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Author SHA1 Message Date
vkandGitHub a298422da7 docs: fix typos in ET.md (#27457) 2026-08-21 12:36:59 +08:00
Xuan-Son NguyenandGitHub 749f688fca ggml: support ggml_rope_set_offset on opencl, sycl, wgpu, hexagon (#27345)
* ggml: support ggml_rope_set_offset on opencl, sycl, wgpu, hexagon

* rm inplace optimization
2026-08-21 00:36:57 +02:00
EveandGitHub 0e1d9185c5 ci: use shell script to check cmake pkg (#27414)
* use regular script to build cmake pkg

* use old grep without perl
2026-08-20 20:01:32 +00:00
Georgi GerganovandGitHub a30273376e metal : clamp K extent in tensor API mat-mat kernel for K not a multiple of 32 (#27450)
The Tensor API mat-mat path of kernel_mul_mm (GGML_METAL_HAS_TENSOR) fed a
static K=32 tile to the matmul2d op on every iteration. On the last, partial
K tile (ne00 % 32 != 0) the src1 slice extends past the K extent of the
tensor, and the op reads those out-of-bounds elements (undefined behavior per
the MSL specification, section 2.22.2). Depending on stale memory contents,
this corrupted the result or produced NaN.

Make the matmul2d op use dynamic_extent for K, and clamp the K extent of both
operand tensor views to the remaining valid K range (min(32, K - loop_k)) per
iteration, so the op reads exactly the valid K range on every iteration
(mirroring the tail handling of the MPP matmul2d examples). On K-aligned
inputs the clamp degenerates to the full 32-wide tile: the only difference
from the static-K op is that the dynamic-K op derives K from the operand
extents and edge-checks the tile against the tensor extents (a handful of
integer ops per iteration).

Add test-backend-ops MUL_MAT cases with K not a multiple of 32 to exercise
the unaligned K path.

Assisted-by: pi:llama.cpp/Qwen3.8-27B
2026-08-20 21:31:29 +03:00
Hongqiang WangandGitHub 6503355df0 opencl: fix q6_K flat mul_mat for Adreno A6x/A7x GPUs with older E031 compilers (#26476)
* opencl: decline KV-convert flash_attn variants on Adreno A7X (compiler SIGSEGV)

The Adreno 740 (A7X) compiler E031.41 crashes inside clBuildProgram when
building the flash_attn programs whose KV path is mixed-type or dequantized:
flash_attn_f32_f16, flash_attn_f32_q8_0, flash_attn_f32_q4_0. It is a driver
crash rather than a compile-error return, so build_program_from_source_ex()
cannot catch it. The uniform f32 and f16 programs build correctly.

Decline the three KV-convert variants on the A7X in supports_op so they never
lazy-compile; those attention layers run on the CPU backend instead. Same
idiom as the existing Intel DK=512 and X1E carve-outs.

test-backend-ops FLASH_ATTN_EXT on the 740: 226 OK / 0 FAIL, previously exit
139. Other parts are unaffected - the gate is dead code there.

* opencl: fix q6_K flat mul_mat on older Adreno E031 compilers, gated

kernel_mul_mv_q6_K_f32_flat produces ~10x-wrong output on the older Adreno
E031 compilers while q4_K and q5_K are correct. Four codegen defects, each
confirmed on-device against the CPU reference:

  1. 64-bit ulong arithmetic is miscompiled, so every weight and scale read
     hit the wrong address - the primary cause, and why q5_K (int offsets)
     was unaffected. The block index is computed in int and widened only
     inside the pointer expression.
  2. The vectorized dequant (int4/float4 bit-ops, convert_*4, dot()) is
     miscompiled; the 6-bit weights are reconstructed and the dot done
     scalar.
  3. vload4 of the f32 activations is miscompiled; replaced by a
     scalar-indexed load.
  4. The accumulation is miscompiled unless a side effect forces the partial
     sums to materialize. A printf under a guard the compiler cannot prove
     false acts as a zero-cost optimizer barrier; its placement is
     load-bearing.

The defect tracks the compiler, not the GPU generation: it reproduces on
E031.38 (Adreno 642L) and E031.41 (Adreno 740) and is fixed by E031.45
(Adreno 619), so the workarounds are gated on the compiler version. Where
they are not needed they cost real throughput - 42.4 -> 35.1 GFLOPS on an
Adreno 840 q6_K GEMV. The explicit compiler-type check is required, not
redundant: newer_than_or_same() is false for every non-E031 compiler, so
negating it alone would enable the workarounds on E17 and DX.

test-backend-ops MUL_MAT is 919/919 on the Adreno 740, 642L, 619, 840 and
850; the 740 and 642L were 909/919 before. The 642L additionally needs the
A6X per-kernel-program support to reach these tests at all.
2026-08-20 10:58:35 -07:00
lhezandGitHub 6b4fa88a6c opencl: fix local size for norm (#27339) 2026-08-20 10:52:07 -07:00
Aleksander GrygierandGitHub 521a64cd01 ui: Stores split refactor (#27240)
* ui: Extract server stream lifecycle from chatStore into ChatStreamManager

Discovery, attach/replay, resume retry and the remote-running snapshot
formed a cohesive cluster inside chatStore. It now lives in
chat-streams.svelte.ts as ChatStreamManager, owned by chatStore, which
keeps the public entry points as delegates so components are
unchanged. chatStore: 2877 -> 2418 lines.

* ui: Extract user interaction gates from agenticStore into AgenticGates

Tool permission requests, turn-limit continue prompts and queued
steering messages are the state the loop waits on between turns. They
had no coupling to session state, so they now live in
agentic-gates.svelte.ts; agenticStore keeps delegates so components
are unchanged. agenticStore: 1196 -> 1073 lines.

* ui: Compose MCP resources under mcpStore.resources

Resource state was a second import scope next to mcpStore. Consumers
now go through mcpStore.resources, so the MCP surface is one store;
mcp-resources.svelte.ts stays a separate file owned by mcpStore.

* ui: Reorganize stores into domain namespaces

* fix: Update stale doc comments

* ui: Consolidate conv running-state into a chat activity ledger

Running-state was split across chatStore.chatLoadingStates (local
pipes), ChatStreamManager.remoteRunningConvs (backend sessions) and
attachingConvs (attach lifecycle), unioned by hand in
getAllLoadingChats and cross-cleaned by setChatLoading calling
streams.clearRemoteRunning - the 'spinner ghosts until tab toggle'
workaround.

chatActivityStore now owns both sets with one transition per event:
markLocal / localEnded (local pipe end also drops the stale remote
hint, no cross-owner call) / applyRemoteSnapshot (diffed). The
sidebar reads chatStore.activity.loadingConvs through the unchanged
getAllLoadingChats entry point.

Consequences:
- isStreamingActive and its five manual writers are gone; isStreaming()
  now reports whether the active conversation has a live streaming
  pipe, which is what all four consumers (assistant row, stop action,
  context gauge, chat screen) actually check
- isLoading/isReasoning become derived from the per-conv maps plus
  the active conversation, dropping the manual resync in
  syncLoadingStateForChat and clearUIState
- attachingConvs and the last-attach coordination disappear from
  ChatStreamManager
- getAllStreamingChats (no consumers) is removed

* ui: Give store collaborators narrow host interfaces

Collaborators took 'host: typeof <store>', i.e. the store's entire
public surface, which is how chatStore's streamChatCompletion,
createAssistantMessage, getApiOptions and setStreamingActive got
widened to public. Replace with per-collaborator interfaces carrying
only the members each one drives:

- ChatStreamHost (chat/streams) - activity, processing, streaming
  states, abort controller, loading/streaming setters
- ChatFlowsHost (chat/flows) - streaming core, message creation,
  per-conv state setters
- McpHealthHost (mcp/health) - connection registry + reconnection
- ModelPropsHost / ModelStatusHost (models) - model rows, feed
  updates; the managers write modalities/status back onto the host's
  rows, so those members stay writable
- ConversationsPreferencesHost (conversations) - the active row and
  the conversation list

The store classes now declare 'implements <Host>' so the contract is
visible at the class level, and the 'import type { <store> }' back
references in the collaborators disappear entirely - the host
contract is local to each collaborator file, and collaborators can
no longer reach around their slice. Members stay public (structural
typing), but the collaborator side is now compiler-enforced.

* test: Chat Activity store test

* refactor: Cleanup

* chore: Remove legacy architecture docs

* ui: Memoize findMessageIndex for the streaming hot path

Streaming looks up the same message index on every chunk, a linear
scan of activeMessages each time. Cache the last lookup and reuse it
after validating the id still sits at the same position (O(1)); any
structural change to the array fails validation and falls back to a
full scan.

* ui: Throttle per-chunk stream state writes to localStorage

saveStreamState ran JSON.stringify + a synchronous localStorage.setItem
on every decoded chunk of the stream. The read loop now goes through a
new saveStreamStateThrottled (one write per conversation per 500ms,
latest value held pending); the public saveStreamState keeps its
immediate-write contract for stream start and pre-fetch, and also
resets the throttle window.

A pending offset is force-flushed at resume boundaries (resumeStream
reads the offset back from localStorage), on visibilitychange->hidden
and on pagehide, so a reload always finds a usable offset. The resume
offset only needs to be roughly current since the server retransmits
from a line boundary and the client discards its partial line.

Adds unit tests for the throttled/flush/clear interplay.

* ui: Compute context gauge timing stats in one pass

currentRead/Fresh/Cache/Output were separate deriveds, each running a
full reverse scan of activeMessages for the last assistant timings,
and cumulative ran its own forward scan plus an agentic filter - 4-5
O(n) passes per chunk while streaming. Replace with a single
summarizeAssistantTimings() pass (last assistant timings, last
agentic llm totals and the cumulative sums) feeding a shared derived
snapshot. Semantics unchanged, including the live-stats overrides and
the agentic llm-totals branch.

* agentic : clear session state when a conversation is deleted

Every conversation that ran an agentic flow left an AgenticSession in the
store forever; clearSession was never called. conversationsStore now
notifies deletion listeners and agenticStore drops the matching sessions,
avoiding a circular import back into conversationsStore.

* chat : extract ChatService.normalizeMessagesForApi

The DB->API message normalization (convert + drop empty system messages)
was duplicated in sendMessage, preEncode and the agentic flow. Extract it
into one shared method and call it from all three.

* sse : share record splitting and data extraction

splitSseRecords and extractSseDataPayload centralize the record-boundary
splitting and data: line extraction used by parseSseJsonStream and the
models status feed. chat.service keeps its own line-based parser for
resume support.

* api : delegate apiFetchWithParams to apiFetch

apiFetchWithParams duplicated apiFetch's headers/fetch/error handling
body-for-body; it only differs in URL construction. Build the URL and
delegate.

* chat flows : dedupe title, timings and cleanup handling

- conversationsStore.applyTitleFromContent centralizes the title-from-first-
  message logic duplicated in 5 places
- ChatProcessingStore.applyStreamTimings centralizes the onTimings handler
  shared by the chat and continue flows
- host.cleanupStreaming centralizes the loading/streaming/processing reset
  repeated across the continue flow's exit paths

* conversations : centralize conversation update mirroring

rename, pin, mcp override, reasoning effort and cwd all repeated the same
write-DB-then-mirror-into-list-and-active dance. A single
applyConversationUpdate(id, updates) on the host collapses all five and
removes the forgot-to-mirror-one-field bug class. Drops the redundant
array reassignment in setCwd (deep  field assignment is reactive).

* mcp : dedupe tool execution, server parsing and tool indexing

- executeTool delegates to executeToolByName (only diff was argument parsing)
- drop the private #parseServerSettings copy; use parseMcpServerSettings
- cache getServers() keyed on the raw config value (hot path)
- indexServerTools() unifies the three identical toolsIndex rebuild loops

Assisted-by: Claude

* mcp : share cursor pagination and tool indexing

- MCPService.paginate() collapses the identical do-while loops in
  listAllResources and listAllResourceTemplates
- promoteHealthCheckToConnection now uses indexServerTools like the other
  connect paths

Assisted-by: Claude

* database : share message parent-child bookkeeping

- addChildToParent() dedups the append-to-children update in createMessageBranch
  and createSystemMessage
- removeChildFromParent() dedups the remove-from-children cleanup in deleteMessage
  and deleteMessageCascading
- bulkAdd the cloned messages when forking a conversation instead of one add
  per message

Assisted-by: Claude

* chore: Lint/format

* fix: `pagehide` event from `window`

* refactor: Api Fetch util

* docs : rewrite architecture sections in README

Update the high-level diagram, routes, hooks, stores, services and data
flow tables to match the current UI structure (mcp/settings/search
routes, agentic/tools/mcp stores, MCPService/ToolsService/SandboxService,
/tools API). Fix stale architectural patterns for per-conversation state
and modality validation.

* chore : add ESLint rule for blank lines between accessors

Enforce a blank line between consecutive class accessors. The core
padding-line-between-statements rule does not cover class members, so a
local rule is needed.

* refactor : reorder store members and unify naming

Order store class members as public fields, private fields, constructor,
getters, public methods, then private methods. Normalize private naming
to the `private` keyword (drop `#` and the `_` prefix where there is no
matching public getter). Rename conversationsStore.init() to
initialize() to match the other stores.

* refactor : prefix lookup methods with get in agentic and chat stores

Unify bare-name lookup methods with the get* prefix used across the
other stores (mcp, models, tools, settings). Renames currentTurn,
totalToolCalls, lastError, streamingToolCall, executingToolCallId,
pendingPermissionRequest, pendingContinueRequest,
pendingSteeringMessageContent, pendingSteeringMessageExtras in the
agentic store and pendingMessageContent, pendingMessageExtras in the
chat store. Updates the two consuming components and a doc comment.

* refactor: Clean up comments in stores' and services' code

* chore : add ESLint rule for class member ordering

Enforce structural order (public fields -> private fields -> constructor ->
getters -> setters -> public methods -> private methods) with alphabetical
sorting within each group via perfectionist/sort-classes. Dependency
detection keeps Svelte $derived fields in a valid dependency order instead
of alphabetizing them, since Svelte rejects forward references.

