56.1",
"svelte-check": "4.6.0",
"svelte-sonner": "1.1.1",
@@ -95,13 +95,16 @@
"unified": "11.0.5",
"unist-util-visit": "5.1.0",
"uuid": "13.0.2",
"vite": "7.3.5",
"vite": "7.3.6",
"vite-plugin-devtools-json": "0.2.1",
"vitest": "4.1.8",
"vitest": "4.1.10",
"vitest-browser-svelte": "2.1.1",
"workbox-window": "7.4.1"
"workbox-window": "7.4.1",
"@storybook/addon-mcp": "0.7.0"
},
"overrides": {
"cookie": "1.1.1"
"cookie": "1.1.1",
"sharp": "0.35.3",
"valibot": "1.4.2"
}
}
+1 -1
View File
@@ -14,7 +14,7 @@ cd ../../
# Ensure node_modules are installed
if [ ! -d "tools/ui/node_modules" ]; then
echo "📦 Installing npm dependencies..."
cd tools/ui && npm install && cd ../../
cd tools/ui && npm ci && cd ../../
fi
# Check and install git hooks if missing
+1 -1
View File
@@ -14,7 +14,7 @@ cd "$REPO_ROOT/tools/ui"
# Check that node_modules exists
if [ ! -d "node_modules" ]; then
echo "❌ node_modules not found. Run 'npm install' first."
echo "❌ node_modules not found. Run 'npm ci' first."
exit 1
fi
+1 -1
View File
@@ -30,7 +30,7 @@ cd "$REPO_ROOT/tools/ui"
# Check that node_modules exists
if [ ! -d "node_modules" ]; then
echo "❌ node_modules not found. Run 'npm install' first."
echo "❌ node_modules not found. Run 'npm ci' first."
exit 1
fi
+9
View File
@@ -142,5 +142,14 @@ declare global {
interface Window {
idxThemeStyle?: number;
idxCodeBlock?: number;
// File System Access API - missing from older DOM lib versions.
// Used by ChatFormWorkingDirectory's native folder picker. Feature availability
// is gated at runtime via `typeof window.showDirectoryPicker === 'function'`.
showDirectoryPicker: (options?: {
id?: string;
mode?: 'read' | 'readwrite';
startIn?: FileSystemHandle | string;
}) => Promise<FileSystemDirectoryHandle>;
}
}
@@ -6,6 +6,7 @@
ChatFormMcpResourcesList,
ChatFormPickers,
ChatFormTextarea,
ChatFormWorkingDirectory,
DialogMcpResourcesBrowser
} from '$lib/components/app';
import {
@@ -31,7 +32,13 @@
import { chatStore } from '$lib/stores/chat.svelte';
import { mcpStore } from '$lib/stores/mcp.svelte';
import { mcpHasResourceAttachments } from '$lib/stores/mcp-resources.svelte';
import { conversationsStore, activeMessages } from '$lib/stores/conversations.svelte';
import { toolsStore } from '$lib/stores/tools.svelte';
import {
conversationsStore,
activeMessages,
activeConversation,
pendingCwd
} from '$lib/stores/conversations.svelte';
import type { GetPromptResult, MCPPromptInfo, MCPResourceInfo, PromptMessage } from '$lib/types';
import { isIMEComposing, parseClipboardContent, uuid } from '$lib/utils';
import {
@@ -107,6 +114,15 @@
let isInlineResourcePickerOpen = $state(false);
let resourceSearchQuery = $state('');
let cwd = $derived(activeConversation()?.cwd ?? pendingCwd());
async function handleWorkingDirectoryChange(value: string | null) {
await conversationsStore.setCwd(value);
if (conversationsStore.activeConversation) {
await chatStore.recordCwdChange(value?.trim() || null);
}
}
// Resource Dialog State
let isResourceDialogOpen = $state(false);
let preSelectedResourceUri = $state<string | undefined>(undefined);
@@ -155,6 +171,12 @@
audioRecorder = new AudioRecorder();
});
// Defer so the closing popover's focus scope tears down first - bits-ui
// yanks a synchronous focus() back into the still-mounted popover.
function refocusInput() {
queueMicrotask(() => textareaRef?.focus());
}
export function focus() {
textareaRef?.focus();
}
@@ -470,7 +492,7 @@
<ChatFormFileInputInvisible bind:this={fileInputRef} onFileSelect={handleFileSelect} />
<form
class="relative {className}"
class="relative grid {className}"
onsubmit={(event) => {
event.preventDefault();
@@ -559,6 +581,15 @@
</div>
<ContextGaugePopup />
{#if toolsStore.builtinTools.length > 0}
<ChatFormWorkingDirectory
directory={cwd}
onChange={handleWorkingDirectoryChange}
onClose={refocusInput}
{disabled}
/>
{/if}
</form>
<DialogMcpResourcesBrowser
@@ -0,0 +1,479 @@
<script lang="ts">
import { FolderOpen } from '@lucide/svelte';
import { untrack } from 'svelte';
import { SvelteMap } from 'svelte/reactivity';
import { ToolsService } from '$lib/services/tools.service';
import { toolsStore } from '$lib/stores/tools.svelte';
import { BuiltInTool, GlobSearchType, KeyboardKey } from '$lib/enums';
import {
abbreviateHome,
buildCaseInsensitiveGlob,
joinPath,
lastPathSegment,
rankEntries,
splitPathQuery,
type GlobEntry
} from '$lib/utils';
import { debounce } from '$lib/utils/debounce';
import * as Popover from '$lib/components/ui/popover';
import SearchInput from '$lib/components/app/forms/SearchInput.svelte';
import ChatFormWorkingDirectoryChip from './ChatFormWorkingDirectoryChip.svelte';
import ChatFormWorkingDirectoryResultsList from './ChatFormWorkingDirectoryResultsList.svelte';
import {
DEFAULT_MOBILE_BREAKPOINT,
GLOB_WILDCARD,
HOME_TILDE,
MAX_RESULTS_SHOWN,
NATIVE_LIMIT,
NATIVE_MAX_DEPTH,
PATH_NAV_MAX_DEPTH,
SEARCH_DEBOUNCE_MS,
SEARCH_LIMIT,
SEARCH_MAX_DEPTH
} from '$lib/constants';
// Microtask delay so the popover's focus scope tears down first.
const FOCUS_DELAY_MS = 0;
interface Props {
class?: string;
disabled?: boolean;
directory?: string | null;
onChange?: (directory: string | null) => void;
/**
* Lets the host refocus the chat input so typing can resume without
* an extra click after the popover closes.
*/
onClose?: () => void;
}
let {
class: className = '',
disabled = false,
directory = $bindable(null),
onChange,
onClose
}: Props = $props();
// File System Access API is opt-in: when available (Chrome / Edge / Opera) the popover
// exposes a "Browse" button that opens the native folder picker. When unavailable the
// popover still works via the text input - no alerts, no upload semantics.
const pickerSupported =
typeof window !== 'undefined' && typeof window.showDirectoryPicker === 'function';
// Popover open state; the element handles outside-click and Escape.
let isOpen = $state(false);
let inputValue = $state('');
let searchInputRef: HTMLInputElement | null = $state(null);
let queryResults = $state<string[]>([]);
let isSearching = $state(false);
let searchError = $state<string | null>(null);
let hoveredIndex = $state(-1);
// Bumped only by ArrowUp/ArrowDown handlers; the list scrolls the
// highlighted row into view only via this trigger, never on hover.
let scrollTrigger = $state(0);
let listContainer = $state<HTMLDivElement | null>(null);
// Absolute home directory on the server, resolved once per session by
// the tools store. Anchors both the search scope and the chip's `~`
// abbreviation.
let homeBase = $derived(toolsStore.serverHome);
// AbortController + sequence counter to discard stale responses when the user
// keeps typing; a newer call aborts the previous one. The sequence counter
// also covers the gap between abort and the catch handler.
let searchController: AbortController | null = null;
let searchSeq = 0;
// Cache of the last file_glob_search result per (parent, include, max_depth),
// so repeated queries in the same directory don't re-walk the tree. Entries
// expire after a short TTL.
const SEARCH_CACHE_TTL_MS = 2000;
const searchCache = new SvelteMap<string, { results: GlobEntry[]; base: string; at: number }>();
const runSearch = debounce((query: string) => {
void doSearch(query);
}, SEARCH_DEBOUNCE_MS);
// Resolve home eagerly on mount so the chip can abbreviate before the
// user opens the picker. resolveServerHome() is cached, so repeat calls
// (e.g. from handleOpenChange) are no-ops.
$effect(() => {
if (typeof window === 'undefined') return;
void toolsStore.resolveServerHome();
});
// Auto-focus the search input when the popover opens.
// HTML `autofocus` is unreliable on dynamically shown elements, so we
// use a microtask (0ms setTimeout) after the effect flushes.
$effect(() => {
if (!isOpen) return;
setTimeout(() => searchInputRef?.focus(), FOCUS_DELAY_MS);
});
let lastScrollTrigger: number | null = null;
// hoveredIndex/queryResults are untracked so hover and result replacement
// never re-fire the scroll; keyboard nav is the only path that bumps the trigger
$effect(() => {
if (scrollTrigger === lastScrollTrigger) return;
lastScrollTrigger = scrollTrigger;
untrack(() => {
if (!listContainer) return;
if (hoveredIndex < 0 || hoveredIndex >= queryResults.length) return;
const selectedElement = listContainer.querySelector(
`[data-result-index="${hoveredIndex}"]`
) as HTMLElement | null;
selectedElement?.scrollIntoView({ block: 'nearest', inline: 'nearest' });
});
});
function cancelSearch() {
searchController?.abort();
searchSeq++;
isSearching = false;
}
// Effective directory the current search runs against (shown in the
// footer); updated by doSearch, including when an exactly-typed
// directory is "entered".
let searchScope = $state(HOME_TILDE);
// Runs a directory listing through the cache, so a repeated query in the
// same directory does not re-walk the tree on the server.