Assisted-by: Claude

* refactor : reorder class members to match new ESLint rule

Apply the sort-classes rule across stores, services, hooks and utils.
Pure reordering - verified no logic changes by comparing sorted line
multisets before/after. All tests and svelte-check pass.
2026-08-20 19:02:04 +02:00
681c29d36a mtmd: add --mmproj-device argument (#23255)
* feat: add --mmproj-device arg & backwards compatible MTMD_BACKEND_DEVICE env var

* feat: load mmproj device backend immediately, add -mmdev shortflag

* fix: its a pointer now get the name

* clean up

* gen docs

* nits

---------

Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
2026-08-20 18:45:37 +02:00
Tarek DakhranandGitHub 07822bddf8 model : support DSpark for LFM2 models (#27383) 2026-08-20 16:36:57 +02:00
Jeff BolzandGitHub 78ec4c3780 vulkan: FA MMQ should use fp32 for Q quantization calculations (#27413)
Codex found that qd could be a denorm and 1/qd would overflow.
2026-08-20 09:18:11 -05:00
Georgi GerganovandGitHub 63b64a50a3 metal : dequant kv cache only for large batches (#27438) 2026-08-20 17:00:54 +03:00
Oliver SimonsandGitHub bf0040e15f CI: Use LLVM's OpenMP over MSVC_DEBUG_non_redist on Windows (#26678)
* CI: Use LLVM's OpenMP over MSFT_DEBUG_non_redist on Windows

Currently, we ship the non-redist debug version of microsoft's libomp.
This PR changes this to official LLVM's release, also packaging
the license as needed.

* Remove LLVM SHA from job name to increase legibility

* Add temp validations to CI

* Revert "Add temp validations to CI"

This reverts commit eef97c88b5.

* Build OpenMP in CI

* Make OpenMP fetch self-contained in cmake and cache in CI

* Robustify Licens-packaging

1. Ship OpenMP license, not LLVM's.
2. Invalidate cache also on checksum of the license

* Remove stale reference in docs/build.md

* No longer package base license in release

This was scope-creep

* Add explanatory comment to OpenMP license

* Remove arm64 smoke

Forgot this during conflict resolution during rebase of
c54c0e9cf6

* Remove GGML_OPENMP_FETCH_CACHE_DIR as requested by @CISC

* whitespace changes
2026-08-20 15:42:26 +02:00
Xuan-Son NguyenandGitHub 9855ad69d3 server: (router) lazy-load startup_models after main setup (#27424)
* server: (router) lazy-load startup_models after main setup

* only allow is_first_load to populate it

* nits

* nits 2
2026-08-20 15:22:16 +02:00
Aritro BandyopadhyayandGitHub 8a832e4bf3 server : fix --docker-repo being treated as router mode (#27416) 2026-08-20 14:37:14 +02:00
2b5621094e CUDA: adding switch points per HW and quant type to tune the mvq->MMQ decode crossover (#26079)
* CUDA: runtime GGML_CUDA_MMVQ_MAX to tune the mvq->MMQ decode crossover

Add a runtime override of the mul_mat_vec_q -> MMQ batch crossover
(default MMVQ_MAX_BATCH_SIZE). Lowering it routes batches above the
threshold from the CUDA-core vector kernel to the int8 MMQ tensor-core
path, which is faster once quantized decode becomes compute-bound at
B>1 (measured +23-41% at B=8 on RTX 5090 for Q4_K dense, no low-batch loss).

The value is parsed once and clamped to [1, MMVQ_MAX_BATCH_SIZE], since
mul_mat_vec_q asserts ncols_dst <= that; invalid input warns and falls
back to the default. The override is applied consistently in both the
mul_mat_vec_q and MUL_MAT_ID dispatch paths. Default behavior unchanged.

* Added Blackwell specific switch point, to reduce dependence on runtime env var.

* Add per-HW switch point values for DGX Spark and removing runtime env var

* Adding switch points for Ada, tested on RTX 4090

* Modifying DGX Spark numbers based on latest run and adding some comments and small functional changes relating to MoE

* Reverting an unnecessary conditional

* Update ggml/src/ggml-cuda/mmvq.cu

---------

Co-authored-by: praneshgo <227579474+praneshgo@users.noreply.github.com>
Co-authored-by: Oliver Simons <osimons@nvidia.com>
2026-08-20 14:36:21 +02:00
Aldehir RojasandGitHub dc64a1620e common : gracefully fallback on unsupported regex patterns in JSON schema (#26939) 2026-08-20 06:59:03 -05:00
Georgi GerganovandGitHub 70aff25250 metal : dequantize quantized KV to F16 before flash attention (#27390)
* metal: dequantize q8_0 KV to f16 before flash attention

Add a preprocessing pass for GGML_OP_FLASH_ATTN_EXT on the Metal backend:
when the KV cache is quantized (Q8_0 for now), dequantize K and V into a
contiguous F16 scratch buffer and run the existing F16 flash attention
kernels on it, instead of the in-kernel dequantization path.

- new kernel kernel_flash_attn_ext_dequant_to_f16<block_t, QK, deq_t4x4>:
  one thread per quant block (K then V), stride-aware so permuted KV is
  supported; instantiated for Q8_0 (extending to Q4_0/Q4_1/Q5_0/Q5_1 is
  one instantiation + one gate case)
- the gate is type-only: dequantize whenever the KV is quantized,
  regardless of head sizes, GQA ratio or n_kv; the attention kernels
  themselves are untouched
- the F16 copies live in the op's own scratch allocation
  (ggml_metal_op_flash_attn_ext_extra_dequant_f16); the KV pad kernel
  reads the dequantized buffers when the path is active
- the FA pipeline getters gain a use_f16_kv flag selecting the existing
  f16 kernels and contiguous strides
- ref: https://github.com/ggml-org/llama.cpp/pull/25556

Verification (M2 Ultra):
- test-backend-ops test -o FLASH_ATTN_EXT: 4798/4798 pass, including the
  new q8_0 eval cases (decode/prompt, permuted, sinks+ALiBi+softcap,
  kv=113 pad path, kv=16384)
- llama-perplexity on Qwen2.5-0.5B with -ctk q8_0 -ctv q8_0 matches the
  f16 KV reference (PPL 1.0008 vs 1.0008)

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : launch the FA KV dequant kernel separately for K and V

Simplify kernel_flash_attn_ext_dequant_to_f16: it now dequantizes a single
tensor (its own ne/nb and dst) with no is_v branching, and the op dispatches
it twice with the same pipeline - once for K and once for V. The kargs
struct shrinks to a single ne/nb set plus nblocks.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : dequantize q4_0, q4_1, q5_0 and q5_1 KV to f16 before flash attention

The dequant pass now covers all quantized KV types supported by the Metal
flash attention kernels. The dequant kernel, kargs, scratch allocation and
dispatch are type-generic, so each type is one kernel instantiation plus one
gate case.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : skip the redundant V dequant when V is a view of K

In MLA-based models, the V of the FA op is a view of K (the first ne20
elements of each K row); the dequantized V is then a view of the dequantized
K, so skip the second dequant dispatch, do not reserve the V scratch region,
and let the pad and attention kernels read V from the K F16 buffer with K's
strides. The detection follows the CUDA backend:
V->view_src && (V->view_src == K || (V->view_src == K->view_src && V->view_offs == K->view_offs))

Also fix the FA pipeline getters: ns10/ns20 are function constants baked into
the kernels and must be the actual K/V row widths as seen by the kernel. The
dispatch now passes them explicitly (nb11_attn/nb10_attn, nb21_attn/nb20_attn)
instead of the getters assuming contiguous F16 KV (ns20 = dv), which was wrong
when V is read from K with K's row pitch (e.g. 576 vs 512).

New test cases: 576/512 q8_0 (MLA shape, V is a view of K) at kv=113 (KV pad),
nb=1 (vec) and nb=64 (non-vec).

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* test : remove backend-specific wording from test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* pi : avoid backend mentions in test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : rename the FA dequant_f16 identifiers to kv_f16

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* cont : clean-up

* cont : remove TODO
2026-08-20 13:43:59 +03:00
Georgi GerganovandGitHub f20395dae5 Revert "tensor-split meta backend fixes (#26502)" (#27433)
This reverts commit d59d455fd8.
2026-08-20 13:35:15 +03:00
Ruben OrtlamandGitHub 8497981321 ggml: fix backend split scheduler race condition (#26040)
* ggml: fix backend split scheduler race condition

splits without input were running concurrently with other splits, while potentially reusing memory the other split is accessing

* only sync when split has no inputs
2026-08-20 10:42:33 +02:00
Rock ChenandGitHub a3b1effcda convert: fix get block count error for Nemotron 3 Ultra (#27101)
* convert: fix get block count error for Nemotron

Signed-off-by: Rock Chen <rockchen.tw@gmail.com>

* fix this in NemotronHModel.__init__ instead.

This reverts commit ca689cbc87.

---------

Signed-off-by: Rock Chen <rockchen.tw@gmail.com>
2026-08-20 10:35:28 +03:00
d9b6be07d0 ggml-cuda: provide static workspace for cuBLAS handles (#26574)
* provide static workspace for cuBLAS handles

* account for concurrent streams when using GGML_CUDA_GRAPH_OPT

* drop cublas_handle overloads and remove direct cublasSetStream calls

* Update ggml/src/ggml-cuda/common.cuh

---------

Co-authored-by: Oliver Simons <osimons@nvidia.com>
2026-08-20 10:27:51 +03:00
Georgi GerganovandGitHub 929d47a391 graph : create V as a view of K in the k_iswa build_attn (#27392)
build_attn with the llm_graph_input_attn_k_iswa input was using the cached K
tensor itself as V. Create V as a view of K (the first v_cur->ne[0] elements
of each row), like the other K-only build_attn overloads.

The deepseek4 MTP call site now passes the kv tensor as v_cur.

Assisted-by: pi:llama.cpp/Qwen3.8-27B
2026-08-20 10:00:35 +03:00
Georgi GerganovandGitHub f466cfa38f spec : avoid binding reference to null pointer (#27404) 2026-08-20 10:00:16 +03:00
Markus TavenrathandGitHub 2cfdb5fc08 vulkan : add source groups for shaders (#26666) 2026-08-20 09:52:28 +03:00
Hongqiang WangandGitHub 9ee9fc04c1 opencl: make the MoE expert scatter deterministic (#26464) 2026-08-19 20:40:19 -07:00
Max KrasnyanskyandGitHub d59d455fd8 tensor-split meta backend fixes (#26502)
* backend: propagate buffer usage in meta backend

* ggml-meta: make sure to call init_tensor for all new tensors

* meta: remove explicit check for meta backend in ggml_backend_meta_get_split_state

I can't seem to reproduce the original failure in the latest code.
2026-08-19 14:53:27 -07:00
Yiwei ShaoandGitHub 990e3bfee3 hexagon: fix FA HMX queue ordering and pack the rescale D matrices (#27042)
* hexagon: fix FA HMX queue ordering in the pipelined path

* hexagon: double buffer D matrix, store diagonal tile only

* format code

* align the indentation
2026-08-19 14:42:57 -07:00
b062ba735e opencl: port fused ssm_scan kernel (Mamba-2, d_state in {128, 256}) to GPU (#26439)
* opencl: port fused ssm_scan kernel (Mamba-2, d_state in {128, 256})

Fold the fused per-token SSM_SCAN recurrent step from opencl/gdn-qwen36-35b
onto the unified base. Previously SSM_SCAN fell back to CPU here; now scalar-A
Mamba-2 with d_state in {128,256}, all-f32, runs on GPU. Other shapes (incl.
Mamba-1 element-wise A) still fall back. test-backend-ops -o SSM_SCAN passes on
Adreno X2-90. opt-out via GGML_OPENCL_DISABLE_SSM_SCAN=1.

* opencl: cleanup

* opencl: require K == 1

---------

Co-authored-by: Li He <lih@qti.qualcomm.com>
2026-08-19 13:35:17 -07:00
PascalandGitHub cd644c3954 ggml-cpu: gate __fp16 on __ARM_FP16_FORMAT_IEEE (#26860)
* ggml-cpu: gate __fp16 on __ARM_FP16_FORMAT_IEEE

__ARM_NEON only signals NEON availability. The __fp16 type also needs
the IEEE half format, implied on AArch64 but selected with
-mfp16-format=ieee on 32 bit Arm, where the compiler otherwise rejects
the type.

The guard keeps every toolchain that provides the type on the same code
and sends that one configuration to the generic lookup path.

* ggml-cpu: gate the NEON+FMA block on __ARM_FP16_FORMAT_IEEE

Both halves of the F16 section dereference __fp16, so armv7 with
neon-vfpv4 hits the same unknown type error. Without the IEEE
format the configuration now falls back to the scalar path.