async function searchDirs(
path: string,
include: string,
maxDepth: number,
signal: AbortSignal
): Promise<{ base: string; entries: GlobEntry[]; error?: string }> {
const key = `${path}\u0000${include}\u0000${maxDepth}`;
const cached = searchCache.get(key);
if (cached && Date.now() - cached.at < SEARCH_CACHE_TTL_MS) {
return { base: cached.base, entries: cached.results };
}
const res = await ToolsService.executeToolRaw(
BuiltInTool.FILE_GLOB_SEARCH,
{ path, type: GlobSearchType.DIR, include, max_depth: maxDepth, limit: SEARCH_LIMIT },
signal
);
if (typeof res.error === 'string') return { base: '', entries: [], error: res.error };
const base = typeof res.base === 'string' ? res.base : '';
const entries = Array.isArray(res.entries) ? (res.entries as GlobEntry[]) : [];
searchCache.set(key, { results: entries, base, at: Date.now() });
return { base, entries };
}
async function doSearch(query: string) {
const trimmed = query.trim();
if (!trimmed) {
queryResults = [];
searchError = null;
isSearching = false;
hoveredIndex = -1;
searchScope = homeBase ?? HOME_TILDE;
return;
}
cancelSearch();
const controller = new AbortController();
searchController = controller;
const mySeq = ++searchSeq;
const pathQuery = splitPathQuery(trimmed);
isSearching = true;
try {
// A generous limit is requested because ranking happens
// client-side; only the top 20 are shown.
const searchPath = pathQuery ? pathQuery.parent : (homeBase ?? HOME_TILDE);
const include = pathQuery
? pathQuery.last
? buildCaseInsensitiveGlob(pathQuery.last)
: GLOB_WILDCARD
: buildCaseInsensitiveGlob(trimmed);
const maxDepth = pathQuery ? PATH_NAV_MAX_DEPTH : SEARCH_MAX_DEPTH;
const res = await searchDirs(searchPath, include, maxDepth, controller.signal);
if (mySeq !== searchSeq) return;
if (res.error) {
queryResults = [];
hoveredIndex = -1;
searchError = res.error;
return;
}
const { base, entries } = res;
const ranked = rankEntries(entries, pathQuery?.last ?? trimmed);
let results = ranked.map((e) => joinPath(base, e.path));
searchScope = pathQuery ? pathQuery.parent : (homeBase ?? HOME_TILDE);
// An exactly-typed directory is "entered": list its children too,
// so path navigation doesn't require a trailing slash.
const last = pathQuery?.last;
const exact = last
? ranked.find((e) => lastPathSegment(e.path).toLowerCase() === last.toLowerCase())
: undefined;
if (exact) {
const exactDir = joinPath(base, exact.path);
const childRes = await searchDirs(
exactDir,
GLOB_WILDCARD,
PATH_NAV_MAX_DEPTH,
controller.signal
);
if (mySeq !== searchSeq) return;
if (!childRes.error) {
const children = childRes.entries
.map((e) => joinPath(childRes.base, e.path))
.sort((a, b) => a.localeCompare(b));
results = [...results, ...children];
searchScope = exactDir;
}
}
queryResults = results.slice(0, MAX_RESULTS_SHOWN);
hoveredIndex = queryResults.length > 0 ? 0 : -1;
// new results: scroll the list back to the top (first item is hovered)
if (hoveredIndex === 0) scrollTrigger++;
searchError = null;
} catch (err) {
if (mySeq !== searchSeq) return;
queryResults = [];
hoveredIndex = -1;
if (controller.signal.aborted) return;
searchError = err instanceof Error ? err.message : String(err);
} finally {
if (mySeq === searchSeq) isSearching = false;
}
}
// Single funnel for every local close so the host refocus fires
// regardless of which commit/dismiss path ended the interaction.
function closePicker() {
isOpen = false;
onClose?.();
}
function commit(path: string) {
directory = path;
onChange?.(path);
closePicker();
}
function setDirectory(value: string) {
const trimmed = value.trim();
if (!trimmed) return;
directory = trimmed;
onChange?.(trimmed);
}
// Resolve a folder name picked via the browser-native picker (which exposes
// only the leaf name) to a server-side absolute path. Returns null when the
// server cannot locate a matching directory, so the caller can fail visibly
// instead of committing a bare leaf name that would resolve against the
// server process working directory.
async function resolveNativeName(name: string): Promise<string | null> {
try {
const res = await ToolsService.executeToolRaw(BuiltInTool.FILE_GLOB_SEARCH, {
path: homeBase ?? HOME_TILDE,
type: GlobSearchType.DIR,
include: buildCaseInsensitiveGlob(name),
max_depth: NATIVE_MAX_DEPTH,
limit: NATIVE_LIMIT
});
const base = typeof res.base === 'string' ? res.base : '';
const entries = Array.isArray(res.entries) ? (res.entries as GlobEntry[]) : [];
const match = entries.find(
(e) => lastPathSegment(e.path).toLowerCase() === name.toLowerCase()
);
return match ? joinPath(base, match.path) : null;
} catch {
return null;
}
}
async function browseNative() {
if (disabled || !window.showDirectoryPicker) return;
try {
const handle = await window.showDirectoryPicker();
const path = await resolveNativeName(handle.name);
if (path) {
setDirectory(path);
closePicker();
} else {
// keep the previous cwd and fail visibly instead of committing a
// bare leaf name that would resolve against the server cwd
searchError = `Could not resolve "${handle.name}" to a server path`;
}
} catch (err) {
// user cancelled - silently ignore; other errors are logged
if (err instanceof DOMException && err.name === 'AbortError') return;
console.error('[ChatFormWorkingDirectory] showDirectoryPicker failed:', err);
}
}
function handleSubmit() {
const value = inputValue.trim();
if (!value) {
closePicker();
return;
}
setDirectory(value);
closePicker();
}
function handleKeydown(event: KeyboardEvent) {
if (event.key === KeyboardKey.ENTER) {
event.preventDefault();
// Commit the highlighted result, falling back to the raw input
// only when the query returned no matches.
if (hoveredIndex >= 0 && queryResults[hoveredIndex]) {
commit(queryResults[hoveredIndex]);
} else if (queryResults.length === 0) {
handleSubmit();
}
} else if (event.key === KeyboardKey.ARROW_DOWN) {
if (queryResults.length > 0) {
event.preventDefault();
hoveredIndex = (hoveredIndex + 1) % queryResults.length;
scrollTrigger++;
}
} else if (event.key === KeyboardKey.ARROW_UP) {
if (queryResults.length > 0) {
event.preventDefault();
hoveredIndex = hoveredIndex <= 0 ? queryResults.length - 1 : hoveredIndex - 1;
scrollTrigger++;
}
}
}
function handleInputInput(value: string) {
hoveredIndex = -1;
if (value.trim().length > 0) {
runSearch(value);
}
}
function clearDirectory(event?: MouseEvent) {
// Stop the click from bubbling into the popover trigger and re-opening
// the picker on top of the now-cleared state.
event?.stopPropagation();
event?.preventDefault();
directory = null;
onChange?.(null);
closePicker();
}
// The chip is always visible; the X clears the directory (no-op when
// already empty).
function handleDismiss(event?: MouseEvent) {
event?.stopPropagation();
event?.preventDefault();
if (directory) {
clearDirectory(event);
}
}
function handleOpenChange(open: boolean) {
isOpen = open;
if (open) {
// Seed the search field with the current path so the user can refine it
// (or hit Enter to confirm / clear via the X icon).
inputValue = directory ?? '';
hoveredIndex = -1;
queryResults = [];
searchError = null;
void toolsStore.resolveServerHome();
searchScope = homeBase ?? HOME_TILDE;
if (inputValue.trim()) runSearch(inputValue);
} else {
cancelSearch();
// bits-ui-initiated close (Escape on the content, outside-click,
// trigger toggle) - the only path that bypasses closePicker().
onClose?.();
}
}
// Tooltips only on wider viewports - hover surfaces get in the way on
// touch / narrow layouts. Mirrors the gate used in ActionIcon.
let innerWidth = $state(0);
const showTooltip = $derived(innerWidth > DEFAULT_MOBILE_BREAKPOINT);
</script>
<div
class={[
'justify-self-start flex min-w-0 w-auto items-center gap-1 mt-1.5 py-1 px-2 backdrop-blur-2xl rounded-md',
className,
isOpen && 'w-full'
]}
>
<Popover.Root bind:open={isOpen} onOpenChange={handleOpenChange}>
<Popover.Trigger {disabled} class="flex justify-start">
<ChatFormWorkingDirectoryChip
{directory}
{homeBase}
{disabled}
{showTooltip}
onClear={handleDismiss}
/>
</Popover.Trigger>
<Popover.Content
side="top"
align="start"
sideOffset={4}
class="md:max-w-3xl w-[calc(100vw-1rem)] rounded-xl border-border/50 p-0 shadow-xl md:-translate-2!"
onkeydown={handleKeydown}
onOpenAutoFocus={(event) => event.preventDefault()}
>
<div class="p-2 min-h-28 flex flex-col justify-between">
<SearchInput
bind:ref={searchInputRef}
bind:value={inputValue}
placeholder="Choose working directory"
onInput={handleInputInput}
onClose={closePicker}
class="w-full"
/>
{#if inputValue.trim() && (isSearching || queryResults.length > 0 || searchError)}
<ChatFormWorkingDirectoryResultsList
results={queryResults}
{hoveredIndex}
{isSearching}
error={searchError}
rawQuery={inputValue}
bind:container={listContainer}
onCommit={commit}
onHover={(index) => (hoveredIndex = index)}
/>
{/if}
{#if pickerSupported}
<button
type="button"
class="-mt-1 flex cursor-pointer items-center gap-2 rounded-sm px-2 py-1.5 text-sm outline-hidden select-none hover:bg-accent hover:text-accent-foreground"
onclick={browseNative}
>
<FolderOpen class="size-4 shrink-0 text-muted-foreground" />
<span>Browse</span>
</button>
{/if}
{#if homeBase}
<div class="-mx-2 my-1 h-px bg-border/20" aria-hidden="true"></div>
<span class="px-2 py-2 font-mono text-[10px]">
Searching in:
<span class="truncate text-muted-foreground/70" title={searchScope}
>{abbreviateHome(searchScope, homeBase)}</span
>
</span>
{/if}
</div>
</Popover.Content>
</Popover.Root>
</div>
<svelte:window bind:innerWidth />
@@ -0,0 +1,69 @@
<script lang="ts">
import { Folder, X } from '@lucide/svelte';
import { abbreviateWorkingDir } from '$lib/utils';
import * as Tooltip from '$lib/components/ui/tooltip';
import { ActionIcon } from '$lib/components/app/actions';
interface Props {
directory?: string | null;
homeBase?: string | null;
disabled?: boolean;
showTooltip?: boolean;
onClear?: (event?: MouseEvent) => void;
}
let {
directory = null,
homeBase = null,
disabled = false,
showTooltip = false,
onClear
}: Props = $props();
const displayLabel = $derived(
directory ? abbreviateWorkingDir(directory, homeBase) : 'Select working directory'
);
// Full path surface: hover the abbreviated label to recall the exact directory.