Address review from @JonathanC-ARM
2026-08-19 22:03:13 +02:00
188 changed files with 12993 additions and 13225 deletions
+16 -20
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@@ -27,30 +27,26 @@ jobs:
cmake --install build --prefix "$PREFIX" --config Release
export LLAMA_CONFIG="$PREFIX"/lib/cmake/llama/llama-config.cmake
tclsh <<'EOF'
set build(commit) [string trim [exec git rev-parse --short HEAD]]
set build(number) [string trim [exec git rev-list --count HEAD]]
build_commit=$(git rev-parse --short HEAD | xargs)
build_number=$(git rev-list --count HEAD | xargs)
set cmakelists [read [open "CMakeLists.txt" r]]
regexp {set\(LLAMA_VERSION_MAJOR\s+(\d+)\)} $cmakelists -> major
regexp {set\(LLAMA_VERSION_MINOR\s+(\d+)\)} $cmakelists -> minor
regexp {set\(LLAMA_VERSION_PATCH\s+(\d+)\)} $cmakelists -> patch
set build(version) "$major.$minor.$patch"
major=$(grep -oE "set\(LLAMA_VERSION_MAJOR[[:space:]]+[0-9]+" CMakeLists.txt | grep -oE "[0-9]+$")
minor=$(grep -oE "set\(LLAMA_VERSION_MINOR[[:space:]]+[0-9]+" CMakeLists.txt | grep -oE "[0-9]+$")
patch=$(grep -oE "set\(LLAMA_VERSION_PATCH[[:space:]]+[0-9]+" CMakeLists.txt | grep -oE "[0-9]+$")
build_version="$major.$minor.$patch"
set llamaconfig [read [open "$env(LLAMA_CONFIG)" r]]
set checks [list "set\\(LLAMA_VERSION \\s+$build(version)\\)" \
"set\\(LLAMA_BUILD_COMMIT\\s+$build(commit)\\)" \
"set\\(LLAMA_BUILD_NUMBER\\s+$build(number)\\)"]
checks=("set\(LLAMA_VERSION[[:space:]]+$build_version\)"
"set\(LLAMA_BUILD_COMMIT[[:space:]]+$build_commit\)"
"set\(LLAMA_BUILD_NUMBER[[:space:]]+$build_number\)")
puts -nonewline "Checking llama-config.cmake version... "
foreach check $checks {
if {![regexp -expanded -- $check $llamaconfig]} {
puts "\"$check\" failed!"
for check in "${checks[@]}"; do
if ! grep -qE "$check" "$LLAMA_CONFIG"; then
echo "Checking llama-config.cmake version... \"$check\" failed!"
exit 1
}
}
puts "success."
EOF
fi
done
echo "Checking llama-config.cmake version... success."
cd examples/simple-cmake-pkg
cmake -S . -B build -DCMAKE_PREFIX_PATH="$PREFIX"/lib/cmake
+3 -2
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@@ -119,6 +119,7 @@ jobs:
./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
windows:
name: windows / ${{ matrix.build }}
runs-on: windows-2025
env:
@@ -130,13 +131,13 @@ jobs:
include:
- build: 'x64-cpu-static'
arch: 'x64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DBUILD_SHARED_LIBS=OFF'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DGGML_OPENMP_FETCH=ON -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DBUILD_SHARED_LIBS=OFF'
- build: 'x64-openblas'
arch: 'x64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_OPENMP=OFF -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS -DBLAS_INCLUDE_DIRS="$env:RUNNER_TEMP/openblas/include" -DBLAS_LIBRARIES="$env:RUNNER_TEMP/openblas/lib/openblas.lib"'
- build: 'arm64'
arch: 'arm64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DGGML_NATIVE=OFF -DGGML_OPENMP_FETCH=ON -DLLAMA_BUILD_SERVER=ON'
steps:
- name: Clone
+2 -1
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@@ -681,6 +681,7 @@ jobs:
name: llama-bin-win-openvino-${{ env.OPENVINO_VERSION_MAJOR }}-x64.zip
windows-cpu:
name: windows-cpu / ${{ matrix.arch }}
needs: [check-release]
if: ${{ needs.check-release.outputs.should_release == 'true' }}
@@ -728,6 +729,7 @@ jobs:
-DGGML_BACKEND_DL=ON ^
-DGGML_CPU_ALL_VARIANTS=${{ matrix.arch == 'x64' && 'ON' || 'OFF' }} ^
-DGGML_OPENMP=ON ^
-DGGML_OPENMP_FETCH=ON ^
${{ env.CMAKE_ARGS }}
cmake --build build --config Release
@@ -739,7 +741,6 @@ jobs:
- name: Pack artifacts
id: pack_artifacts
run: |
Copy-Item "C:\Program Files\Microsoft Visual Studio\18\Enterprise\VC\Redist\MSVC\14.51.36231\debug_nonredist\${{ matrix.arch }}\Microsoft.VC145.OpenMP.LLVM\libomp140.${{ matrix.arch == 'x64' && 'x86_64' || 'aarch64' }}.dll" .\build\bin\Release\
7z a -snl llama-bin-win-cpu-${{ matrix.arch }}.zip .\build\bin\Release\*
- name: Upload artifacts
+1
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@@ -9,6 +9,7 @@ General:
Coding:
- When in doubt, always refer to the CONTRIBUTING.md file of the project
- In `test-backend-ops.cpp`, do not mention specific backends (e.g. Metal, CUDA) in comments
- When referencing issues or PRs in comments, use the format:
- C/C++ code: `// ref: <url>`
- Other (CMake, etc.): `# ref: <url>`
+1
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@@ -8,6 +8,7 @@ set( CMAKE_CXX_COMPILER clang++ )
set( CMAKE_C_COMPILER_TARGET ${target} )
set( CMAKE_CXX_COMPILER_TARGET ${target} )
set( CMAKE_ASM_COMPILER_TARGET ${target} )
set( arch_c_flags "-march=armv8.7-a -fvectorize -ffp-model=fast -fno-finite-math-only" )
set( warn_c_flags "-Wno-format -Wno-unused-variable -Wno-unused-function -Wno-gnu-zero-variadic-macro-arguments" )
+20
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@@ -2595,6 +2595,26 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.mmproj_use_gpu = value;
}
).set_examples(mmproj_examples).set_env("LLAMA_ARG_MMPROJ_OFFLOAD"));
add_opt(common_arg(
// note: "-mmdev" must sort after "--rpc" in the preset map, else RPC devices are not registered yet
{"-mmdev", "--mmproj-device"}, "DEVICE",
"device to use for multimodal projector (none = don't offload, default: auto)\n"
"use --list-devices to see a list of available devices",
[](common_params & params, const std::string & value) {
if (value == "none") {
params.mmproj_use_gpu = false;
params.mmproj_device = nullptr;
return;
}
auto devices = parse_device_list(value);
// parse_device_list pushes nullptr at back so devices is length 2 for single device.
if (devices.size() > 2) {
throw std::invalid_argument("only one device may be specified for mmproj");
}
params.mmproj_use_gpu = true;
params.mmproj_device = devices.front();
}
).set_examples(mmproj_examples).set_env("MTMD_BACKEND_DEVICE")); // no LLAMA_ARG_ prefix for backward compatibility reason
add_opt(common_arg(
{"--image", "--audio", "--video"}, "FILE",
"path to an image, audio, or video file. use with multimodal models, use comma-separated values for multiple files\n",
+4 -3
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@@ -581,9 +581,10 @@ struct common_params {
// multimodal models (see tools/mtmd)
struct common_params_model mmproj;
bool mmproj_use_gpu = true; // use GPU for multimodal model
bool no_mmproj = false; // explicitly disable multimodal model
std::vector<std::string> image; // path to image file(s) ; TODO: change the name to "media"
bool mmproj_use_gpu = true; // use GPU for multimodal model
ggml_backend_dev_t mmproj_device = nullptr; // GPU device to use for multimodal model
bool no_mmproj = false; // explicitly disable multimodal model
std::vector<std::string> image; // path to image file(s) ; TODO: change the name to "media"
int image_min_tokens = -1;
int image_max_tokens = -1;
int mtmd_batch_max_tokens = 1024;
+107 -35
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@@ -278,7 +278,9 @@ static std::unordered_map<char, std::string> GRAMMAR_LITERAL_ESCAPES = {
{'\r', "\\r"}, {'\n', "\\n"}, {'"', "\\\""}, {'-', "\\-"}, {']', "\\]"}, {'\\', "\\\\"}
};
static std::unordered_set<char> NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?'};
static const int MAX_PATTERN_DEPTH = 100;
static std::unordered_set<char> NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?', '^', '$'};
static std::unordered_set<char> ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'^', '$', '.', '[', ']', '(', ')', '|', '{', '}', '*', '+', '?'};
static std::string replacePattern(const std::string & input, const std::regex & regex, const std::function<std::string(const std::smatch &)> & replacement) {
@@ -309,6 +311,32 @@ static std::string format_literal(const std::string & literal) {
std::string gbnf_format_literal(const std::string & literal) { return format_literal(literal); }
static size_t gbnf_escape_length(const std::string & pattern, size_t pos) {
if (pos + 1 >= pattern.length() || pattern[pos] != '\\') {
return 0;
}
size_t n_hex = 0;
switch (pattern[pos + 1]) {
case 'x': n_hex = 2; break;
case 'u': n_hex = 4; break;
case 'U': n_hex = 8; break;
case 't': case 'r': case 'n': case '\\': case '"': case '[': case ']':
return 2;
default:
return 0;
}
if (pos + 2 + n_hex > pattern.length()) {
return 0;
}
for (size_t i = pos + 2; i < pos + 2 + n_hex; i++) {
char h = pattern[i];
if (!((h >= '0' && h <= '9') || (h >= 'a' && h <= 'f') || (h >= 'A' && h <= 'F'))) {
return 0;
}
}
return 2 + n_hex;
}
class common_schema_converter {
private:
friend class common_schema_info;
@@ -345,16 +373,42 @@ private:
return string_join(rules, " | ");
}
// thrown when the pattern is a valid regex with no grammar equivalent
struct unsupported_pattern : public std::runtime_error {
using std::runtime_error::runtime_error;
};
// thrown when the pattern is not a valid regex
struct invalid_pattern : public std::runtime_error {
using std::runtime_error::runtime_error;
};
std::string _visit_pattern(const std::string & pattern, const std::string & name) {
if (!(pattern.front() == '^' && pattern.back() == '$')) {
_errors.push_back("Pattern must start with '^' and end with '$'");
auto rules_snapshot = _rules;
try {
return _pattern_to_rule(pattern, name);
} catch (const unsupported_pattern & err) {
// revert rules
_rules = std::move(rules_snapshot);
_warnings.push_back("pattern " + pattern + " is not supported (" + err.what() + "), accepting any string");
return _add_rule(name, _add_primitive("string", PRIMITIVE_RULES.at("string")));
} catch (const invalid_pattern & err) {
_rules = std::move(rules_snapshot);
_errors.push_back("Invalid pattern " + pattern + ": " + err.what());
return "";
}
}
std::string _pattern_to_rule(const std::string & pattern, const std::string & name) {
if (pattern.length() < 2 || pattern.front() != '^' || pattern.back() != '$') {
throw unsupported_pattern("not anchored with '^' and '$'");
}
std::string sub_pattern = pattern.substr(1, pattern.length() - 2);
std::unordered_map<std::string, std::string> sub_rule_ids;
size_t i = 0;
size_t length = sub_pattern.length();
int paren_depth = 0;
using literal_or_rule = std::pair<std::string, bool>;
auto to_rule = [&](const literal_or_rule & ls) {
@@ -363,7 +417,6 @@ private:
return is_literal ? "\"" + s + "\"" : s;
};
std::function<literal_or_rule()> transform = [&]() -> literal_or_rule {
size_t start = i;
std::vector<literal_or_rule> seq;
auto get_dot = [&]() {
@@ -420,43 +473,42 @@ private:
if (i + 1 < length && sub_pattern[i + 1] == ':') {
i += 2; // skip "?:" for non-capturing group, treat as regular group
} else {
// lookahead/lookbehind (?=, ?!, ?<=, ?<!) - not supported
_warnings.push_back("Unsupported pattern syntax");
// skip to matching ')' to avoid UB on empty seq
int depth = 1;