const displayLabelTitle = $derived(directory ?? '');
</script>
<span
class="text-muted-foreground inline-flex items-center gap-1 text-xs group"
class:text-foreground={directory}
>
<div class="flex min-w-0 items-center gap-1 cursor-pointer">
<Folder class="w-3.5 h-3.5" />
{#if showTooltip && displayLabelTitle}
<Tooltip.Root>
<Tooltip.Trigger>
{#snippet child({ props })}
<span {...props} class="max-w-64 truncate">{displayLabel}</span>
{/snippet}
</Tooltip.Trigger>
<Tooltip.Content>
<p>{displayLabelTitle}</p>
</Tooltip.Content>
</Tooltip.Root>
{:else}
<span class="max-w-64 truncate">{displayLabel}</span>
{/if}
</div>
{#if directory}
<div
class="w-0 overflow-hidden opacity-0 transition-[width,opacity] duration-200 ease-out group-hover:w-auto group-hover:opacity-100"
>
<ActionIcon
icon={X}
tooltip="Reset working directory"
ariaLabel="Reset working directory"
{disabled}
onclick={onClear}
iconSize="h-3 w-3"
stopPropagationOnClick
class="!h-4 !w-4 shrink-0 text-muted-foreground hover:text-foreground"
/>
</div>
{/if}
</span>
@@ -0,0 +1,72 @@
<script lang="ts">
import { Folder } from '@lucide/svelte';
import { fly } from 'svelte/transition';
import { highlightMatch } from '$lib/utils';
import { cn } from '$lib/components/ui/utils';
// Fly-in transition for the results list.
const FLY_Y_PX = -4;
const FLY_DURATION_MS = 100;
interface Props {
results: string[];
hoveredIndex: number;
isSearching: boolean;
error: string | null;
rawQuery: string;
container?: HTMLDivElement | null;
onCommit?: (path: string) => void;
onHover?: (index: number) => void;
}
let {
results,
hoveredIndex,
isSearching,
error,
rawQuery,
container = $bindable(null),
onCommit,
onHover
}: Props = $props();
</script>
<div
bind:this={container}
class="max-h-48 overflow-y-auto py-2"
transition:fly={{ y: FLY_Y_PX, duration: FLY_DURATION_MS }}
>
{#if isSearching && results.length === 0}
<div class="px-2 py-1.5 text-sm text-muted-foreground">Searching...</div>
{:else if error}
<div class="px-2 py-1.5 text-sm text-destructive">{error}</div>
{:else if results.length === 0}
<div class="px-2 py-1.5 text-sm text-muted-foreground">No matching folders</div>
{:else}
{#each results as path, index (path)}
<button
type="button"
data-result-index={index}
data-highlighted={index === hoveredIndex ? '' : undefined}
class={cn(
'relative flex w-full cursor-pointer items-center gap-2 rounded-sm px-2 py-1.5 text-sm outline-hidden select-none data-highlighted:bg-accent data-highlighted:text-accent-foreground'
)}
onclick={() => onCommit?.(path)}
onmouseenter={() => onHover?.(index)}
>
<Folder class="size-4 shrink-0 text-muted-foreground" />
<span class="min-w-0 flex-1 truncate font-mono text-left">
{#each highlightMatch(path, rawQuery.trim()) as seg, segIndex (segIndex)}
{#if seg.match}
<mark class="rounded bg-yellow-200/60 px-0.5 text-foreground dark:bg-yellow-500/30"
>{seg.text}</mark
>
{:else}
{seg.text}
{/if}
{/each}
</span>
</button>
{/each}
{/if}
</div>
@@ -12,6 +12,7 @@
ChatMessageAssistant,
ChatMessageUser,
ChatMessageSystem,
ChatMessageSynthetic,
ChatMessageMcpPrompt
} from '$lib/components/app/chat';
import { parseFilesToMessageExtras } from '$lib/utils/browser-only';
@@ -56,6 +57,10 @@
: message.content
);
// Synthetic cwd-change messages render with the folder-row UI instead
// of a user bubble. The persisted flag is the single source of truth.
let isSynthetic = $derived(Boolean(message.isSynthetic));
let rawEditContent = $derived.by(() => {
if (message.role !== MessageRole.ASSISTANT) return undefined;
@@ -344,7 +349,7 @@
}
</script>
<div class="chat-message">
<div class="chat-message" class:chat-message--synthetic={isSynthetic}>
{#if message.role === MessageRole.SYSTEM}
<ChatMessageSystem
bind:textareaElement
@@ -375,6 +380,8 @@
{showDeleteDialog}
{siblingInfo}
/>
{:else if isSynthetic}
<ChatMessageSynthetic {message} class={className} />
{:else if message.role === MessageRole.USER}
<ChatMessageUser
class={className}
@@ -422,7 +429,17 @@
* once known; 500px sizes messages that have never been rendered.
*/
.chat-message {
--chat-message-intrinsic-size: 500px;
content-visibility: auto;
contain-intrinsic-size: auto 500px;
contain-intrinsic-size: auto var(--chat-message-intrinsic-size);
}
/*
* Synthetic rows (e.g. the working-directory change) are small, so an
* accurate placeholder keeps the injected row from inflating the
* auto-scroll offset; the 500px default is for ordinary bubbles.
*/
.chat-message--synthetic {
--chat-message-intrinsic-size: 40px;
}
</style>
@@ -0,0 +1,31 @@
<script lang="ts">
import { Folder, FolderX } from '@lucide/svelte';
import { parseCwdMessage } from '$lib/utils';
import type { DatabaseMessage } from '$lib/types';
interface Props {
class?: string;
message: DatabaseMessage;
}
let { class: className = '', message }: Props = $props();
// Parse the synthetic message content in the UI so the row reuses the
// exact same text the model saw, including any guidance suffix.
let info = $derived(parseCwdMessage(message.content));
</script>
{#if info}
<div class="text-muted-foreground flex items-center gap-2 py-1.5 {className}">
{#if info.path === null}
<FolderX class="text-muted-foreground/60 h-3.5 w-3.5 shrink-0" />
<span class="text-foreground/80 text-sm font-medium">Working directory cleared</span>
{:else}
<Folder class="text-muted-foreground/60 h-3.5 w-3.5 shrink-0" />
<span class="text-foreground/80 text-sm font-medium">Set working directory to&nbsp;</span>
<span class="font-mono text-foreground/90 text-sm break-all" title={info.path}>
{info.display}
</span>
{/if}
</div>
{/if}
@@ -0,0 +1,23 @@
<script lang="ts">
import { parseCwdMessage } from '$lib/utils';
import type { DatabaseMessage } from '$lib/types';
import ChatMessageCwdChange from './ChatMessageCwdChange.svelte';
interface Props {
class?: string;
message: DatabaseMessage;
}
let { class: className = '', message }: Props = $props();
// Synthetic messages render a dedicated UI, never a user bubble. The only
// kind today is the working-directory change; parse the content so the
// row reuses the exact synthetic text (and future kinds slot in here).
let isCwdChange = $derived(parseCwdMessage(message.content) !== null);
</script>
{#if isCwdChange}
<ChatMessageCwdChange {message} class={className} />
{:else}
<span class="text-muted-foreground block text-sm {className}">{message.content}</span>
{/if}
@@ -12,6 +12,7 @@
import ChatMessageToolCallBlockExecShellCommand from './ChatMessageToolCallBlockExecShellCommand.svelte';
import ChatMessageToolCallBlockFileGlobSearch from './ChatMessageToolCallBlockFileGlobSearch.svelte';
import ChatMessageToolCallBlockGetDatetime from './ChatMessageToolCallBlockGetDatetime.svelte';
import ChatMessageToolCallBlockGetInfo from './ChatMessageToolCallBlockGetInfo.svelte';
import ChatMessageToolCallBlockGrepSearch from './ChatMessageToolCallBlockGrepSearch.svelte';
import ChatMessageToolCallBlockReadFile from './ChatMessageToolCallBlockReadFile.svelte';
import ChatMessageToolCallBlockRunJavascript from './ChatMessageToolCallBlockRunJavascript.svelte';
@@ -40,6 +41,8 @@
<ChatMessageToolCallBlockSearchResults {section} {open} {isStreaming} {onToggle} />
{:else if section.toolName === BuiltInTool.GET_DATETIME}
<ChatMessageToolCallBlockGetDatetime {section} {isStreaming} />
{:else if section.toolName === BuiltInTool.GET_INFO}
<ChatMessageToolCallBlockGetInfo {section} {isStreaming} />
{:else if section.toolName === BuiltInTool.READ_FILE}
<ChatMessageToolCallBlockReadFile {section} {open} {isStreaming} {onToggle} />
{:else if section.toolName === BuiltInTool.EDIT_FILE}
@@ -1,7 +1,8 @@
<script lang="ts">
import { XCircle } from '@lucide/svelte';
import { MAX_HEIGHT_CODE_BLOCK, RESULT_STAT_SEPARATOR } from '$lib/constants';
import { computeLineDiff, prefixFor, type AgenticSection } from '$lib/utils';
import { computeLineDiff, prefixFor, abbreviateHome, type AgenticSection } from '$lib/utils';
import { toolsStore } from '$lib/stores/tools.svelte';
import { parseEditFileMeta } from './parsers/edit-file';
import ToolCallBlock from './ToolCallBlock.svelte';
@@ -15,6 +16,7 @@
let { section, open, isStreaming, onToggle }: Props = $props();
const editFileMeta = $derived(parseEditFileMeta(section));
const home = $derived(toolsStore.serverHome);
const editDiffs = $derived(
(editFileMeta?.edits ?? []).map((edit) => computeLineDiff(edit.oldText, edit.newText))
);
@@ -23,7 +25,9 @@
<ToolCallBlock {section} {open} {isStreaming} meta={editFileMeta} {onToggle}>
{#snippet titleSnippet()}
<span class="text-muted-foreground">Edit file </span>
<span class="font-mono">{editFileMeta?.filePath}</span>
<span class="font-mono" title={editFileMeta?.filePath}
>{abbreviateHome(editFileMeta?.filePath ?? '', home)}</span
>
{#if editFileMeta?.errorMessage}
<span class="ml-1 text-xs italic text-muted-foreground/70">(failed)</span>
{/if}
@@ -12,6 +12,7 @@
import { config } from '$lib/stores/settings.svelte';
import { TOOL_RUNTIME_SCROLL_AT_BOTTOM_THRESHOLD_PX } from '$lib/constants/auto-scroll';
import {
abbreviateHome,
highlightCode,
isExitCodeSummaryLine,
parseExecShellCommandError,
@@ -21,6 +22,7 @@
type ExecShellExitStatus,
type ToolResultLine
} from '$lib/utils';
import { toolsStore } from '$lib/stores/tools.svelte';
import { parseExecShellCommandMeta } from './parsers/exec-shell-command';
import type { DatabaseMessageExtra } from '$lib/types';
import ToolCallBlock from './ToolCallBlock.svelte';
@@ -75,6 +77,14 @@
execShellMeta ? highlightCode(execShellMeta.command, 'bash') : ''
);
// The working directory the command ran with, persisted per call on the
// tool result message (it travels via the x-tool-cwd header, not the tool
// args). Reading it from the section keeps it accurate even if the
// conversation cwd changes later.