while (i < length && depth > 0) {
if (sub_pattern[i] == '\\' && i + 1 < length) {
i += 2; // skip escaped character
} else {
if (sub_pattern[i] == '(') depth++;
else if (sub_pattern[i] == ')') depth--;
i++;
}
}
continue;
// lookaround, named group, inline flags, ...
throw unsupported_pattern("unsupported group syntax");
}
}
paren_depth++;
if (paren_depth > MAX_PATTERN_DEPTH) {
throw unsupported_pattern("pattern nesting too deep");
}
seq.emplace_back("(" + to_rule(transform()) + ")", false);
} else if (c == ')') {
i++;
if (start > 0 && sub_pattern[start - 1] != '(' && (start < 2 || sub_pattern[start - 2] != '?' || sub_pattern[start - 1] != ':')) {
_errors.push_back("Unbalanced parentheses");
if (paren_depth == 0) {
throw invalid_pattern("unbalanced parentheses");
}
paren_depth--;
return join_seq();
} else if (c == '^' || c == '$') {
throw unsupported_pattern("anchor inside the pattern");
} else if (c == '[') {
std::string square_brackets = std::string(1, c);
i++;
while (i < length && sub_pattern[i] != ']') {
if (sub_pattern[i] == '\\') {
square_brackets += sub_pattern.substr(i, 2);
i += 2;
auto escape_length = gbnf_escape_length(sub_pattern, i);
if (escape_length == 0) {
throw unsupported_pattern("unsupported escape in character class: " + sub_pattern.substr(i, 2));
}
square_brackets += sub_pattern.substr(i, escape_length);
i += escape_length;
} else {
square_brackets += sub_pattern[i];
i++;
}
}
if (i >= length) {
_errors.push_back("Unbalanced square brackets");
throw invalid_pattern("unterminated character class");
}
square_brackets += ']';
i++;
@@ -465,6 +517,9 @@ private:
seq.emplace_back("|", false);
i++;
} else if (c == '*' || c == '+' || c == '?') {
if (seq.empty()) {
throw invalid_pattern("nothing to repeat");
}
seq.back() = std::make_pair(to_rule(seq.back()) + c, false);
i++;
} else if (c == '{') {
@@ -475,18 +530,19 @@ private:
i++;
}
if (i >= length) {
_errors.push_back("Unbalanced curly brackets");
throw unsupported_pattern("unterminated curly brackets");
}
curly_brackets += '}';
i++;
auto nums = string_split(curly_brackets.substr(1, curly_brackets.length() - 2), ",");
int min_times = 0;
int max_times = std::numeric_limits<int>::max();
if (nums.size() != 1 && nums.size() != 2) {
throw unsupported_pattern("wrong number of values in curly brackets");
}
try {
if (nums.size() == 1) {
min_times = max_times = std::stoi(nums[0]);
} else if (nums.size() != 2) {
_errors.push_back("Wrong number of values in curly brackets");
} else {
if (!nums[0].empty()) {
min_times = std::stoi(nums[0]);
@@ -495,9 +551,11 @@ private:
max_times = std::stoi(nums[1]);
}
}
} catch (const std::invalid_argument & e) {
_errors.push_back("Invalid number in curly brackets");
return std::make_pair("", false);
} catch (const std::logic_error &) {
throw unsupported_pattern("invalid number in curly brackets");
}
if (seq.empty()) {
throw invalid_pattern("nothing to repeat");
}
auto &last = seq.back();
auto &sub = last.first;
@@ -523,15 +581,22 @@ private:
return NON_LITERAL_SET.find(c) != NON_LITERAL_SET.end();
};
while (i < length) {
if (sub_pattern[i] == '\\' && i < length - 1) {
if (sub_pattern[i] == '\\') {
if (i == length - 1) {
throw invalid_pattern("trailing backslash");
}
char next = sub_pattern[i + 1];
if (ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS.find(next) != ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS.end()) {
i++;
literal += sub_pattern[i];
i++;
} else {
literal += sub_pattern.substr(i, 2);
i += 2;
auto escape_length = gbnf_escape_length(sub_pattern, i);
if (escape_length == 0) {
throw unsupported_pattern("unsupported escape: " + sub_pattern.substr(i, 2));
}
literal += sub_pattern.substr(i, escape_length);
i += escape_length;
}
} else if (sub_pattern[i] == '"') {
literal += "\\\"";
@@ -544,14 +609,21 @@ private:
break;
}
}
if (!literal.empty()) {
seq.emplace_back(literal, true);
if (literal.empty()) { // nothing was consumed, ex. a stray ']' or '}'
throw unsupported_pattern(std::string("unsupported character: ") + c);
}
seq.emplace_back(literal, true);
}
}
return join_seq();
};
return _add_rule(name, "\"\\\"\" (" + to_rule(transform()) + ") \"\\\"\"");
auto rule = to_rule(transform());
if (paren_depth != 0) {
throw invalid_pattern("unbalanced parentheses");
}
return _add_rule(name, "\"\\\"\" (" + rule + ") \"\\\"\"");
}
/*
+4
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@@ -2649,6 +2649,10 @@ void common_speculative_draft(common_speculative * spec) {
for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) dparams.size(); ++seq_id) {
auto & dp = dparams[seq_id];
if (!dp.drafting) {
continue;
}
auto & result = *dp.result;
// a new draft has been sampled
+1
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@@ -57,6 +57,7 @@ TEXT_MODEL_MAP: dict[str, str] = {
"Qwen3DSparkModel": "qwen",
"DSparkDraftModel": "qwen",
"DSparkSpeculator": "qwen",
"Lfm2DSparkDraftModel": "qwen",
"DeepseekV4ForCausalLM": "deepseek",
"DeepseekV4DSparkModel": "deepseek",
"DistilBertForMaskedLM": "bert",
+7 -2
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@@ -207,7 +207,9 @@ class NemotronHModel(GraniteHybridModel):
# calling the parent __init__. This is because the parent constructor
# uses self.model_arch to build the tensor name map, and all MoE-specific
# mappings would be missed if it were called with the default non-MoE arch.
hparams = ModelBase.load_hparams(args[0], self.is_mistral_format)
hparams = kwargs.pop("hparams", None)
if hparams is None:
hparams = ModelBase.load_hparams(args[0], self.is_mistral_format)
has_moe_params = (
"num_experts_per_tok" in hparams
or (isinstance(hparams.get("llm_config"), dict) and "num_experts_per_tok" in hparams["llm_config"])
@@ -215,8 +217,11 @@ class NemotronHModel(GraniteHybridModel):
if has_moe_params:
self.model_arch = gguf.MODEL_ARCH.NEMOTRON_H_MOE
self.is_moe = True
layers_block_type = hparams.get("layers_block_type")
if layers_block_type is not None:
hparams["num_hidden_layers"] = len(layers_block_type)
super().__init__(*args, **kwargs)
super().__init__(*args, hparams=hparams, **kwargs)
# Save the top-level head_dim for later
self.head_dim = self.hparams.get("head_dim", self.hparams.get("attention_head_dim"))
+14 -1
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@@ -709,7 +709,7 @@ class DFlashModel(Qwen3Model):
yield from super().modify_tensors(data_torch, name, bid)
@ModelBase.register("Qwen3DSparkModel", "DSparkDraftModel", "DSparkSpeculator")
@ModelBase.register("Qwen3DSparkModel", "DSparkDraftModel", "DSparkSpeculator", "Lfm2DSparkDraftModel")
@ModelBase.example("satgeze/Qwen3.6-27B-DSpark")
class DSparkModel(DFlashModel):
# DSpark = DFlash + a semi-autoregressive Markov head.
@@ -759,6 +759,13 @@ class DSparkModel(DFlashModel):
return None
return super().filter_tensors(item)
_ROPE_PERMUTE_SUFFIXES = (
"self_attn.q_proj.weight",
"self_attn.k_proj.weight",
"self_attn.q_norm.weight",
"self_attn.k_norm.weight",
)
def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
if name == "model.d2t":
self._d2t = data_torch
@@ -767,6 +774,12 @@ class DSparkModel(DFlashModel):
if self._n_vocab_draft == self.hparams["vocab_size"] and name.endswith(("embed_tokens.weight", "lm_head.weight")):
return
# interleaved-rope checkpoints (rope_is_neox_style = false) -> NeoX layout: per head, even dims first then odd
if not self.hparams.get("rope_is_neox_style", True) and name.endswith(self._ROPE_PERMUTE_SUFFIXES):
head_dim = self.hparams["head_dim"]
shape = data_torch.shape
data_torch = data_torch.reshape(-1, head_dim // 2, 2, *shape[1:]).transpose(1, 2).reshape(shape)
yield from super().modify_tensors(data_torch, name, bid)
def prepare_tensors(self):
+4 -4
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@@ -116,7 +116,7 @@ in inline assembler.
Most kernels are very naive with lots of low hanging fruits left:
> [!IMPORTANT]
> Several assembly instructions emmited by the compiler are not implemented
> Several assembly instructions emitted by the compiler are not implemented
> in hardware and software emulation in firmware is not ready yet.
> Eventually firmware will transparently trap unimplemented instructions
> and will emulate them inside exception handler. Until then, kernel
@@ -138,12 +138,12 @@ Most kernels are very naive with lots of low hanging fruits left:
> kernel build process. Feel free to take ideas/code from there or try linking
> it in.
Before commiting any changes to operations and/or kernels, don't forget
Before committing any changes to operations and/or kernels, don't forget
to update supported ops reports (instructions at `docs/ops.md`).
When logging is enabled (e.g. by setting `--log-file` cli param),
each compute kernel run outputs a line with
pipe-delimited key-value pairs containing kernel level performance infomation.
pipe-delimited key-value pairs containing kernel level performance information.
Line is prefixed with `ET_PERF`:
```
@@ -160,7 +160,7 @@ to `GGML_ET_PROFILE/et_runtime_trace.json` and `GGML_ET_PROFILE/kernel_map` on e
### Uberkernel
The in-knernel implementaiton of device dispatch/kernel fusion. The ET SDK has a non-trivial op-to-op gap. `Uberkernel` (name taken from the original Esperanto AI's compiler)
The in-kernel implementation of device dispatch/kernel fusion. The ET SDK has a non-trivial op-to-op gap. `Uberkernel` (name taken from the original Esperanto AI's compiler)
dispatches multiple already existing kernel implementations with device side synchronization. Due to the processor's design, there is no natural memory visibility
horizon between sub-kernel invocations. This makes uberkernel much more difficult to develop and debug. Currently Uberkerel is hidden begind the
`GGML_ET_UBERKERNEL` environment variable and is disabled by default. Setting it to 1 enables it and provides significant performance improvements but is only
+2 -1
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@@ -72,9 +72,10 @@ cmake --build build --config Release
- Please remember to always use a Developer Command Prompt / PowerShell for VS2022 for git, build, test
- For Windows on ARM (arm64, WoA) build with:
```bash
cmake --preset arm64-windows-llvm-release -D GGML_OPENMP=OFF
cmake --preset arm64-windows-llvm-release -D GGML_OPENMP_FETCH=ON
cmake --build build-arm64-windows-llvm-release
```
`GGML_OPENMP_FETCH` downloads the official LLVM OpenMP runtime and requires Clang, 7-Zip and network access during configuration. CMake selects the runtime from the target architecture, so this also works when cross-compiling for WoA from x64. The extracted header, import library, DLL and OpenMP license are placed under `build/_deps`. The build copies `libomp.dll` and `LICENSE-LLVM-OpenMP` to the runtime output directory and installs them together. Omit the option to use CMake's normal OpenMP detection, or pass `-D GGML_OPENMP=OFF` to disable OpenMP.