const cwd = $derived(section.toolCwd);
const home = $derived(toolsStore.serverHome);
const wdDisplay = $derived(abbreviateHome(cwd ?? '', home));
const exitBadgeClass = $derived(
execShellExitStatus?.timedOut
? 'exit-badge warning'
@@ -159,6 +169,11 @@
</script>
{#snippet execShellTitle()}
{#if cwd}
<span class="exec-wd" title={cwd}>{wdDisplay}</span>
<span class="exec-prompt">$</span>
{/if}
{#if highlightedCommandHtml}
<span class="font-mono">{@html highlightedCommandHtml}</span>
{:else}
@@ -232,6 +247,23 @@
</ToolCallBlock>
<style>
:root {
--exec-wd-margin: 0.4rem;
}
.exec-wd {
font-family: var(--font-mono);
color: var(--muted-foreground);
margin-right: var(--exec-wd-margin);
}
.exec-prompt {
font-family: var(--font-mono);
color: var(--muted-foreground);
opacity: 0.55;
margin-right: var(--exec-wd-margin);
}
.terminal-output {
overscroll-behavior: contain;
}
@@ -1,6 +1,7 @@
<script lang="ts">
import { XCircle } from '@lucide/svelte';
import { type AgenticSection } from '$lib/utils';
import { abbreviateHome, type AgenticSection } from '$lib/utils';
import { toolsStore } from '$lib/stores/tools.svelte';
import { parseFileGlobSearchMeta } from './parsers/file-glob-search';
import ToolCallBlock from './ToolCallBlock.svelte';
@@ -14,6 +15,7 @@
let { section, open, isStreaming, onToggle }: Props = $props();
const fileGlobMeta = $derived(parseFileGlobSearchMeta(section));
const home = $derived(toolsStore.serverHome);
</script>
<ToolCallBlock {section} {open} {isStreaming} meta={fileGlobMeta} {onToggle}>
@@ -26,7 +28,9 @@
<span class="font-mono">{fileGlobMeta.include}</span>
{/if}
<span class="text-muted-foreground">&nbsp;in&nbsp;</span>
<span class="font-mono">{fileGlobMeta.path}</span>
<span class="font-mono" title={fileGlobMeta.path}
>{abbreviateHome(fileGlobMeta.path, home)}</span
>
{/if}
{/snippet}
@@ -0,0 +1,69 @@
<script lang="ts">
import { Info, Loader2 } from '@lucide/svelte';
import { AgenticSectionType } from '$lib/enums';
import { abbreviateHome, type AgenticSection } from '$lib/utils';
import { toolsStore } from '$lib/stores/tools.svelte';
interface Props {
section: AgenticSection;
isStreaming?: boolean;
}
let { section, isStreaming = false }: Props = $props();
const isPending = $derived(section.type === AgenticSectionType.TOOL_CALL_PENDING);
const isStreamingCall = $derived(section.type === AgenticSectionType.TOOL_CALL_STREAMING);
const showSpinner = $derived(isPending || (isStreamingCall && isStreaming));
type GetInfoMeta = {
os?: string;
cwd?: string;
errorMessage?: string;
};
function parseGetInfoMeta(toolResultString: string | undefined): GetInfoMeta {
if (!toolResultString) return {};
try {
const parsed: unknown = JSON.parse(toolResultString);
if (parsed && typeof parsed === 'object' && !Array.isArray(parsed)) {
const obj = parsed as Record<string, unknown>;
if (typeof obj.error === 'string') return { errorMessage: obj.error };
return {
os: typeof obj.os === 'string' ? obj.os : undefined,
cwd: typeof obj.cwd === 'string' ? obj.cwd : undefined
};
}
} catch {
// not JSON - nothing to show
}
return {};
}
const infoMeta = $derived(parseGetInfoMeta(section.toolResult));
const home = $derived(toolsStore.serverHome);
const cwdDisplay = $derived(abbreviateHome(infoMeta.cwd ?? '', home));
</script>
<div class="text-muted-foreground flex items-center gap-2 py-1.5">
<Info class="text-muted-foreground/60 h-3.5 w-3.5 shrink-0" />
{#if showSpinner}
<span class="text-foreground/80 text-sm font-medium">Runtime info</span>
<Loader2 class="text-muted-foreground/70 h-3 w-3 animate-spin" />
{:else if infoMeta.errorMessage}
<span class="text-foreground/80 text-sm font-medium">Runtime info&nbsp;</span>
<span class="text-red-600 text-xs italic dark:text-red-400">-&nbsp;{infoMeta.errorMessage}</span
>
{:else if infoMeta.os || infoMeta.cwd}
<span class="text-foreground/80 text-sm font-medium">Runtime info&nbsp;</span>
{#if infoMeta.os}
<span class="font-mono text-foreground/90 text-sm">{infoMeta.os}</span>
{/if}
{#if infoMeta.cwd}
<span class="font-mono text-foreground/90 text-sm" title={infoMeta.cwd}>{cwdDisplay}</span>
{/if}
{:else}
<span class="text-foreground/80 text-sm font-medium">Runtime info</span>
{/if}
</div>
@@ -1,6 +1,7 @@
<script lang="ts">
import { XCircle } from '@lucide/svelte';
import { type AgenticSection } from '$lib/utils';
import { abbreviateHome, type AgenticSection } from '$lib/utils';
import { toolsStore } from '$lib/stores/tools.svelte';
import { parseGrepSearchMeta } from './parsers/grep-search';
import ToolCallBlock from './ToolCallBlock.svelte';
@@ -14,6 +15,7 @@
let { section, open, isStreaming, onToggle }: Props = $props();
const grepMeta = $derived(parseGrepSearchMeta(section));
const home = $derived(toolsStore.serverHome);
</script>
<ToolCallBlock {section} {open} {isStreaming} meta={grepMeta} {onToggle}>
@@ -22,7 +24,7 @@
<span class="text-muted-foreground">Search for&nbsp;</span>
<span class="font-mono">{grepMeta.pattern}</span>
<span class="text-muted-foreground">&nbsp;in&nbsp;</span>
<span class="font-mono">{grepMeta.path}</span>
<span class="font-mono" title={grepMeta.path}>{abbreviateHome(grepMeta.path, home)}</span>
{/if}
{/snippet}
@@ -2,7 +2,8 @@
import { XCircle } from '@lucide/svelte';
import { SyntaxHighlightedCode } from '$lib/components/app';
import { MAX_HEIGHT_CODE_BLOCK, RESULT_STAT_SEPARATOR } from '$lib/constants';
import { type AgenticSection } from '$lib/utils';
import { abbreviateHome, type AgenticSection } from '$lib/utils';
import { toolsStore } from '$lib/stores/tools.svelte';
import { parseWriteFileMeta } from './parsers/write-file';
import ToolCallBlock from './ToolCallBlock.svelte';
@@ -16,12 +17,15 @@
let { section, open, isStreaming, onToggle }: Props = $props();
const writeFileMeta = $derived(parseWriteFileMeta(section));
const home = $derived(toolsStore.serverHome);
</script>
<ToolCallBlock {section} {open} {isStreaming} meta={writeFileMeta} {onToggle}>
{#snippet titleSnippet()}
<span class="text-muted-foreground">Write file </span>
<span class="font-mono">{writeFileMeta?.filePath}</span>
<span class="font-mono" title={writeFileMeta?.filePath}
>{abbreviateHome(writeFileMeta?.filePath ?? '', home)}</span
>
{#if writeFileMeta?.errorMessage}
<span class="ml-1 text-xs italic text-muted-foreground/70">(failed)</span>
{/if}
@@ -272,6 +272,16 @@ export { default as ChatFormMcpResourcesList } from './ChatForm/ChatFormMcpResou
*/
export { default as ChatFormTextarea } from './ChatForm/ChatFormTextarea.svelte';
/**
* Working directory selector for agent mode. Renders a chip below the chat
* form; clicking it opens a popover with a directory picker backed by the
* server's `file_glob_search` built-in tool (POST /tools). The picked
* directory is exposed via `bind:directory`; changing it records a
* synthetic "Set working directory to ..." user message into chat history
* and is enforced on tool calls via the `x-tool-cwd` request header.
*/
export { default as ChatFormWorkingDirectory } from './ChatForm/ChatFormWorkingDirectory.svelte';
/**
* **ChatFormPickerMcpPrompts** - MCP prompt selection interface
*
@@ -557,6 +567,22 @@ export { default as ChatMessageStatisticsBadge } from './ChatMessages/ChatMessag
*/
export { default as ChatMessageMcpPrompt } from './ChatMessages/ChatMessage/ChatMessageMcpPrompt/ChatMessageMcpPrompt.svelte';
/**
* Synthetic working-directory-change message. Rendered in place of a user
* bubble when the message content parses as a cwd message (see
* parseCwdMessage); shows the new cwd with the same folder-row treatment
* the tool-call UI used.
*/
export { default as ChatMessageCwdChange } from './ChatMessages/ChatMessage/ChatMessageCwdChange.svelte';
/**
* Generic wrapper for UI-generated (synthetic) messages. Routes the
* working-directory change to ChatMessageCwdChange and renders a muted
* fallback for any other synthetic text, so no synthetic message ever
* surfaces as a user bubble.