For building with ninja generator and clang compiler as default:
-set path:set LIB=C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\um\x64;C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Tools\MSVC\14.41.34120\lib\x64\uwp;C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\ucrt\x64
```bash
+1
View File
@@ -243,6 +243,7 @@ set (GGML_METAL_MACOSX_VERSION_MIN "" CACHE STRING
"ggml: metal minimum macOS version")
set (GGML_METAL_STD "" CACHE STRING "ggml: metal standard version (-std flag)")
option(GGML_OPENMP "ggml: use OpenMP" ON)
option(GGML_OPENMP_FETCH "ggml: fetch LLVM OpenMP" OFF)
option(GGML_RPC "ggml: use RPC" OFF)
option(GGML_SYCL "ggml: use SYCL" OFF)
option(GGML_SYCL_F16 "ggml: use 16 bit floats for sycl calculations" OFF)
+116 -2
View File
@@ -222,9 +222,123 @@ if (GGML_SCHED_NO_REALLOC)
target_compile_definitions(ggml-base PUBLIC GGML_SCHED_NO_REALLOC)
endif()
if (GGML_OPENMP)
if (GGML_OPENMP_FETCH)
if (NOT GGML_OPENMP)
message(FATAL_ERROR "GGML_OPENMP_FETCH requires GGML_OPENMP")
elseif (NOT WIN32 OR NOT (CMAKE_C_COMPILER_ID MATCHES "Clang"))
message(FATAL_ERROR "GGML_OPENMP_FETCH currently requires Clang on Windows")
endif()
set(GGML_OPENMP_LLVM_VERSION "20.1.8")
string(REGEX MATCH "^[0-9]+" GGML_OPENMP_LLVM_VERSION_MAJOR "${GGML_OPENMP_LLVM_VERSION}")
string(REGEX MATCH "^[0-9]+" GGML_OPENMP_COMPILER_VERSION_MAJOR "${CMAKE_C_COMPILER_VERSION}")
if (NOT GGML_OPENMP_COMPILER_VERSION_MAJOR STREQUAL GGML_OPENMP_LLVM_VERSION_MAJOR)
message(FATAL_ERROR "LLVM OpenMP ${GGML_OPENMP_LLVM_VERSION} requires Clang ${GGML_OPENMP_LLVM_VERSION_MAJOR}.x")
endif()
string(TOLOWER "${CMAKE_SYSTEM_PROCESSOR}" GGML_OPENMP_SYSTEM_PROCESSOR)
if (GGML_OPENMP_SYSTEM_PROCESSOR MATCHES "^(amd64|x86_64)$")
set(GGML_OPENMP_ARCH "x64")
set(GGML_OPENMP_INSTALLER_SUFFIX "win64")
set(GGML_OPENMP_INSTALLER_SHA256 "3197846a2b19063687dd56e93e34cd941e3548d907f23a6131571321bdf9fe7b")
elseif (GGML_OPENMP_SYSTEM_PROCESSOR MATCHES "^(aarch64|arm64)$")
set(GGML_OPENMP_ARCH "arm64")
set(GGML_OPENMP_INSTALLER_SUFFIX "woa64")
set(GGML_OPENMP_INSTALLER_SHA256 "7c4ac97eb2ae6b960ca5f9caf3ff6124c8d2a18cc07a7840a4d2ea15537bad8e")
else()
message(FATAL_ERROR "GGML_OPENMP_FETCH does not support ${CMAKE_SYSTEM_PROCESSOR}")
endif()
set(GGML_OPENMP_CACHE_DIR "${CMAKE_BINARY_DIR}/_deps")
set(GGML_OPENMP_ROOT "${GGML_OPENMP_CACHE_DIR}/llvm-openmp-${GGML_OPENMP_LLVM_VERSION}-${GGML_OPENMP_ARCH}")
set(GGML_OPENMP_LIBRARY "${GGML_OPENMP_ROOT}/lib/libomp.lib")
set(GGML_OPENMP_RUNTIME "${GGML_OPENMP_ROOT}/bin/libomp.dll")
set(GGML_OPENMP_HEADER "${GGML_OPENMP_ROOT}/include/omp.h")
set(GGML_OPENMP_LICENSE "${GGML_OPENMP_ROOT}/LICENSE.TXT")
set(GGML_OPENMP_LICENSE_SHA256 "fdad1758a9e1f9d5a81e18879b3406772115edc92c24bfa36b70c654f325e8e4")
if (NOT EXISTS "${GGML_OPENMP_LIBRARY}" OR NOT EXISTS "${GGML_OPENMP_RUNTIME}" OR NOT EXISTS "${GGML_OPENMP_HEADER}")
find_program(GGML_OPENMP_7Z NAMES 7z 7zz 7za)
if (NOT GGML_OPENMP_7Z)
message(FATAL_ERROR "GGML_OPENMP_FETCH requires 7-Zip to extract the LLVM installer")
endif()
set(GGML_OPENMP_INSTALLER "${GGML_OPENMP_ROOT}/LLVM-${GGML_OPENMP_LLVM_VERSION}-${GGML_OPENMP_INSTALLER_SUFFIX}.exe")
set(GGML_OPENMP_EXTRACT_DIR "${GGML_OPENMP_ROOT}/extract")
set(GGML_OPENMP_INSTALLER_URL "https://github.com/llvm/llvm-project/releases/download/llvmorg-${GGML_OPENMP_LLVM_VERSION}/LLVM-${GGML_OPENMP_LLVM_VERSION}-${GGML_OPENMP_INSTALLER_SUFFIX}.exe")
file(MAKE_DIRECTORY "${GGML_OPENMP_EXTRACT_DIR}")
file(DOWNLOAD "${GGML_OPENMP_INSTALLER_URL}" "${GGML_OPENMP_INSTALLER}"
EXPECTED_HASH "SHA256=${GGML_OPENMP_INSTALLER_SHA256}"
SHOW_PROGRESS
STATUS GGML_OPENMP_DOWNLOAD_STATUS)
list(GET GGML_OPENMP_DOWNLOAD_STATUS 0 GGML_OPENMP_DOWNLOAD_RESULT)
if (NOT GGML_OPENMP_DOWNLOAD_RESULT EQUAL 0)
list(GET GGML_OPENMP_DOWNLOAD_STATUS 1 GGML_OPENMP_DOWNLOAD_ERROR)
message(FATAL_ERROR "Failed to download LLVM OpenMP: ${GGML_OPENMP_DOWNLOAD_ERROR}")
endif()
execute_process(
COMMAND "${GGML_OPENMP_7Z}" e -y "-o${GGML_OPENMP_EXTRACT_DIR}" "${GGML_OPENMP_INSTALLER}" -r libomp.lib libomp.dll omp.h
RESULT_VARIABLE GGML_OPENMP_EXTRACT_RESULT
OUTPUT_QUIET)
if (NOT GGML_OPENMP_EXTRACT_RESULT EQUAL 0 OR
NOT EXISTS "${GGML_OPENMP_EXTRACT_DIR}/libomp.lib" OR
NOT EXISTS "${GGML_OPENMP_EXTRACT_DIR}/libomp.dll" OR
NOT EXISTS "${GGML_OPENMP_EXTRACT_DIR}/omp.h")
message(FATAL_ERROR "Failed to extract libomp from ${GGML_OPENMP_INSTALLER}")
endif()
file(MAKE_DIRECTORY "${GGML_OPENMP_ROOT}/lib" "${GGML_OPENMP_ROOT}/bin" "${GGML_OPENMP_ROOT}/include")
file(COPY "${GGML_OPENMP_EXTRACT_DIR}/libomp.lib" DESTINATION "${GGML_OPENMP_ROOT}/lib")
file(COPY "${GGML_OPENMP_EXTRACT_DIR}/libomp.dll" DESTINATION "${GGML_OPENMP_ROOT}/bin")
file(COPY "${GGML_OPENMP_EXTRACT_DIR}/omp.h" DESTINATION "${GGML_OPENMP_ROOT}/include")
file(REMOVE_RECURSE "${GGML_OPENMP_INSTALLER}" "${GGML_OPENMP_EXTRACT_DIR}")
endif()
# The NSIS installer embeds LLVM's general license in its UI but does not install it as a file; use OpenMP's license to include its additional notices.
if (EXISTS "${GGML_OPENMP_LICENSE}")
file(SHA256 "${GGML_OPENMP_LICENSE}" GGML_OPENMP_LICENSE_ACTUAL_SHA256)
endif()
if (NOT GGML_OPENMP_LICENSE_ACTUAL_SHA256 STREQUAL GGML_OPENMP_LICENSE_SHA256)
file(DOWNLOAD "https://raw.githubusercontent.com/llvm/llvm-project/llvmorg-${GGML_OPENMP_LLVM_VERSION}/openmp/LICENSE.TXT" "${GGML_OPENMP_LICENSE}"
EXPECTED_HASH "SHA256=${GGML_OPENMP_LICENSE_SHA256}")
endif()
if (COMMAND license_add_file)
license_add_file("LLVM OpenMP" "${GGML_OPENMP_LICENSE}")
endif()
add_library(ggml-openmp-c INTERFACE)
target_compile_options(ggml-openmp-c INTERFACE "$<$<COMPILE_LANGUAGE:C>:-fopenmp=libomp>")
target_include_directories(ggml-openmp-c SYSTEM INTERFACE "${GGML_OPENMP_ROOT}/include")
target_link_libraries(ggml-openmp-c INTERFACE "${GGML_OPENMP_LIBRARY}")
add_library(ggml-openmp-cxx INTERFACE)
target_compile_options(ggml-openmp-cxx INTERFACE "$<$<COMPILE_LANGUAGE:CXX>:-fopenmp=libomp>")
target_include_directories(ggml-openmp-cxx SYSTEM INTERFACE "${GGML_OPENMP_ROOT}/include")
target_link_libraries(ggml-openmp-cxx INTERFACE "${GGML_OPENMP_LIBRARY}")
set(GGML_OPENMP_RUNTIME_OUTPUT_DIR "${CMAKE_RUNTIME_OUTPUT_DIRECTORY}")
if (CMAKE_CONFIGURATION_TYPES)
string(APPEND GGML_OPENMP_RUNTIME_OUTPUT_DIR "/$<CONFIG>")
endif()
add_custom_target(ggml-openmp-runtime ALL
COMMAND ${CMAKE_COMMAND} -E make_directory "${GGML_OPENMP_RUNTIME_OUTPUT_DIR}"
COMMAND ${CMAKE_COMMAND} -E copy_if_different "${GGML_OPENMP_RUNTIME}" "${GGML_OPENMP_RUNTIME_OUTPUT_DIR}/libomp.dll"
COMMAND ${CMAKE_COMMAND} -E copy_if_different "${GGML_OPENMP_LICENSE}" "${GGML_OPENMP_RUNTIME_OUTPUT_DIR}/LICENSE-LLVM-OpenMP")
add_dependencies(ggml-base ggml-openmp-runtime)
install(FILES "${GGML_OPENMP_RUNTIME}" DESTINATION ${CMAKE_INSTALL_BINDIR})
install(FILES "${GGML_OPENMP_LICENSE}" DESTINATION ${CMAKE_INSTALL_BINDIR} RENAME LICENSE-LLVM-OpenMP)
set(GGML_OPENMP_TARGET_C ggml-openmp-c)
set(GGML_OPENMP_TARGET_CXX ggml-openmp-cxx)
set(GGML_OPENMP_ENABLED "ON" CACHE INTERNAL "")
elseif (GGML_OPENMP)
find_package(OpenMP)
if (OpenMP_FOUND)
set(GGML_OPENMP_TARGET_C OpenMP::OpenMP_C)
set(GGML_OPENMP_TARGET_CXX OpenMP::OpenMP_CXX)
set(GGML_OPENMP_ENABLED "ON" CACHE INTERNAL "")
else()
set(GGML_OPENMP_ENABLED "OFF" CACHE INTERNAL "")
@@ -236,7 +350,7 @@ endif()
if (GGML_OPENMP_ENABLED)
target_compile_definitions(ggml-base PRIVATE GGML_USE_OPENMP)
target_link_libraries(ggml-base PRIVATE OpenMP::OpenMP_C OpenMP::OpenMP_CXX)
target_link_libraries(ggml-base PRIVATE ${GGML_OPENMP_TARGET_C} ${GGML_OPENMP_TARGET_CXX})
endif()
add_library(ggml
+17 -5
View File
@@ -1599,11 +1599,23 @@ static enum ggml_status ggml_backend_sched_compute_splits(ggml_backend_sched_t s
std::vector<int32_t> ids;
std::vector<ggml_bitset_t> used_ids;
int prev_backend_id = -1;
for (int split_id = 0; split_id < sched->n_splits; split_id++) {
struct ggml_backend_sched_split * split = &splits[split_id];
int split_backend_id = split->backend_id;
ggml_backend_t split_backend = sched->backends[split_backend_id];
// ensure the previous split's async work has completed before we start
// this split, the allocator may have reused buffer regions across splits
if (split->n_inputs == 0 && prev_backend_id >= 0 && prev_backend_id != split_backend_id) {
if (sched->events[prev_backend_id][sched->cur_copy] != NULL) {
ggml_backend_event_synchronize(sched->events[prev_backend_id][sched->cur_copy]);
} else {
ggml_backend_synchronize(sched->backends[prev_backend_id]);
}
}
// copy the input tensors to the split backend
for (int input_id = 0; input_id < split->n_inputs; input_id++) {
ggml_backend_t input_backend = ggml_backend_sched_get_tensor_backend(sched, split->inputs[input_id]);
@@ -1766,12 +1778,12 @@ static enum ggml_status ggml_backend_sched_compute_splits(ggml_backend_sched_t s
}
}
// record the event of this copy
if (split->n_inputs > 0) {
if (sched->events[split_backend_id][sched->cur_copy] != NULL) {
ggml_backend_event_record(sched->events[split_backend_id][sched->cur_copy], split_backend);
}
// record the event of this split
if (sched->events[split_backend_id][sched->cur_copy] != NULL) {
ggml_backend_event_record(sched->events[split_backend_id][sched->cur_copy], split_backend);
}
prev_backend_id = split_backend_id;
}
return GGML_STATUS_SUCCESS;
+1 -1
View File
@@ -74,7 +74,7 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
if (GGML_OPENMP_ENABLED)
target_compile_definitions(${GGML_CPU_NAME} PRIVATE GGML_USE_OPENMP)
target_link_libraries(${GGML_CPU_NAME} PRIVATE OpenMP::OpenMP_C OpenMP::OpenMP_CXX)
target_link_libraries(${GGML_CPU_NAME} PRIVATE ${GGML_OPENMP_TARGET_C} ${GGML_OPENMP_TARGET_CXX})
endif()
if (GGML_LLAMAFILE)
+5 -3
View File
@@ -29,13 +29,15 @@ extern "C" {
// FP16 to FP32 conversion
// 16-bit float
// on Arm, we use __fp16
// on Arm, we use __fp16, which requires the IEEE fp16 format: implied on
// AArch64, selected by -mfp16-format=ieee on 32 bit Arm, where the compiler
// may otherwise reject the type
// on x86, we use uint16_t
//
// for old CUDA compilers (<= 11), we use uint16_t: ref https://github.com/ggml-org/llama.cpp/pull/10616
// for MUSA compilers , we use uint16_t: ref https://github.com/ggml-org/llama.cpp/pull/11843
//
#if defined(__ARM_NEON) && !(defined(__CUDACC__) && __CUDACC_VER_MAJOR__ <= 11) && !defined(__MUSACC__)
#if defined(__ARM_NEON) && defined(__ARM_FP16_FORMAT_IEEE) && !(defined(__CUDACC__) && __CUDACC_VER_MAJOR__ <= 11) && !defined(__MUSACC__)
#define GGML_CPU_COMPUTE_FP16_TO_FP32(x) neon_compute_fp16_to_fp32(x)
#define GGML_CPU_COMPUTE_FP32_TO_FP16(x) neon_compute_fp32_to_fp16(x)
@@ -326,7 +328,7 @@ inline static float ggml_lookup_fp16_to_fp32(ggml_fp16_t f) {
#define GGML_F16_VEC_REDUCE GGML_F32Cx4_REDUCE