*/
export { default as ChatMessageSynthetic } from './ChatMessages/ChatMessage/ChatMessageSynthetic.svelte';
/**
* Formatted content display for MCP prompt messages. Renders the full prompt
* content with arguments in a readable format. Used within ChatMessageMcpPrompt
@@ -15,6 +15,7 @@ import {
FilePlus,
FileSearch,
FileText,
Info,
SearchCode,
Terminal
} from '@lucide/svelte';
@@ -41,6 +42,7 @@ export const BUILTIN_TOOL_UI: Readonly<Record<BuiltInTool, BuiltinToolUiEntry>>
source: ToolSource.BUILTIN
},
[BuiltInTool.GET_DATETIME]: { icon: Clock, label: 'Current time', source: ToolSource.BUILTIN },
[BuiltInTool.GET_INFO]: { icon: Info, label: 'Runtime info', source: ToolSource.BUILTIN },
[BuiltInTool.EXEC_SHELL_COMMAND]: {
icon: Terminal,
label: 'Run command',
+2
View File
@@ -40,6 +40,7 @@ export * from './mcp';
export * from './mcp-form';
export * from './mcp-resource';
export * from './message-export';
export * from './path-display';
export * from './model-id';
export * from './model-loading';
export * from './sse';
@@ -60,3 +61,4 @@ export * from './ui';
export * from './uri-template';
export * from './url';
export * from './viewport';
export * from './working-directory';
@@ -0,0 +1,22 @@
/**
* Constants for synthetic working-directory messages.
*
* The synthetic cwd-change message is text the UI renders as a folder row
* and the model sees as a turn reminder. The prefix and cleared marker keep
* the human-readable wording; the file-link regexes parse the
* `[file:///abs/path](display)` payload back out on the UI side.
*/
import { UrlProtocol } from '$lib/enums';
export const CWD_CHANGED_PREFIX = 'Set working directory to ';
export const CWD_CLEARED_TEXT = 'Working directory cleared';
export const HOME_TILDE = '~';
export const HOME_TILDE_PREFIX = '~/'; // tilde plus path separator
/** Scheme prefix of the file link embedded in a synthetic cwd message. */
export const FILE_URI_PREFIX = `${UrlProtocol.FILE}//`;
/** Matches the leading `[file:///abs/path](display)` link; not anchored to the end so trailing guidance may follow. */
export const CWD_LINK_REGEX = /^\[file:\/\/([\s\S]*?)\]\(([\s\S]*?)\)/;
+3
View File
@@ -1,5 +1,8 @@
import { ToolSource } from '$lib/enums/tools.enums';
/** HTTP header carrying the working directory a tool call runs in. The server resolves relative paths against it; the model cannot override it. */
export const X_TOOL_CWD_HEADER = 'x-tool-cwd';
export const TOOL_GROUP_LABELS = {
[ToolSource.BUILTIN]: 'Built-in',
[ToolSource.CUSTOM]: 'JSON Schema',
@@ -0,0 +1,40 @@
/**
* Constants for the working-directory picker's glob search.
*
* The picker glob-matches home-relative names client-side. Character classes
* are built case-insensitively and the reserved glob metacharacters are
* escaped (passed through literally) so a query never changes matching.
*/
export const GLOB_WILDCARD = '*';
/** Character that starts and ends a glob character-class fragment. */
export const GLOB_RANGE_OPEN = '[';
export const GLOB_RANGE_CLOSE = ']';
/** Query characters that carry glob meaning and are passed through literally. */
export const GLOB_SPECIAL_CHARS = '*?[]';
/** Separator Windows accepts alongside `/`, and a legal POSIX filename character. */
export const WINDOWS_SEPARATOR = '\\';
/** `C:`, the drive part of a Windows absolute path. */
export const DRIVE_PREFIX_REGEX = /^[A-Za-z]:/;
/** `C:` or `C:/`, the root of a Windows drive-absolute path. */
export const DRIVE_ROOT_REGEX = /^[A-Za-z]:\/?/;
/** `//host/share` or `//host/share/`, the root of a UNC path. */
export const UNC_ROOT_REGEX = /^\/\/[^/]+\/[^/]+\/?/;
// Search tuning for the picker's file_glob_search calls.
export const SEARCH_DEBOUNCE_MS = 180;
export const SEARCH_LIMIT = 100;
export const MAX_RESULTS_SHOWN = 20;
// Home-relative globs descend deeper than path navigation, which only
// needs the direct children of the parent.
export const SEARCH_MAX_DEPTH = 6;
export const PATH_NAV_MAX_DEPTH = 1;
// Native folder-picker resolution searches a shallow, bounded window.
export const NATIVE_MAX_DEPTH = 4;
export const NATIVE_LIMIT = 20;
+7 -1
View File
@@ -72,6 +72,12 @@ export { ColorMode, HtmlInputType, McpPromptVariant, TooltipSide, UrlProtocol }
export { KeyboardKey } from './keyboard.enums';
export { BuiltInTool, ToolSource, ToolPermissionDecision, ToolResponseField } from './tools.enums';
export {
BuiltInTool,
GlobSearchType,
ToolSource,
ToolPermissionDecision,
ToolResponseField
} from './tools.enums';
export { SplashOrientation } from './splash.enums';
+11
View File
@@ -17,6 +17,16 @@ export enum ToolResponseField {
ERROR = 'error'
}
/**
* Entry types accepted by the `file_glob_search` tool's `type` parameter.
* Mirrors the server-side validation in server-tools.cpp.
*/
export enum GlobSearchType {
FILE = 'file',
DIR = 'dir',
ALL = 'all'
}
/**
* Wire-format identifiers for built-in and frontend tools. The string
* value matches what the model emits in tool call names, so comparing
@@ -30,6 +40,7 @@ export enum BuiltInTool {
EDIT_FILE = 'edit_file',
WRITE_FILE = 'write_file',
GET_DATETIME = 'get_datetime',
GET_INFO = 'get_info',
FILE_GLOB_SEARCH = 'file_glob_search',
GREP_SEARCH = 'grep_search',
EXEC_SHELL_COMMAND = 'exec_shell_command',
+1
View File
@@ -24,6 +24,7 @@ export enum McpPromptVariant {
*/
export enum UrlProtocol {
DATA = 'data:',
FILE = 'file:',
HTTP = 'http:',
HTTPS = 'https:',
WEBSOCKET = 'ws:',
@@ -674,7 +674,8 @@ export class DatabaseService {
serverId: o.serverId,
enabled: o.enabled
}))
: undefined
: undefined,
cwd: sourceConv.cwd
};
await db[IDXDB_TABLES.conversations].add(newConv);
@@ -30,7 +30,7 @@ describe('ParameterSyncService', () => {
dry_multiplier: 0.0,
dry_base: 1.75,
dry_allowed_length: 2,
dry_penalty_last_n: -1,
dry_penalty_last_n: 64,
mirostat: 0,
mirostat_tau: 5.0,
mirostat_eta: 0.1,
@@ -96,7 +96,7 @@ describe('ParameterSyncService', () => {
dry_multiplier: 0.0,
dry_base: 1.75,
dry_allowed_length: 2,
dry_penalty_last_n: -1,
dry_penalty_last_n: 64,
mirostat: 0,
mirostat_tau: 5.0,
mirostat_eta: 0.1,
+30 -3
View File
@@ -2,7 +2,7 @@ import { base } from '$app/paths';
import { getJsonHeaders } from '$lib/utils/api-headers';
import { parseSseJsonStream, type SseJsonEvent } from '$lib/utils/sse';
import { apiFetch } from '$lib/utils';
import { API_TOOLS } from '$lib/constants';
import { API_TOOLS, X_TOOL_CWD_HEADER } from '$lib/constants';
import { ToolResponseField } from '$lib/enums';
import type { ToolExecutionResult, ServerBuiltinToolInfo } from '$lib/types';
@@ -18,15 +18,21 @@ export class ToolsService {
/**
* Execute a built-in tool on the server.
*
* @param cwd - Working directory for the tool call, sent as the
* x-tool-cwd request header. The server resolves relative paths
* against it; the model cannot override it.
*/
static async executeTool(
toolName: string,
params: Record<string, unknown>,
signal?: AbortSignal
signal?: AbortSignal,
cwd?: string
): Promise<ToolExecutionResult> {
const result = await apiFetch<Record<string, unknown>>(API_TOOLS.EXECUTE, {
method: 'POST',
body: JSON.stringify({ tool: toolName, params }),
headers: cwd ? { [X_TOOL_CWD_HEADER]: cwd } : undefined,
signal
});
@@ -41,6 +47,25 @@ export class ToolsService {
return { content: JSON.stringify(result), isError: false };
}
/**
* Execute a built-in tool and return the raw JSON response. Unlike
* executeTool, this preserves structured fields (e.g. file_glob_search's
* `entries` and `base`) that the flattened ToolExecutionResult drops.
*/
static async executeToolRaw(
toolName: string,
params: Record<string, unknown>,
signal?: AbortSignal,
cwd?: string
): Promise<Record<string, unknown>> {
return apiFetch<Record<string, unknown>>(API_TOOLS.EXECUTE, {
method: 'POST',
body: JSON.stringify({ tool: toolName, params }),
headers: cwd ? { [X_TOOL_CWD_HEADER]: cwd } : undefined,
signal
});
}
/**
* Stream a built-in tool's output chunks from the server. The server
* `POST /tools` endpoint with `{stream: true}` emits `data: {"chunk": "..."}`
@@ -59,9 +84,11 @@ export class ToolsService {
static async *streamTool(
toolName: string,
params: Record<string, unknown>,
signal?: AbortSignal
signal?: AbortSignal,
cwd?: string
): AsyncGenerator<ToolStreamEvent> {
const headers = getJsonHeaders();
if (cwd) headers[X_TOOL_CWD_HEADER] = cwd;
const response = await fetch(`${base}${API_TOOLS.EXECUTE}`, {
method: 'POST',
headers,
+6 -3
View File
@@ -22,6 +22,7 @@
import { ChatService } from '$lib/services';
import { config } from '$lib/stores/settings.svelte';
import { conversationsStore } from '$lib/stores/conversations.svelte';
import { mcpStore } from '$lib/stores/mcp.svelte';
import { modelsStore } from '$lib/stores/models.svelte';
import { toolsStore } from '$lib/stores/tools.svelte';
@@ -812,11 +813,12 @@ class AgenticStore {
updateToolResultMessage
) {
const args = this.parseToolArguments(toolCall.function.arguments);
const msg = await createToolResultMessage(toolCall.id, '');
const cwd = conversationsStore.activeConversation?.cwd;
const msg = await createToolResultMessage(toolCall.id, '', undefined, cwd);
createdToolResultMessageId = msg.id;
let accumulated = '';
for await (const ev of ToolsService.streamTool(toolName, args, signal)) {
for await (const ev of ToolsService.streamTool(toolName, args, signal, cwd)) {
if (ev.chunk !== null) {
accumulated += ev.chunk;
await updateToolResultMessage(msg.id, accumulated);
@@ -835,7 +837,8 @@ class AgenticStore {
result = accumulated;
} else if (toolSource === ToolSource.BUILTIN) {
const args = this.parseToolArguments(toolCall.function.arguments);
const executionResult = await ToolsService.executeTool(toolName, args, signal);
const cwd = conversationsStore.activeConversation?.cwd;
const executionResult = await ToolsService.executeTool(toolName, args, signal, cwd);
result = executionResult.content;
+58 -6
View File
@@ -35,9 +35,12 @@ import {
findDescendantMessages,
findLeafNode,
findMessageById,
formatCwdMessage,
isAbortError,
generateConversationTitle
generateConversationTitle,
CWD_CLEARED_TEXT
} from '$lib/utils';
import { toolsStore } from '$lib/stores/tools.svelte';
import { classifyContinueIntent } from '$lib/utils/agentic';
import {
MAX_INACTIVE_CONVERSATION_STATES,
@@ -870,7 +873,8 @@ class ChatStore {
content: string,
type: MessageType = MessageType.TEXT,
parent: string = '-1',
extras?: DatabaseMessageExtra[]
extras?: DatabaseMessageExtra[],
isSynthetic?: boolean
): Promise<DatabaseMessage> {
const activeConv = conversationsStore.activeConversation;
if (!activeConv) throw new Error('No active conversation');
@@ -893,7 +897,8 @@ class ChatStore {
timestamp: Date.now(),
toolCalls: '',
children: [],
extra: extras
extra: extras,
isSynthetic
},
parentId
);
@@ -903,6 +908,33 @@ class ChatStore {
return message;
}
/**
* Record a working-directory change into chat history as a synthetic
* user message, so the model sees it on its next turn (the client
* sends the cwd itself via the x-tool-cwd header on tool calls).
* A plain user message is used because some chat templates reject
* tool messages without a preceding tool call.
*/
async recordCwdChange(cwd: string | null): Promise<void> {
const content = cwd
? formatCwdMessage(cwd, await toolsStore.resolveServerHome())
: CWD_CLEARED_TEXT;
// Reuse the trailing cwd row when it is already the last message, so
// repeated picks update it in place instead of stacking another row.
const last = conversationsStore.activeMessages[conversationsStore.activeMessages.length - 1];
if (last && last.role === MessageRole.USER && last.isSynthetic === true) {
await DatabaseService.updateMessage(last.id, { content, isSynthetic: true });
conversationsStore.updateMessageAtIndex(conversationsStore.activeMessages.length - 1, {
content,
isSynthetic: true
});
return;
}
await this.addMessage(MessageRole.USER, content, MessageType.TEXT, '-1', undefined, true);
}
async addSystemPrompt(): Promise<void> {
let activeConv = conversationsStore.activeConversation;
if (!activeConv) {
@@ -1055,6 +1087,7 @@ class ChatStore {
const rootId = await DatabaseService.createRootMessage(currentConv.id);
const currentConfig = config();
const systemPrompt = currentConfig.systemMessage?.toString().trim();
let sysOrRootId = rootId;
if (systemPrompt) {
const systemMessage = await DatabaseService.createSystemMessage(
currentConv.id,
@@ -1062,8 +1095,25 @@ class ChatStore {
rootId
);
conversationsStore.addMessageToActive(systemMessage);
parentIdForUserMessage = systemMessage.id;
} else parentIdForUserMessage = rootId;
sysOrRootId = systemMessage.id;
}
// Reflect a working directory picked on the new-chat screen into
// chat history before the first user message, so the model sees
// it on its first turn. createConversation() has already threaded
// the pending pick onto the conversation.
if (currentConv.cwd) {
const cwdMessage = await this.addMessage(
MessageRole.USER,
formatCwdMessage(currentConv.cwd, await toolsStore.resolveServerHome()),
MessageType.TEXT,
sysOrRootId,
undefined,
true
);
parentIdForUserMessage = cwdMessage.id;
} else {
parentIdForUserMessage = sysOrRootId;
}
}
const userMessage = await this.addMessage(
MessageRole.USER,
@@ -1282,7 +1332,8 @@ class ChatStore {
createToolResultMessage: async (
toolCallId: string,
content: string,
extras?: DatabaseMessageExtra[]
extras?: DatabaseMessageExtra[],
toolCwd?: string
) => {
const msg = await DatabaseService.createMessageBranch(
{
@@ -1291,6 +1342,7 @@ class ChatStore {
role: MessageRole.TOOL,
content,
toolCallId,
toolCwd,
timestamp: Date.now(),
toolCalls: '',
children: [],
@@ -86,6 +86,15 @@ class ConversationsStore {
/** Global (non-conversation-specific) reasoning effort default */
pendingReasoningEffort = $state<ReasoningEffort>(ConversationsStore.loadReasoningEffortDefault());
/**
* Working directory picked on the empty new-chat screen, before any
* conversation exists. Consumed by `chatStore.sendMessage()`, which
* records it into chat history as a synthetic message on first send.
* Cleared by `loadConversation` and `clearActiveConversation` so a
* stale pick can't bleed onto an unrelated chat.
*/
pendingCwd = $state<string | null>(null);
/** Load reasoning effort default from localStorage, DEFAULT defers to the server */
private static loadReasoningEffortDefault(): ReasoningEffort {
if (typeof globalThis.localStorage === 'undefined') return ReasoningEffort.DEFAULT;
@@ -250,9 +259,13 @@ class ConversationsStore {
// No MCP override list is seeded: getAllMcpServerOverrides resolves
// servers without a per-conversation override to `mcpServers[i].enabled`,
// and only explicit toggles are stored on the conversation.
// Working directory picked on the new-chat screen gets threaded in
// here too, then cleared so it doesn't bleed onto subsequent new chats.
const conversation = await DatabaseService.createConversation(conversationName, {
reasoningEffort: this.pendingReasoningEffort
reasoningEffort: this.pendingReasoningEffort,
cwd: this.pendingCwd ?? undefined
});
this.pendingCwd = null;
this.conversations = [conversation, ...this.conversations];
this.activeConversation = conversation;
@@ -276,6 +289,10 @@ class ConversationsStore {
return false;
}
// Drop any cwd the user drafted on the empty new-chat screen -
// it doesn't belong to this conversation.
this.pendingCwd = null;
this.activeConversation = conversation;
if (conversation.currNode) {
@@ -306,6 +323,7 @@ class ConversationsStore {
this.activeMessages = [];
// reload defaults so new chats inherit persisted state
this.pendingReasoningEffort = ConversationsStore.loadReasoningEffortDefault();
this.pendingCwd = null;
}
/**
@@ -855,6 +873,42 @@ class ConversationsStore {
}
}
/**
* Sets the working directory for the active conversation. Pass `null` or
* an empty string to clear it, which restores the picker's empty state.
*
* On the empty new-chat screen (no active conversation yet), the value
* is buffered into `pendingCwd` so the user can pick before
* sending the first message; `createConversation()` consumes it.
*
* @param value - Absolute server-side path to the working directory, or null to clear
*/
async setCwd(value: string | null): Promise<void> {
const trimmed = value?.trim() || undefined;
// No chat yet - buffer for the first chat the user creates.
if (!this.activeConversation) {
this.pendingCwd = trimmed ?? null;
return;
}
this.activeConversation = {
...this.activeConversation,
cwd: trimmed
};
await DatabaseService.updateConversation(this.activeConversation.id, {
cwd: trimmed
});
const convIndex = this.conversations.findIndex((c) => c.id === this.activeConversation!.id);
if (convIndex !== -1) {
this.conversations[convIndex].cwd = trimmed;
this.conversations = [...this.conversations];
}
this.pendingCwd = null;
}
/**
* Forks a conversation at a specific message, creating a new conversation
* containing messages from root up to the target message, then navigates to it.
@@ -1169,6 +1223,7 @@ if (browser) {
export const conversations = () => conversationsStore.conversations;
export const activeConversation = () => conversationsStore.activeConversation;
export const activeMessages = () => conversationsStore.activeMessages;
export const pendingCwd = () => conversationsStore.pendingCwd;
export const isConversationsInitialized = () => conversationsStore.isInitialized;
/**
+37 -1
View File
@@ -1,11 +1,19 @@
import type { OpenAIToolDefinition, ToolEntry, ToolGroup } from '$lib/types';
import { ToolsService } from '$lib/services/tools.service';
import { mcpStore } from '$lib/stores/mcp.svelte';
import { HealthCheckStatus, JsonSchemaType, ToolCallType, ToolSource } from '$lib/enums';
import {
BuiltInTool,
GlobSearchType,
HealthCheckStatus,
JsonSchemaType,
ToolCallType,
ToolSource
} from '$lib/enums';
import { config } from '$lib/stores/settings.svelte';
import {
DISABLED_TOOL_KEYS_LOCALSTORAGE_KEY,
buildSandboxToolDefinition,
HOME_TILDE,
TOOL_GROUP_LABELS,
TOOL_SERVER_LABELS
} from '$lib/constants';
@@ -20,6 +28,7 @@ class ToolsStore {
private _error = $state<string | null>(null);
private _disabledTools = $state(new SvelteSet<string>());
private _toolsEndpointUnreachable = $state(false);
private _serverHome = $state<string | null | undefined>(undefined);
constructor() {
try {
@@ -138,6 +147,10 @@ class ToolsStore {
return this._builtinTools;
}
get serverHome(): string | null {
return this._serverHome ?? null;
}
get mcpTools(): OpenAIToolDefinition[] {
return this.mcpEntries().map((e) => e.definition);
}
@@ -488,6 +501,29 @@ class ToolsStore {
this._loading = false;
}
}
/**
* Absolute home directory on the server, resolved once per session via
* file_glob_search's `base` field (the server expands `~`). Anchors the
* directory picker's search scope and the `~` abbreviation of cwd
* displays. Returns null when tools are unavailable.