#endif
#elif defined(__ARM_NEON) && defined(__ARM_FEATURE_FMA)
#elif defined(__ARM_NEON) && defined(__ARM_FEATURE_FMA) && defined(__ARM_FP16_FORMAT_IEEE)
#define GGML_SIMD
+18 -11
View File
@@ -1418,7 +1418,9 @@ struct ggml_backend_cuda_context {
cudaEvent_t copy_event = nullptr;
cudaStream_t streams[GGML_CUDA_MAX_DEVICES][GGML_CUDA_MAX_STREAMS] = { { nullptr } };
cublasHandle_t cublas_handles[GGML_CUDA_MAX_DEVICES] = {nullptr};
cublasHandle_t cublas_handles[GGML_CUDA_MAX_DEVICES][GGML_CUDA_MAX_STREAMS] = {nullptr};
void * cublas_workspaces[GGML_CUDA_MAX_DEVICES][GGML_CUDA_MAX_STREAMS] = {nullptr};
size_t cublas_workspace_sizes[GGML_CUDA_MAX_DEVICES] = {0};
int curr_stream_no = 0;
@@ -1495,17 +1497,22 @@ struct ggml_backend_cuda_context {
ggml_cuda_stream_context & stream_context() { return concurrent_stream_context; }
cublasHandle_t cublas_handle(int device) {
if (cublas_handles[device] == nullptr) {
ggml_cuda_set_device(device);
CUBLAS_CHECK(cublasCreate(&cublas_handles[device]));
CUBLAS_CHECK(cublasSetMathMode(cublas_handles[device], CUBLAS_TF32_TENSOR_OP_MATH));
}
return cublas_handles[device];
}
cublasHandle_t cublas_handle() {
return cublas_handle(device);
if (cublas_handles[device][curr_stream_no] == nullptr) {
ggml_cuda_set_device(device);
CUBLAS_CHECK(cublasCreate(&cublas_handles[device][curr_stream_no]));
CUBLAS_CHECK(cublasSetMathMode(cublas_handles[device][curr_stream_no], CUBLAS_TF32_TENSOR_OP_MATH));
CUBLAS_CHECK(cublasSetStream(cublas_handles[device][curr_stream_no], stream()));
#if !defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA) && (CUBLAS_VER_MAJOR > 11 || (CUBLAS_VER_MAJOR == 11 && CUBLAS_VER_MINOR >= 2))
if (cublas_workspace_sizes[device] == 0) {
const int cc = ggml_cuda_info().devices[device].cc;
cublas_workspace_sizes[device] = (cc >= GGML_CUDA_CC_HOPPER) ? 32 * 1024 * 1024 : 4 * 1024 * 1024;
}
CUDA_CHECK(cudaMalloc(&cublas_workspaces[device][curr_stream_no], cublas_workspace_sizes[device]));
CUBLAS_CHECK(cublasSetWorkspace(cublas_handles[device][curr_stream_no], cublas_workspaces[device][curr_stream_no], cublas_workspace_sizes[device]));
#endif
}
return cublas_handles[device][curr_stream_no];
}
// pool
+11 -8
View File
@@ -711,9 +711,12 @@ ggml_backend_cuda_context::~ggml_backend_cuda_context() {
if (streams[i][j] != nullptr) {
CUDA_CHECK(cudaStreamDestroy(streams[i][j]));
}
}
if (cublas_handles[i] != nullptr) {
CUBLAS_CHECK(cublasDestroy(cublas_handles[i]));
if (cublas_handles[i][j] != nullptr) {
CUBLAS_CHECK(cublasDestroy(cublas_handles[i][j]));
}
if (cublas_workspaces[i][j] != nullptr) {
CUDA_CHECK(cudaFree(cublas_workspaces[i][j]));
}
}
}
}
@@ -1416,7 +1419,7 @@ static void ggml_cuda_mul_mat_cublas_impl(ggml_backend_cuda_context & ctx, const
const int64_t ne_dst = ggml_nelements(dst);
cudaStream_t main_stream = ctx.stream();
CUBLAS_CHECK(cublasSetStream(ctx.cublas_handle(), main_stream));
cublasHandle_t cublas_h = ctx.cublas_handle();
const size_t src0_ts = ggml_type_size(src0->type);
GGML_ASSERT(nb00 == src0_ts);
@@ -1539,14 +1542,14 @@ static void ggml_cuda_mul_mat_cublas_impl(ggml_backend_cuda_context & ctx, const
// probably because the internal kernel selection logic is suboptimal.
if (compute_type == GGML_TYPE_F32 && ne12 == 1 && ne13 == 1) {
CUBLAS_CHECK(
cublasSgemm(ctx.cublas_handle(), CUBLAS_OP_T, CUBLAS_OP_N,
cublasSgemm(cublas_h, CUBLAS_OP_T, CUBLAS_OP_N,
ne01, ne11, ne10,
(const float *) alpha, (const float *) src0_ptr, s01,
(const float *) src1_ptr, s11,
(const float *) beta, (float *) dst_ptr, ne0));
} else if (ne12 == 1 && ne13 == 1) {
CUBLAS_CHECK(
cublasGemmEx(ctx.cublas_handle(), CUBLAS_OP_T, CUBLAS_OP_N,
cublasGemmEx(cublas_h, CUBLAS_OP_T, CUBLAS_OP_N,
ne01, ne11, ne10,
alpha, src0_ptr, cu_data_type_a, s01,
src1_ptr, cu_data_type_b, s11,
@@ -1561,7 +1564,7 @@ static void ggml_cuda_mul_mat_cublas_impl(ggml_backend_cuda_context & ctx, const
// there is no broadcast and src0, src1 are contiguous across dims 2, 3
// use cublasGemmStridedBatchedEx
CUBLAS_CHECK(
cublasGemmStridedBatchedEx(ctx.cublas_handle(), CUBLAS_OP_T, CUBLAS_OP_N,
cublasGemmStridedBatchedEx(cublas_h, CUBLAS_OP_T, CUBLAS_OP_N,
ne01, ne11, ne10,
alpha, src0_ptr, cu_data_type_a, s01, sma, // strideA
src1_ptr, cu_data_type_b, s11, smb, // strideB
@@ -1599,7 +1602,7 @@ static void ggml_cuda_mul_mat_cublas_impl(ggml_backend_cuda_context & ctx, const
CUDA_CHECK(cudaGetLastError());
CUBLAS_CHECK(
cublasGemmBatchedEx(ctx.cublas_handle(), CUBLAS_OP_T, CUBLAS_OP_N,
cublasGemmBatchedEx(cublas_h, CUBLAS_OP_T, CUBLAS_OP_N,
ne01, ne11, ne10,
alpha, (const void **) (ptrs_src.get() + 0*ne23), cu_data_type_a, s01,
(const void **) (ptrs_src.get() + 1*ne23), cu_data_type_b, s11,
+36
View File
@@ -290,6 +290,42 @@ bool ggml_cuda_should_use_mmvq(enum ggml_type type, int cc, int64_t ne11) {
if (!ggml_is_quantized(type)) {
return false;
}
// k-quants cost more to decode and mvq redoes that per column, so MMQ wins sooner.
// Only list quant-types MMQ supports, others would fall back to cuBLAS.
if (GGML_CUDA_CC_IS_NVIDIA(cc) && cc == GGML_CUDA_CC_ADA_LOVELACE) {
switch (type) { // tuned on RTX 4090
case GGML_TYPE_Q2_K:
return ne11 <= 4;
case GGML_TYPE_Q3_K:
return ne11 <= 6;
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
return ne11 <= 7;
default:
return ne11 <= MMVQ_MAX_BATCH_SIZE;
}
}
if (GGML_CUDA_CC_IS_NVIDIA(cc) && cc == GGML_CUDA_CC_BLACKWELL) {
switch (type) { // tuned on RTX 5090
case GGML_TYPE_Q2_K:
case GGML_TYPE_Q3_K:
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
return ne11 <= 5;
case GGML_TYPE_Q6_K:
return ne11 <= 7;
default:
return ne11 <= MMVQ_MAX_BATCH_SIZE;
}
}
if (GGML_CUDA_CC_IS_NVIDIA(cc) && cc == GGML_CUDA_CC_DGX_SPARK) {
switch (type) { // tuned on DGX Spark GB10
case GGML_TYPE_Q2_K:
return ne11 <= 6;
default:
return ne11 <= MMVQ_MAX_BATCH_SIZE;
}
}
if (GGML_CUDA_CC_IS_CDNA(cc)) {
if (GGML_CUDA_CC_IS_CDNA1(cc)) {
switch (type) {
-2
View File
@@ -54,8 +54,6 @@ void ggml_cuda_out_prod(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
const float alpha = 1.0f;
const float beta = 0.0f;
CUBLAS_CHECK(cublasSetStream(handle, stream));
const int64_t lda = nb01 / sizeof(float);
const int64_t ldc = nb1 / sizeof(float);
+3 -5
View File
@@ -65,15 +65,13 @@ static void solve_tri_f32_cublas(ggml_backend_cuda_context & ctx,
get_batch_pointers<<<(total_batches + 255) / 256, 256, 0, stream>>>(A, X, A_ptrs_dev, X_ptrs_dev, ne02,
total_batches, s02, s03, s2, s3);
CUBLAS_CHECK(cublasSetStream(ctx.cublas_handle(id), stream));
// Yes, this is necessary, without this we get RMSE errors
CUBLAS_CHECK(cublasSetMathMode(ctx.cublas_handle(id), CUBLAS_DEFAULT_MATH));
CUBLAS_CHECK(cublasStrsmBatched(ctx.cublas_handle(id), CUBLAS_SIDE_RIGHT, CUBLAS_FILL_MODE_UPPER, CUBLAS_OP_N,
CUBLAS_CHECK(cublasSetMathMode(ctx.cublas_handle(), CUBLAS_DEFAULT_MATH));
CUBLAS_CHECK(cublasStrsmBatched(ctx.cublas_handle(), CUBLAS_SIDE_RIGHT, CUBLAS_FILL_MODE_UPPER, CUBLAS_OP_N,
CUBLAS_DIAG_NON_UNIT, k, n, &alpha, A_ptrs_dev, n, X_ptrs_dev, k, total_batches));
// revert to standard mode from common.cuh
CUBLAS_CHECK(cublasSetMathMode(ctx.cublas_handle(id), CUBLAS_TF32_TENSOR_OP_MATH));
CUBLAS_CHECK(cublasSetMathMode(ctx.cublas_handle(), CUBLAS_TF32_TENSOR_OP_MATH));
GGML_UNUSED_VARS(s12, s13);
}
-1
View File
@@ -632,7 +632,6 @@ static void ssm_scan_ssd_f32_cuda(
// Step 3: chunked SSD loop
// Per chunk: pre_matmul (incl. M) + 4 cuBLAS (CB, Y, S@C, state update) + scale_state
cublasHandle_t handle = ctx.cublas_handle();
CUBLAS_CHECK(cublasSetStream(handle, stream));
const float alpha_one = 1.0f;
const float beta_zero = 0.0f;
const float beta_one = 1.0f;
+3 -2
View File
@@ -3180,8 +3180,9 @@ static bool ggml_hexagon_supported_argsort(const struct ggml_hexagon_session * s
static bool ggml_hexagon_supported_rope(const struct ggml_hexagon_session * sess, const struct ggml_tensor * op) {
const int32_t * op_params = &op->op_params[0];
if (op_params[15] != 0) {
return false; // FIXME: support ggml_rope_set_offset
// ggml_rope_set_offset: HVX kernels need a VLEN-aligned window start (32 f32 elems)
if (op_params[15] % 32 != 0) {
return false;
}
int mode = op_params[2];
+43 -33
View File
@@ -132,8 +132,8 @@ struct hmx_fa_context {
__fp16 * vtcm_v_tiles[2]; // V tiles (column-major, double-buffered)
__fp16 * vtcm_s_tiles[2]; // S = QK^T [g_br, Bc] (double-buffered)
__fp16 * vtcm_p_tiles[2]; // P = softmax(S) [g_br, Bc]
__fp16 * vtcm_d_tiles; // Diagonal rescale [g_br, g_br]
__fp16 * vtcm_d_inv_l; // Diagonal rescale (1/l) [g_br, g_br]
__fp16 * vtcm_d_tiles[2]; // Diagonal rescale, g_br/32 packed diagonal tiles (double-buffered)
__fp16 * vtcm_d_inv_l; // Diagonal rescale (1/l), same packed layout
HVX_Vector * vtcm_m_vec; // Row max [g_br]
HVX_Vector * vtcm_l_vec; // Row sum [g_br]
HVX_Vector * vtcm_s_rowmax; // Softmax intermediate [g_br]
@@ -782,13 +782,14 @@ static void fa_q_load_thread(unsigned int n, unsigned int i, void * data) {
}
}
// Initialize vtcm_d_tiles and vtcm_d_inv_l to 0
// Zero the whole rescale region: vtcm_d_tiles[0], the optional vtcm_d_tiles[1]
// and vtcm_d_inv_l are equal-sized and allocated back to back, so one run covers
// them all. The scatter only ever writes the diagonal, ignore the rest.
const size_t d_bytes_per_t = hex_align_up(d_tile_bytes / n, 128);
const size_t d_start = i * d_bytes_per_t;
const size_t d_end = hex_smin(d_start + d_bytes_per_t, d_tile_bytes);
if (d_start < d_tile_bytes) {
hvx_splat_u8_a((char *) factx->vtcm_d_tiles + d_start, 0, d_end - d_start);
hvx_splat_u8_a((char *) factx->vtcm_d_inv_l + d_start, 0, d_end - d_start);
hvx_splat_u8_a((char *) factx->vtcm_d_tiles[0] + d_start, 0, d_end - d_start);
}
}
@@ -1432,17 +1433,19 @@ static inline void fa_softmax_impl(
const HVX_VectorPred q_32_mask = Q6_Q_vsetq_R(32 * sizeof(__fp16));
HVX_Vector v_exp_m_diff = exp_m_diff_f16;
__fp16 * const d_tiles_out = factx->vtcm_d_tiles[args->buf_idx];
size_t t0 = r_vec_idx * 2;
if (t0 < args->n_row_tiles) {
const HVX_Vector v_content = v_exp_m_diff;
__fp16 * out_base = factx->vtcm_d_tiles + t0 * (args->n_row_tiles_g_br + 1) * HMX_FP16_TILE_N_ELMS;
__fp16 * out_base = d_tiles_out + t0 * HMX_FP16_TILE_N_ELMS;
Q6_vscatter_QRMVhV(q_32_mask, (size_t) out_base, HMX_FP16_TILE_SIZE - 1, v_offsets, v_content);
}
size_t t1 = r_vec_idx * 2 + 1;
if (t1 < args->n_row_tiles) {
const HVX_Vector v_content = Q6_V_vror_VR(v_exp_m_diff, 64);
__fp16 * out_base = factx->vtcm_d_tiles + t1 * (args->n_row_tiles_g_br + 1) * HMX_FP16_TILE_N_ELMS;
__fp16 * out_base = d_tiles_out + t1 * HMX_FP16_TILE_N_ELMS;
Q6_vscatter_QRMVhV(q_32_mask, (size_t) out_base, HMX_FP16_TILE_SIZE - 1, v_offsets, v_content);
}
}
@@ -1506,7 +1509,7 @@ static __attribute__((noinline)) void fa_build_d_diag_inv_l(struct hmx_fa_contex
v_content = Q6_V_vror_VR(v_content, 64);
}
__fp16 * out_base = factx->vtcm_d_inv_l + i * (n_row_tiles_g_br + 1) * HMX_FP16_TILE_N_ELMS;
__fp16 * out_base = factx->vtcm_d_inv_l + i * HMX_FP16_TILE_N_ELMS;
Q6_vscatter_QRMVhV(q_32_mask, (size_t) out_base, HMX_FP16_TILE_SIZE - 1, v_offsets, v_content);
}
}
@@ -1615,7 +1618,7 @@ static void hmx_fa_o_update_worker(void * data) {
const size_t o_stride = n_row_tiles_g_br * HMX_FP16_TILE_N_ELMS;
const size_t v_stride = n_tiles_per_bc * HMX_FP16_TILE_N_ELMS;
for (size_t r = 0; r < n_row_tiles; ++r) {
const __fp16 * d_diag = d_tiles + r * (n_row_tiles_g_br + 1) * HMX_FP16_TILE_N_ELMS;
const __fp16 * d_diag = d_tiles + r * HMX_FP16_TILE_N_ELMS;
const __fp16 * p_tile_in = p_tiles + (r * n_tiles_per_bc) * HMX_FP16_TILE_N_ELMS;
const __fp16 * o_rc = o_prev + r * HMX_FP16_TILE_N_ELMS;
const __fp16 * v_tile_in = v_tiles;
@@ -1654,7 +1657,7 @@ static void hmx_fa_o_norm_worker(void * data) {
asm volatile(HMX_SET_BIAS("%0") :: "r"((unsigned int)job->hmx_scales));
const size_t o_stride = n_row_tiles_g_br * HMX_FP16_TILE_N_ELMS;
for (size_t r = 0; r < n_row_tiles; ++r) {
const __fp16 * d_diag = d_tiles + r * (n_row_tiles_g_br + 1) * HMX_FP16_TILE_N_ELMS;
const __fp16 * d_diag = d_tiles + r * HMX_FP16_TILE_N_ELMS;
const __fp16 * o_rc = o_prev + r * HMX_FP16_TILE_N_ELMS;
__fp16 * o_out = o_curr + r * DV_tiles * HMX_FP16_TILE_N_ELMS;
@@ -1882,7 +1885,8 @@ int hmx_flash_attn_ext(struct htp_ops_context * octx) {
factx.vtcm_s_tiles[1] = VTCM_LAYOUT_PTR_OPTIONAL(__fp16, base, L.off_s_tiles[1], pipeline);
factx.vtcm_p_tiles[0] = VTCM_LAYOUT_PTR(__fp16, base, L.off_p_tiles[0]);
factx.vtcm_p_tiles[1] = VTCM_LAYOUT_PTR_OPTIONAL(__fp16, base, L.off_p_tiles[1], pipeline);
factx.vtcm_d_tiles = VTCM_LAYOUT_PTR(__fp16, base, L.off_d_tiles);
factx.vtcm_d_tiles[0] = VTCM_LAYOUT_PTR(__fp16, base, L.off_d_tiles[0]);
factx.vtcm_d_tiles[1] = VTCM_LAYOUT_PTR_OPTIONAL(__fp16, base, L.off_d_tiles[1], pipeline);
factx.vtcm_d_inv_l = VTCM_LAYOUT_PTR(__fp16, base, L.off_d_inv_l);
factx.vtcm_m_vec = VTCM_LAYOUT_PTR(HVX_Vector, base, L.off_m_vec);
factx.vtcm_l_vec = VTCM_LAYOUT_PTR(HVX_Vector, base, L.off_l_vec);
@@ -2039,7 +2043,30 @@ int hmx_flash_attn_ext(struct htp_ops_context * octx) {
}
}
// ---- 3. Pop and run K-prep for next block & push next QK-dot ----
// ---- 3. Start HMX O update for block kv_blk - 1 (reads P[1 - buf_idx], V[1 - buf_idx], D) ----
// O update relys on the previous block's P and V tiles.
// O update MUST be pushed before the next block's QK-dot: hmx_queue_pop() retires the
// oldest descriptor, so push order alone decides which pop waits for which job.
// If OU went in after QK(i+1), the pop below would retire QK(i+1) and leave
// OU(i-1) in flight into the next iteration, where V-prep overwrites V[prev_buf].
if (kv_blk > 0) {
const size_t prev_buf = 1 - buf_idx;
ou_job[prev_buf].o_curr = o_tile_curr;
ou_job[prev_buf].o_prev = o_tile_prev;
ou_job[prev_buf].p_tiles = factx.vtcm_p_tiles[prev_buf];
ou_job[prev_buf].v_tiles = factx.vtcm_v_tiles[prev_buf];
ou_job[prev_buf].d_tiles = factx.vtcm_d_tiles[prev_buf];
ou_job[prev_buf].hmx_scales = factx.vtcm_hmx_scales_id;
ou_job[prev_buf].n_row_tiles = n_row_tiles;
ou_job[prev_buf].n_col_tiles =
hmx_ceil_div(hex_smin(Bc, nek1 - (kv_blk - 1) * Bc), HMX_FP16_TILE_N_COLS);
ou_job[prev_buf].n_row_tiles_g_br = n_row_tiles_g_br;
ou_job[prev_buf].n_tiles_per_bc = n_tiles_per_bc;
ou_job[prev_buf].DV = DV;
hmx_queue_push(hmx_q, hmx_queue_make_desc(hmx_fa_o_update_worker, &ou_job[prev_buf]));
}
// ---- 4. Pop and run K-prep for next block & push next QK-dot ----
if (kv_blk + 1 < factx.n_kv_blocks) {
const uint32_t next_start = (kv_blk + 1) * Bc;
const uint32_t next_rows = hex_smin(Bc, nek1 - next_start);
@@ -2059,10 +2086,10 @@ int hmx_flash_attn_ext(struct htp_ops_context * octx) {
hmx_queue_push(hmx_q, hmx_queue_make_desc(hmx_fa_qk_dot_worker, &qk_job[next_buf]));
}
// ---- 4. Wait for current block's QK-dot to finish ----
// ---- 5. Wait for current block's QK-dot to finish ----
hmx_queue_pop(hmx_q);
// ---- 5. Phase 2: softmax + build_D ----
// ---- 6. Phase 2: softmax + build_D ----
fa_softmax_args_t sargs;
memset(&sargs, 0, sizeof(sargs));
sargs.factx = &factx;
@@ -2085,23 +2112,6 @@ int hmx_flash_attn_ext(struct htp_ops_context * octx) {
sargs.mask_vtcm_row_stride = factx.mask_buf_row_stride;
sargs.slopes = factx.vtcm_slopes;
// Start HMX O update for block kv_blk - 1 (reads P[1 - buf_idx], V[1 - buf_idx])
if (kv_blk > 0) {
const size_t prev_buf = 1 - buf_idx;
ou_job[prev_buf].o_curr = o_tile_curr;
ou_job[prev_buf].o_prev = o_tile_prev;
ou_job[prev_buf].p_tiles = factx.vtcm_p_tiles[prev_buf];
ou_job[prev_buf].v_tiles = factx.vtcm_v_tiles[prev_buf];
ou_job[prev_buf].d_tiles = factx.vtcm_d_tiles;
ou_job[prev_buf].hmx_scales = factx.vtcm_hmx_scales_id;
ou_job[prev_buf].n_row_tiles = n_row_tiles;
ou_job[prev_buf].n_col_tiles = hmx_ceil_div(hex_smin(Bc, nek1 - (kv_blk - 1) * Bc), HMX_FP16_TILE_N_COLS);
ou_job[prev_buf].n_row_tiles_g_br = n_row_tiles_g_br;
ou_job[prev_buf].n_tiles_per_bc = n_tiles_per_bc;
ou_job[prev_buf].DV = DV;
hmx_queue_push(hmx_q, hmx_queue_make_desc(hmx_fa_o_update_worker, &ou_job[prev_buf]));
}
// Run Softmax on HVX (blocking call)
fa_phase_softmax_and_build_d(&factx, &sargs, n_row_tiles, n_row_tiles_g_br);
@@ -2128,7 +2138,7 @@ int hmx_flash_attn_ext(struct htp_ops_context * octx) {
ou_job[0].o_prev = o_tile_prev;
ou_job[0].p_tiles = factx.vtcm_p_tiles[1 - buf_idx];
ou_job[0].v_tiles = factx.vtcm_v_tiles[1 - buf_idx];
ou_job[0].d_tiles = factx.vtcm_d_tiles;
ou_job[0].d_tiles = factx.vtcm_d_tiles[1 - buf_idx];
ou_job[0].hmx_scales = factx.vtcm_hmx_scales_id;
ou_job[0].n_row_tiles = n_row_tiles;
ou_job[0].n_col_tiles = last_cols;
@@ -2232,7 +2242,7 @@ int hmx_flash_attn_ext(struct htp_ops_context * octx) {
ou_job.o_prev = o_tile_prev;
ou_job.p_tiles = factx.vtcm_p_tiles[0];
ou_job.v_tiles = factx.vtcm_v_tiles[0];
ou_job.d_tiles = factx.vtcm_d_tiles;
ou_job.d_tiles = factx.vtcm_d_tiles[0];
ou_job.hmx_scales = factx.vtcm_hmx_scales_id;
ou_job.n_row_tiles = n_row_tiles;
ou_job.n_col_tiles = n_col_tiles;
+14 -5
View File
@@ -109,7 +109,7 @@ struct hmx_fa_vtcm_layout {
size_t off_v_tiles[2];
size_t off_s_tiles[2];
size_t off_p_tiles[2];
size_t off_d_tiles;
size_t off_d_tiles[2];
size_t off_d_inv_l;
size_t off_m_vec;
size_t off_l_vec;
@@ -125,7 +125,7 @@ struct hmx_fa_vtcm_layout {
size_t q_tile_bytes;
size_t o_tile_bytes;
size_t s_tile_bytes; // S and P tiles (same size)
size_t d_tile_bytes;
size_t d_tile_bytes; // d_tiles[0..1] + d_inv_l, allocated back to back
size_t m_line_bytes; // one mask row
size_t m_buf_slot_bytes; // one dma_cache slot = align_up(Br * m_line_bytes, 4096)
size_t col_vec_bytes;
@@ -149,7 +149,12 @@ static inline void hmx_fa_vtcm_layout_build(struct hmx_fa_vtcm_layout * L,
const size_t k_tile_size = hex_align_up(Bc * DK * sizeof(__fp16), HTP_FA_HMX_TILE_SIZE);
const size_t v_tile_size = hex_align_up(Bc * DV * sizeof(__fp16), HTP_FA_HMX_TILE_SIZE);
const size_t s_tile_size = hex_align_up(g_br * Bc * sizeof(__fp16), HTP_FA_HMX_TILE_SIZE);
const size_t d_tile_size = hex_align_up(g_br * g_br * sizeof(__fp16), HTP_FA_HMX_TILE_SIZE);
// The rescale matrices are diagonal: the HMX kernels only ever load the g_br/32
// tiles that sit on the diagonal, so store just those, packed back to back with
// a stride of one tile. The old [g_br, g_br] square layout allocated g_br/32
// times more than it used, which is also why a second D buffer was unaffordable.
const size_t d_tile_size = (g_br / HMX_FP16_TILE_N_ROWS) * HTP_FA_HMX_TILE_SIZE;
const size_t q_dma_size = hex_align_up(g_br * DK * (is_q_fp32 ? sizeof(float) : sizeof(__fp16)), 128);
const size_t k_dma_size = hex_align_up(Bc * hex_round_up(DK * sizeof(__fp16), 128), 128);
@@ -167,7 +172,8 @@ static inline void hmx_fa_vtcm_layout_build(struct hmx_fa_vtcm_layout * L,
VTCM_LAYOUT_ALLOC(off, off_q_tiles, q_tile_size);
VTCM_LAYOUT_ALLOC(off, off_o_tiles[0], o_tile_size);
VTCM_LAYOUT_ALLOC(off, off_o_tiles[1], o_tile_size);
VTCM_LAYOUT_ALLOC(off, off_d_tiles, d_tile_size);
VTCM_LAYOUT_ALLOC(off, off_d_tiles[0], d_tile_size);
VTCM_LAYOUT_ALLOC_OPTIONAL(off, off_d_tiles[1], d_tile_size, pipeline);
VTCM_LAYOUT_ALLOC(off, off_d_inv_l, d_tile_size);
// Group B & C share start offset (Group B tiles must be 2KB aligned)
@@ -213,7 +219,10 @@ static inline void hmx_fa_vtcm_layout_build(struct hmx_fa_vtcm_layout * L,
L->o_tile_bytes = o_tile_size;
L->col_vec_bytes = col_vec_size;
L->s_tile_bytes = s_tile_size;
L->d_tile_bytes = d_tile_size;
// Measured from the actual offsets rather than assumed to be N * d_tile_size, so
// that inserting a region between them (or adding padding to VTCM_LAYOUT_ALLOC)
// cannot silently leave the tail of the run unzeroed.
L->d_tile_bytes = (L->off_d_inv_l + d_tile_size) - L->off_d_tiles[0];
L->m_line_bytes = m_line_size;
L->m_buf_slot_bytes = m_buf_slot;
L->row_buf_stride = row_vec_size / 128;
+16 -6
View File
@@ -53,6 +53,7 @@
struct htp_rope_context {
int32_t n_dims;
int32_t n_offs;
int32_t mode;
int32_t n_ctx_orig;
int32_t sections[4];
@@ -405,32 +406,40 @@ static inline void hvx_rope_f32_aa(float * restrict dst, const float * restrict
static void inline rope_basic_f32(struct htp_rope_context * rctx, uint8_t * restrict dst, uint8_t * restrict src,
uint32_t nr, uint32_t ne0, const float * restrict theta_cache) {
const uint32_t n_offs = rctx->n_offs; // VLEN-aligned (enforced by supports_op)
#pragma unroll(4)
for (uint32_t i = 0; i < nr; i++) {
float * d = (float *) (dst + i * rctx->dst_row_size_aligned);
float * s = (float *) (src + i * rctx->src0_row_size_aligned);
hvx_rope_f32_aa(d, s, rctx->n_dims, theta_cache);
hvx_rope_f32_aa(d + n_offs, s + n_offs, rctx->n_dims, theta_cache);
// fill the remain channels with data from src tensor
if (rctx->n_dims < ne0) {
hvx_copy_f32_uu((uint8_t *)(d + rctx->n_dims), (uint8_t *)(s + rctx->n_dims), ne0 - rctx->n_dims);
if (n_offs > 0) {
hvx_copy_f32_uu((uint8_t *) d, (uint8_t *) s, n_offs);
}
if (n_offs + rctx->n_dims < ne0) {
hvx_copy_f32_uu((uint8_t *)(d + n_offs + rctx->n_dims), (uint8_t *)(s + n_offs + rctx->n_dims), ne0 - n_offs - rctx->n_dims);
}
}
}
static void inline rope_neox_f32(struct htp_rope_context * rctx, uint8_t * restrict dst, uint8_t * restrict src,
uint32_t nr, uint32_t ne0, const float * restrict theta_cache) {
const uint32_t n_offs = rctx->n_offs; // VLEN-aligned (enforced by supports_op)
#pragma unroll(4)
for (uint32_t i = 0; i < nr; i++) {
float * d = (float *) (dst + i * rctx->dst_row_size_aligned);
float * s = (float *) (src + i * rctx->src0_row_size_aligned);
hvx_rope_neox_f32_aa(d, s, rctx->n_dims, theta_cache);
hvx_rope_neox_f32_aa(d + n_offs, s + n_offs, rctx->n_dims, theta_cache);
// fill the remain channels with data from src tensor