*/
async resolveServerHome(): Promise<string | null> {
if (this._serverHome !== undefined) return this._serverHome;
try {
const res = await ToolsService.executeToolRaw(BuiltInTool.FILE_GLOB_SEARCH, {
path: HOME_TILDE,
type: GlobSearchType.DIR,
max_depth: 1,
limit: 1
});
this._serverHome = typeof res.base === 'string' ? res.base : null;
} catch {
// searches still work via a literal `~`, only `~` abbreviation degrades
this._serverHome = null;
}
return this._serverHome;
}
}
export const toolsStore = new ToolsStore();
+2 -1
View File
@@ -109,7 +109,8 @@ export interface AgenticFlowCallbacks {
createToolResultMessage?: (
toolCallId: string,
content: string,
extras?: DatabaseMessageExtra[]
extras?: DatabaseMessageExtra[],
toolCwd?: string
) => Promise<DatabaseMessage>;
/** Update an already-created tool result message. Used while a streaming
* tool (e.g. exec_shell_command) accumulates output chunks before its
+2 -1
View File
@@ -108,7 +108,8 @@ export interface ChatStreamCallbacks {
createToolResultMessage?: (
toolCallId: string,
content: string,
extras?: DatabaseMessageExtra[]
extras?: DatabaseMessageExtra[],
toolCwd?: string
) => Promise<DatabaseMessage>;
updateToolResultMessage?: (
messageId: string,
+5
View File
@@ -14,6 +14,7 @@ export interface DatabaseConversation {
mcpServerOverrides?: McpServerOverride[];
thinkingEnabled?: boolean;
reasoningEffort?: ReasoningEffort;
cwd?: string;
forkedFromConversationId?: string;
pinned?: boolean;
}
@@ -119,6 +120,10 @@ export interface DatabaseMessage {
completionId?: string;
/** Tool call ID for tool result messages (role: 'tool') */
toolCallId?: string;
/** Working directory the tool call ran with (sent via the x-tool-cwd header), stored per call so the UI can show it accurately even after the conversation cwd changes */
toolCwd?: string;
/** Internal flag marking a UI-generated message (e.g. a cwd change). The row is sent to the model as a "user" turn so chat templates accept it; the flag is only read by the renderer. */
isSynthetic?: boolean;
children: string[];
extra?: DatabaseMessageExtra[];
timings?: ChatMessageTimings;
+4
View File
@@ -38,6 +38,9 @@ export interface AgenticSection {
toolArgs?: string;
toolResult?: string;
toolResultExtras?: DatabaseMessageExtra[];
/** Working directory the tool call ran with (from the tool result
* message), shown by the exec_shell_command renderer. */
toolCwd?: string;
/** ID of the model-side tool call (matches tool_calls[i].id). Lets
* downstream consumers correlate a section with the agentic loop's
* currently-executing tool, e.g. to drive live-streaming UI state
@@ -116,6 +119,7 @@ function deriveSingleTurnSections(
toolArgs: tc.function?.arguments,
toolResult: resultMsg?.content,
toolResultExtras: resultMsg?.extra,
toolCwd: resultMsg?.toolCwd,
toolCallId: tc.id
});
}
+23
View File
@@ -158,6 +158,29 @@ export { createBase64DataUrl } from './data-url';
// Header utilities
export { parseHeadersToArray, serializeHeaders } from './headers';
// Working-directory display helpers (HOME-style tilde abbreviation)
export {
abbreviateWorkingDir,
abbreviateHome,
lastPathSegment,
formatCwdMessage,
parseCwdMessage,
CWD_CHANGED_PREFIX,
CWD_CLEARED_TEXT,
type CwdMessageInfo
} from './path-display';
// Working-directory picker search helpers
export {
splitPathQuery,
buildCaseInsensitiveGlob,
rankEntries,
joinPath,
highlightMatch,
type GlobEntry,
type PathQuery
} from './working-directory';
// Agentic content utilities (structured section derivation)
export {
deriveAgenticSections,
+93
View File
@@ -0,0 +1,93 @@
import { PATH_SEPARATOR } from '$lib/constants/mcp-resource';
import { TRAILING_SLASHES_REGEX } from '$lib/constants/url';
import {
CWD_CHANGED_PREFIX,
CWD_CLEARED_TEXT,
CWD_LINK_REGEX,
FILE_URI_PREFIX,
HOME_TILDE,
HOME_TILDE_PREFIX
} from '$lib/constants';
/**
* Last non-empty slash-delimited segment of `path`, with trailing
* slashes stripped. Returns the input unchanged when no `/` is present.
*/
export function lastPathSegment(p: string): string {
const trimmed = p.replace(TRAILING_SLASHES_REGEX, '');
const idx = trimmed.lastIndexOf(PATH_SEPARATOR);
return idx === -1 ? trimmed : trimmed.slice(idx + 1);
}
/**
* Abbreviate `path` to `~/...` when it sits under `home`, or to `~` when
* it equals `home`. Falls back to `lastPathSegment(path)` when home is
* unknown or the path is outside it. `~` semantics are reserved for the
* home directory, mirroring how shells render it.
*/
export function abbreviateWorkingDir(
path: string | null | undefined,
home: string | null | undefined
): string {
if (!path) return '';
if (!home) return lastPathSegment(path);
if (path === home) return HOME_TILDE;
if (path.startsWith(home + PATH_SEPARATOR))
return HOME_TILDE_PREFIX + path.slice(home.length + 1);
return lastPathSegment(path);
}
/**
* Replace a leading `home` prefix in `path` with `~`. Unlike
* abbreviateWorkingDir, paths outside `home` (or an unknown home) are
* returned unchanged - used for tool-call path displays where the full
* path matters.
*/
export function abbreviateHome(path: string, home: string | null | undefined): string {
if (!home) return path;
if (path === home) return HOME_TILDE;
if (path.startsWith(home + PATH_SEPARATOR))
return HOME_TILDE_PREFIX + path.slice(home.length + 1);
return path;
}
export { CWD_CHANGED_PREFIX, CWD_CLEARED_TEXT } from '$lib/constants';
export interface CwdMessageInfo {
// absolute server-side path, null when the cwd was cleared
path: string | null;
// display form shown in the UI (e.g. ~/Documents)
display: string;
}
/**
* Format a synthetic cwd-change message. The text mirrors what the UI
* renders for it; the path travels as `[file:///abs/path](display)` so
* both the absolute and the short form are visible to the model and
* parseable back by the UI.
*/
export function formatCwdMessage(cwd: string, home: string | null): string {
const display = abbreviateWorkingDir(cwd, home);
return `${CWD_CHANGED_PREFIX}[${FILE_URI_PREFIX}${cwd}](${display}).`;
}
/**
* Parse a synthetic cwd message back into its parts. The caller must already
* know the message is synthetic (via the persisted `isSynthetic` flag); this
* only extracts the path from the message text. Returns null when `content`
* is not a cwd message.
*/
export function parseCwdMessage(content: string): CwdMessageInfo | null {
const trimmed = content.trim();
if (trimmed === CWD_CLEARED_TEXT) {
return { path: null, display: '' };
}
if (trimmed.startsWith(CWD_CHANGED_PREFIX)) {
const rest = trimmed.slice(CWD_CHANGED_PREFIX.length);
// not anchored to the end: guidance may follow the link
const link = rest.match(CWD_LINK_REGEX);
if (link) return { path: link[1], display: link[2] };
return { path: rest, display: rest };
}
return null;
}
+151
View File
@@ -0,0 +1,151 @@
/**
* Pure helpers for the working-directory picker search.
*
* The picker is backed by the server's `file_glob_search` built-in tool.
* Queries that start from a root (`/`, `C:\`, `\\host\share`) or from `~`
* navigate the directory tree (search the parent for the last segment);
* anything else glob-matches home-relative entries. Paths are carried with
* `/` separators, which is what the server returns and what Windows accepts.
* These helpers build the glob, normalize results and rank them
* client-side; the component owns the network/state plumbing.
*/
import { PATH_SEPARATOR } from '$lib/constants/mcp-resource';
import { TRAILING_SLASHES_REGEX } from '$lib/constants/url';
import {
DRIVE_PREFIX_REGEX,
DRIVE_ROOT_REGEX,
GLOB_RANGE_CLOSE,
GLOB_RANGE_OPEN,
GLOB_SPECIAL_CHARS,
GLOB_WILDCARD,
HOME_TILDE,
LEADING_SLASHES_REGEX,
UNC_ROOT_REGEX,
WINDOWS_SEPARATOR
} from '$lib/constants';
import { lastPathSegment } from './path-display';
export interface GlobEntry {
path: string;
type: string;
}
export interface PathQuery {
parent: string;
last: string;
}
/**
* Rewrite `\` into `/` when the query carries a Windows root. Elsewhere the
* backslash is left alone: it is a legal filename character on POSIX.
*/
function toPosixSeparators(query: string): string {
if (!DRIVE_PREFIX_REGEX.test(query) && !query.startsWith(WINDOWS_SEPARATOR)) return query;
return query.split(WINDOWS_SEPARATOR).join(PATH_SEPARATOR);
}
/**
* Length of the root prefix of `path`, or 0 when it has none. Covers the
* POSIX root, a Windows drive (`C:/`) and a UNC share (`//host/share/`).
*/
export function rootPrefixLength(path: string): number {
const unc = path.match(UNC_ROOT_REGEX);
if (unc) return unc[0].length;
const drive = path.match(DRIVE_ROOT_REGEX);
if (drive) return drive[0].length;
return path.startsWith(PATH_SEPARATOR) ? PATH_SEPARATOR.length : 0;
}
/** A query starting from a root or from `~` is path navigation, not a home-relative glob. */
export function splitPathQuery(query: string): PathQuery | null {
const normalized = toPosixSeparators(query);
const rootLength = rootPrefixLength(normalized);
if (rootLength === 0 && !normalized.startsWith(HOME_TILDE)) return null;
// a root keeps its trailing separator so it stays absolute on its own
const root =
rootLength > 0
? normalized.slice(0, rootLength).replace(TRAILING_SLASHES_REGEX, '') + PATH_SEPARATOR
: HOME_TILDE;
const rest = normalized
.slice(rootLength > 0 ? rootLength : HOME_TILDE.length)
.replace(LEADING_SLASHES_REGEX, '')
.replace(TRAILING_SLASHES_REGEX, '');
const parentOf = (dirs: string) =>
rootLength > 0 ? root + dirs : HOME_TILDE + PATH_SEPARATOR + dirs;
if (!rest) return { parent: root, last: '' };
const idx = rest.lastIndexOf(PATH_SEPARATOR);
if (idx === -1) return { parent: root, last: rest };
return { parent: parentOf(rest.slice(0, idx)), last: rest.slice(idx + 1) };
}
/** Build a case-insensitive glob that matches `query` anywhere within a name. */
export function buildCaseInsensitiveGlob(query: string): string {
let out = GLOB_WILDCARD;
for (const c of query) {
const lo = c.toLowerCase();
const up = c.toUpperCase();
if (lo !== up) out += GLOB_RANGE_OPEN + lo + up + GLOB_RANGE_CLOSE;
// glob metacharacters are escaped into a literal character class so a
// query like "a*b" matches a literal '*' instead of becoming "ab"
else if (GLOB_SPECIAL_CHARS.includes(c)) out += GLOB_RANGE_OPEN + c + GLOB_RANGE_CLOSE;
else out += c;
}
return out + GLOB_WILDCARD;
}
/** Exact basename first, then prefix, then substring; lower is better. */
const RANK_EXACT = 0;
const RANK_PREFIX = 1;
const RANK_SUBSTRING = 2;
const RANK_OTHER = 3;
function rankScore(path: string, query: string): number {
const name = lastPathSegment(path).toLowerCase();
const q = query.toLowerCase();
if (name === q) return RANK_EXACT;
if (name.startsWith(q)) return RANK_PREFIX;
if (name.includes(q)) return RANK_SUBSTRING;
return RANK_OTHER;
}
/** Sort entries by relevance, then shorter path, then alphabetically. */
export function rankEntries(entries: GlobEntry[], query: string): GlobEntry[] {
return [...entries].sort(
(a, b) =>
rankScore(a.path, query) - rankScore(b.path, query) ||
a.path.length - b.path.length ||
a.path.localeCompare(b.path)
);
}
/** Join a base path and a relative segment, avoiding duplicate slashes. */
export function joinPath(base: string, rel: string): string {
if (!base) return rel;
return base.replace(TRAILING_SLASHES_REGEX, '') + PATH_SEPARATOR + rel;
}
/** Split `text` into alternating segments at each case-insensitive `query` match. */
export function highlightMatch(text: string, query: string): { text: string; match: boolean }[] {
if (!query) return [{ text, match: false }];
const segments: { text: string; match: boolean }[] = [];
const lowerText = text.toLowerCase();
const lowerQuery = query.toLowerCase();
let i = 0;
while (i < text.length) {
const idx = lowerText.indexOf(lowerQuery, i);
if (idx < 0) {
segments.push({ text: text.slice(i), match: false });
break;
}
if (idx > i) segments.push({ text: text.slice(i, idx), match: false });
segments.push({ text: text.slice(idx, idx + query.length), match: true });
i = idx + query.length;
}
return segments;
}
+85
View File
@@ -2,6 +2,7 @@ import { describe, expect, it } from 'vitest';
import { AgenticSectionType, BuiltInTool } from '$lib/enums';
import type { AgenticSection } from '$lib/utils';
import { parseToolArgs } from '$lib/components/app/chat/ChatMessages/ChatMessage/ChatMessageToolCall/parsers/_shared';
import { lastPathSegment, abbreviateHome, formatCwdMessage, parseCwdMessage } from '$lib/utils';
import {
parseWriteFileMeta,
type WriteFileMeta
@@ -27,6 +28,90 @@ function makeSection(
};
}
describe('lastPathSegment', () => {
it('returns the last segment of an absolute path', () => {
expect(lastPathSegment('/Users/me/code/my-project')).toBe('my-project');
});
it('returns the last segment of a tilde-relative path', () => {
expect(lastPathSegment('~/git/llama.brand')).toBe('llama.brand');
});
it('strips trailing slashes', () => {
expect(lastPathSegment('/foo/bar/')).toBe('bar');
});
it('strips multiple trailing slashes', () => {
expect(lastPathSegment('/foo/bar///')).toBe('bar');
});
it('returns the input unchanged when there is no slash', () => {
expect(lastPathSegment('project')).toBe('project');
});
it('returns tilde when only tilde is given', () => {
expect(lastPathSegment('~/')).toBe('~');
});
});
describe('abbreviateHome', () => {
it('abbreviates paths under home with a tilde', () => {
expect(abbreviateHome('/Users/al/Documents/x.txt', '/Users/al')).toBe('~/Documents/x.txt');
});
it('abbreviates home itself to a bare tilde', () => {
expect(abbreviateHome('/Users/al', '/Users/al')).toBe('~');
});
it('returns paths outside home unchanged', () => {
expect(abbreviateHome('/opt/project', '/Users/al')).toBe('/opt/project');
});
it('does not abbreviate a mere prefix match', () => {
expect(abbreviateHome('/Users/alice/x', '/Users/al')).toBe('/Users/alice/x');
});
it('returns the path unchanged when home is unknown', () => {
expect(abbreviateHome('/Users/al/Documents', null)).toBe('/Users/al/Documents');
});
});
describe('formatCwdMessage / parseCwdMessage', () => {
it('formats a cwd change matching the UI text, with a file link', () => {
expect(formatCwdMessage('/Users/al/Documents', '/Users/al')).toBe(
'Set working directory to [file:///Users/al/Documents](~/Documents).'
);
});
it('falls back to the basename display when home is unknown', () => {
expect(formatCwdMessage('/opt/project', null)).toBe(
'Set working directory to [file:///opt/project](project).'
);
});
it('round-trips through the parser', () => {
const info = parseCwdMessage(formatCwdMessage('/Users/al/Documents', '/Users/al'));
expect(info?.path).toBe('/Users/al/Documents');
expect(info?.display).toBe('~/Documents');
});
it('parses a cwd message even when guidance follows the link', () => {
expect(
parseCwdMessage(
'Set working directory to [file:///a/b](~/b). Tool calls run with this as their working directory.'
)
).toEqual({ path: '/a/b', display: '~/b' });
});
it('parses the cleared marker', () => {
expect(parseCwdMessage('Working directory cleared')).toEqual({ path: null, display: '' });
});
it('returns null for non-cwd content', () => {
expect(parseCwdMessage('hello there')).toBeNull();
});
});
describe('parseToolArgs (shared)', () => {
it('returns null when the section has no toolArgs', () => {
const result = parseToolArgs(BuiltInTool.READ_FILE, makeSection({ toolArgs: undefined }));
@@ -0,0 +1,126 @@
import { describe, expect, it } from 'vitest';
import {
splitPathQuery,
buildCaseInsensitiveGlob,
rankEntries,
joinPath,
highlightMatch
} from '$lib/utils';
describe('splitPathQuery', () => {
it('treats a plain query as a home-relative glob (not navigation)', () => {
expect(splitPathQuery('docs')).toBeNull();
});
it('navigates the root for `/`', () => {
expect(splitPathQuery('/')).toEqual({ parent: '/', last: '' });
});
it('navigates home for `~`', () => {
expect(splitPathQuery('~')).toEqual({ parent: '~', last: '' });
});
it('splits an absolute path into parent and last segment', () => {
expect(splitPathQuery('/Users/al/proj')).toEqual({ parent: '/Users/al', last: 'proj' });
});
it('navigates a Windows drive path written with backslashes', () => {
expect(splitPathQuery('C:\\repos\\llama.cpp')).toEqual({
parent: 'C:/repos',
last: 'llama.cpp'
});
});
it('navigates a Windows drive path written with forward slashes', () => {
expect(splitPathQuery('D:/repos')).toEqual({ parent: 'D:/', last: 'repos' });
});
it('treats a bare drive as its root', () => {
expect(splitPathQuery('D:')).toEqual({ parent: 'D:/', last: '' });
expect(splitPathQuery('D:\\')).toEqual({ parent: 'D:/', last: '' });
});
it('navigates a UNC share', () => {
expect(splitPathQuery('\\\\host\\share\\proj')).toEqual({
parent: '//host/share/',
last: 'proj'
});
});
it('keeps a backslash as a POSIX filename character', () => {
expect(splitPathQuery('/tmp/a\\b')).toEqual({ parent: '/tmp', last: 'a\\b' });
});
it('splits a home-relative path into parent and last segment', () => {
expect(splitPathQuery('~/Documents')).toEqual({ parent: '~', last: 'Documents' });
});
it('strips trailing slashes before splitting', () => {
expect(splitPathQuery('/Users/al/')).toEqual({ parent: '/Users', last: 'al' });
});
it('handles a single-segment absolute path', () => {
expect(splitPathQuery('/opt')).toEqual({ parent: '/', last: 'opt' });
});
});
describe('buildCaseInsensitiveGlob', () => {
it('wraps letters in case-insensitive character classes', () => {
expect(buildCaseInsensitiveGlob('ab')).toBe('*[aA][bB]*');
});
it('escapes glob metacharacters into literal fragments', () => {
expect(buildCaseInsensitiveGlob('a*b')).toBe('*[aA][*][bB]*');
});
});
describe('rankEntries', () => {
const entries = [
{ path: '/h/README', type: 'dir' },
{ path: '/h/read', type: 'dir' },
{ path: '/h/readme.txt', type: 'dir' }
];
it('ranks exact basename match first', () => {
const ranked = rankEntries(entries, 'read');
expect(ranked[0].path).toBe('/h/read');
});
it('breaks ties by shorter path, then alphabetically', () => {
const ranked = rankEntries(entries, 'read');
expect(ranked[ranked.length - 1].path).toBe('/h/readme.txt');
});
it('does not mutate the input', () => {
const snapshot = [...entries];
rankEntries(entries, 'read');
expect(entries).toEqual(snapshot);
});
});
describe('joinPath', () => {
it('joins base and relative avoiding a double slash', () => {
expect(joinPath('/home/al/', 'docs')).toBe('/home/al/docs');
});
it('returns the relative path when base is empty', () => {
expect(joinPath('', 'docs')).toBe('docs');
});
});
describe('highlightMatch', () => {
it('returns a single non-matching segment when query is empty', () => {
expect(highlightMatch('abc', '')).toEqual([{ text: 'abc', match: false }]);
});
it('marks every case-insensitive occurrence of the query', () => {
expect(highlightMatch('aXa', 'ax')).toEqual([
{ text: 'aX', match: true },
{ text: 'a', match: false }
]);
});
it('returns non-matching text when the query is absent', () => {
expect(highlightMatch('abc', 'z')).toEqual([{ text: 'abc', match: false }]);
});
});
+1 -2
View File
@@ -76,8 +76,7 @@ export default defineConfig({
extends: './vite.config.ts',
test: {
name: 'ui',
browser: { ...browserBaseConfig, instances: [{ browser: 'chromium', headless: true }] },
setupFiles: ['./.storybook/vitest.setup.ts']
browser: { ...browserBaseConfig, instances: [{ browser: 'chromium', headless: true }] }
},
plugins: [
storybookTest({