if (rctx->n_dims < ne0) {
hvx_copy_f32_uu((uint8_t *)(d + rctx->n_dims), (uint8_t *)(s + rctx->n_dims), ne0 - rctx->n_dims);
if (n_offs > 0) {
hvx_copy_f32_uu((uint8_t *) d, (uint8_t *) s, n_offs);
}
if (n_offs + rctx->n_dims < ne0) {
hvx_copy_f32_uu((uint8_t *)(d + n_offs + rctx->n_dims), (uint8_t *)(s + n_offs + rctx->n_dims), ne0 - n_offs - rctx->n_dims);
}
}
}
@@ -673,6 +682,7 @@ static int execute_op_rope_f32(struct htp_ops_context * octx) {
rctx.n_dims = ((const int32_t *) op_params)[1];
rctx.mode = ((const int32_t *) op_params)[2];
rctx.n_ctx_orig = ((const int32_t *) op_params)[4];
rctx.n_offs = ((const int32_t *) op_params)[15];
memcpy(&rctx.freq_base, (int32_t *) op_params + 5, sizeof(float));
memcpy(&rctx.freq_scale, (int32_t *) op_params + 6, sizeof(float));
+29 -8
View File
@@ -1409,6 +1409,23 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_p
return res;
}
ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_kv_f16(
ggml_metal_library_t lib,
const ggml_tensor * op) {
assert(op->op == GGML_OP_FLASH_ATTN_EXT);
char base[256];
snprintf(base, 256, "kernel_flash_attn_ext_kv_%s_f16", ggml_type_name(op->src[1]->type));
ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, base);
if (!res.pipeline) {
res = ggml_metal_library_compile_pipeline(lib, base, base, nullptr);
}
return res;
}
ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_blk(
ggml_metal_library_t lib,
const struct ggml_tensor * op,
@@ -1460,7 +1477,10 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext(
bool has_bias,
bool has_scap,
bool has_kvpad,
int32_t nsg) {
int32_t nsg,
bool use_kv_f16,
int32_t ns10,
int32_t ns20) {
assert(op->op == GGML_OP_FLASH_ATTN_EXT);
char base[256];
@@ -1469,15 +1489,14 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext(
const int32_t dk = (int32_t) op->src[1]->ne[0];
const int32_t dv = (int32_t) op->src[2]->ne[0];
const int32_t ns10 = op->src[1]->nb[1]/op->src[1]->nb[0];
const int32_t ns20 = op->src[2]->nb[1]/op->src[2]->nb[0];
const char * type = use_kv_f16 ? "f16" : ggml_type_name(op->src[1]->type);
// do bounds checks for the mask?
const bool bc_mask = op->src[3] && (op->src[3]->ne[1] % 8 != 0);
snprintf(base, 256, "kernel_%s_%s_dk%d_dv%d",
"flash_attn_ext",
ggml_type_name(op->src[1]->type),
type,
dk,
dv);
@@ -1526,7 +1545,10 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_v
bool has_scap,
bool has_kvpad,
int32_t nsg,
int32_t nwg) {
int32_t nwg,
bool use_kv_f16,
int32_t ns10,
int32_t ns20) {
assert(op->op == GGML_OP_FLASH_ATTN_EXT);
char base[256];
@@ -1535,12 +1557,11 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_v
const int32_t dk = (int32_t) op->src[1]->ne[0];
const int32_t dv = (int32_t) op->src[2]->ne[0];
const int32_t ns10 = op->src[1]->nb[1]/op->src[1]->nb[0];
const int32_t ns20 = op->src[2]->nb[1]/op->src[2]->nb[0];
const char * type = use_kv_f16 ? "f16" : ggml_type_name(op->src[1]->type);
snprintf(base, 256, "kernel_%s_%s_dk%d_dv%d",
"flash_attn_ext_vec",
ggml_type_name(op->src[1]->type),
type,
dk,
dv);
+12 -2
View File
@@ -176,6 +176,10 @@ struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_att
bool has_mask,
int32_t ncpsg);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_kv_f16(
ggml_metal_library_t lib,
const struct ggml_tensor * op);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_blk(
ggml_metal_library_t lib,
const struct ggml_tensor * op,
@@ -190,7 +194,10 @@ struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_att
bool has_bias,
bool has_scap,
bool has_kvpad,
int32_t nsg);
int32_t nsg,
bool use_kv_f16,
int32_t ns10,
int32_t ns20);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_vec(
ggml_metal_library_t lib,
@@ -201,7 +208,10 @@ struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_att
bool has_scap,
bool has_kvpad,
int32_t nsg,
int32_t nwg);
int32_t nwg,
bool use_kv_f16,
int32_t ns10,
int32_t ns20);
struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_attn_ext_vec_reduce(
ggml_metal_library_t lib,
+12
View File
@@ -345,6 +345,18 @@ typedef struct {
bool inplace;
} ggml_metal_kargs_rope;
typedef struct {
int32_t ne0;
int32_t ne1;
int32_t ne2;
int32_t ne3;
uint64_t nb0;
uint64_t nb1;
uint64_t nb2;
uint64_t nb3;
int32_t nblocks;
} ggml_metal_kargs_flash_attn_ext_kv_f16;
typedef struct {
int32_t ne11;
int32_t ne_12_2; // assume K and V are same shape
+234 -43
View File
@@ -2801,6 +2801,51 @@ bool ggml_metal_op_flash_attn_ext_use_vec(const ggml_tensor * op) {
return (ne01 < 20) && (ne00 % 32 == 0);
}
// ref: https://github.com/ggml-org/llama.cpp/pull/27390
// dequantize the quantized KV cache to F16 before running the F16 flash attention kernels
static bool ggml_metal_op_flash_attn_ext_use_kv_f16(const ggml_tensor * op) {
assert(op->op == GGML_OP_FLASH_ATTN_EXT);
// depending on compute/bandwidth ratio, dequant to f16 kv is not always beneficial
// ref: https://github.com/ggml-org/llama.cpp/pull/27390#issuecomment-5355152767
// TODO: tune per device
if (op->src[0]->ne[1] < 32) {
return false;
}
switch (op->src[1]->type) {
case GGML_TYPE_Q4_0:
case GGML_TYPE_Q4_1:
case GGML_TYPE_Q5_0:
case GGML_TYPE_Q5_1:
case GGML_TYPE_Q8_0:
return true;
default:
return false;
}
}
// in some models (e.g. MLA-based), V is a view of K (the first ne20 elements of each K row);
// the dequantized V is then a view of the dequantized K and does not need its own dequant or scratch
// - ref: https://github.com/ggml-org/llama.cpp/pull/13435
static bool ggml_metal_op_flash_attn_ext_v_is_view_of_k(const ggml_tensor * op) {
assert(op->op == GGML_OP_FLASH_ATTN_EXT);
const ggml_tensor * K = op->src[1];
const ggml_tensor * V = op->src[2];
return V->view_src && (V->view_src == K || (V->view_src == K->view_src && V->view_offs == K->view_offs));
}
// size of the F16 dequantized K tensor; the dequantized V tensor follows it in the same scratch buffer
static size_t ggml_metal_op_flash_attn_ext_kv_f16_k_size(const ggml_tensor * op) {
assert(op->op == GGML_OP_FLASH_ATTN_EXT);
GGML_TENSOR_LOCALS( int32_t, ne1, op->src[1], ne);
return GGML_PAD(sizeof(ggml_fp16_t)*(size_t) ne10*ne11*ne12*ne13, 16);
}
size_t ggml_metal_op_flash_attn_ext_extra_pad(const ggml_tensor * op) {
assert(op->op == GGML_OP_FLASH_ATTN_EXT);
@@ -2816,6 +2861,18 @@ size_t ggml_metal_op_flash_attn_ext_extra_pad(const ggml_tensor * op) {
size_t res = 0;
const bool has_mask = op->src[3] != nullptr;
const bool use_kv_f16 = ggml_metal_op_flash_attn_ext_use_kv_f16(op);
// when the KV is dequantized to F16, the pad kernel copies the tail chunk from the F16 scratch buffer
// note: when V is a view of K, the dequantized V is read from the dequantized K with K's row stride
const bool v_is_view_of_k = use_kv_f16 && ggml_metal_op_flash_attn_ext_v_is_view_of_k(op);
uint64_t nb11_pad = nb11;
uint64_t nb21_pad = nb21;
if (use_kv_f16) {
nb11_pad = sizeof(ggml_fp16_t)*ne10;
nb21_pad = sizeof(ggml_fp16_t)*(v_is_view_of_k ? ne10 : ne20);
}
// note: the non-vec kernel requires more extra memory, so always reserve for it
GGML_ASSERT(OP_FLASH_ATTN_EXT_NCPSG >= OP_FLASH_ATTN_EXT_VEC_NCPSG);
@@ -2828,8 +2885,8 @@ size_t ggml_metal_op_flash_attn_ext_extra_pad(const ggml_tensor * op) {
if (has_kvpad) {
res += OP_FLASH_ATTN_EXT_VEC_NCPSG*(
nb11*ne12*ne13 +
nb21*ne22*ne23 +
nb11_pad*ne12*ne13 +
nb21_pad*ne22*ne23 +
(has_mask ? ggml_type_size(GGML_TYPE_F16)*ne31*ne32*ne33 : 0));
}
} else {
@@ -2838,8 +2895,8 @@ size_t ggml_metal_op_flash_attn_ext_extra_pad(const ggml_tensor * op) {
if (has_kvpad) {
res += OP_FLASH_ATTN_EXT_NCPSG*(
nb11*ne12*ne13 +
nb21*ne22*ne23 +
nb11_pad*ne12*ne13 +
nb21_pad*ne22*ne23 +
(has_mask ? ggml_type_size(GGML_TYPE_F16)*ne31*ne32*ne33 : 0));
}
}
@@ -2915,6 +2972,29 @@ size_t ggml_metal_op_flash_attn_ext_extra_tmp(const ggml_tensor * op) {
return res;
}
size_t ggml_metal_op_flash_attn_ext_extra_kv_f16(const ggml_tensor * op) {
assert(op->op == GGML_OP_FLASH_ATTN_EXT);
// note: always reserve the temp buffer to avoid graph reallocations
//if (!ggml_metal_op_flash_attn_ext_use_kv_f16(op)) {
// return 0;
//}
GGML_TENSOR_LOCALS( int32_t, ne2, op->src[2], ne);
const size_t k_size = ggml_metal_op_flash_attn_ext_kv_f16_k_size(op);
// when V is a view of K, the dequantized V is a view of the dequantized K
const bool v_is_view_of_k = ggml_metal_op_flash_attn_ext_v_is_view_of_k(op);
if (v_is_view_of_k) {
return k_size;
}
const size_t v_size = GGML_PAD(sizeof(ggml_fp16_t)*(size_t) ne20*ne21*ne22*ne23, 16);
return k_size + v_size;
}
int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
ggml_tensor * op = ctx->node(idx);
@@ -2989,6 +3069,111 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
ggml_metal_buffer_id bid_tmp = bid_blk;
bid_tmp.offs += ggml_metal_op_flash_attn_ext_extra_blk(op);
ggml_metal_buffer_id bid_kv_f16 = bid_tmp;
bid_kv_f16.offs += ggml_metal_op_flash_attn_ext_extra_tmp(op);
const bool use_kv_f16 = ggml_metal_op_flash_attn_ext_use_kv_f16(op);
ggml_metal_buffer_id bid_k = bid_src1;
ggml_metal_buffer_id bid_v = bid_src2;
uint64_t nb10_attn = nb10;
uint64_t nb11_attn = nb11;
uint64_t nb12_attn = nb12;
uint64_t nb13_attn = nb13;
uint64_t nb20_attn = nb20;
uint64_t nb21_attn = nb21;
uint64_t nb22_attn = nb22;
uint64_t nb23_attn = nb23;
if (use_kv_f16) {
assert(ggml_metal_op_flash_attn_ext_extra_kv_f16(op) != 0);
const bool v_is_view_of_k = ggml_metal_op_flash_attn_ext_v_is_view_of_k(op);
const int64_t nblocks1_64 = (ne10/ggml_blck_size(op->src[1]->type))*(int64_t) ne11*ne12*ne13;
GGML_ASSERT(nblocks1_64 <= INT32_MAX);
const int32_t nblocks1 = nblocks1_64;
ggml_metal_buffer_id bid_v_f16 = bid_kv_f16;
bid_v_f16.offs += ggml_metal_op_flash_attn_ext_kv_f16_k_size(op);
auto pipeline0 = ggml_metal_library_get_pipeline_flash_attn_ext_kv_f16(lib, op);
const int nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline0), 256);
// K
ggml_metal_kargs_flash_attn_ext_kv_f16 args_k = {
/*.ne0 =*/ ne10,
/*.ne1 =*/ ne11,
/*.ne2 =*/ ne12,
/*.ne3 =*/ ne13,
/*.nb0 =*/ nb10,
/*.nb1 =*/ nb11,
/*.nb2 =*/ nb12,
/*.nb3 =*/ nb13,
/*.nblocks =*/ nblocks1,
};
ggml_metal_encoder_set_pipeline(enc, pipeline0);
ggml_metal_encoder_set_bytes (enc, &args_k, sizeof(args_k), 0);
ggml_metal_encoder_set_buffer (enc, bid_src1, 1);
ggml_metal_encoder_set_buffer (enc, bid_kv_f16, 2);
ggml_metal_encoder_dispatch_threadgroups(enc, (nblocks1 + nth - 1)/nth, 1, 1, nth, 1, 1);
// V (skip when V is a view of K: the dequantized V is a view of the dequantized K)
if (!v_is_view_of_k) {
const int64_t nblocks2_64 = (ne20/ggml_blck_size(op->src[2]->type))*(int64_t) ne21*ne22*ne23;
GGML_ASSERT(nblocks2_64 <= INT32_MAX);
const int32_t nblocks2 = nblocks2_64;
ggml_metal_kargs_flash_attn_ext_kv_f16 args_v = {
/*.ne0 =*/ ne20,
/*.ne1 =*/ ne21,
/*.ne2 =*/ ne22,
/*.ne3 =*/ ne23,
/*.nb0 =*/ nb20,
/*.nb1 =*/ nb21,
/*.nb2 =*/ nb22,
/*.nb3 =*/ nb23,
/*.nblocks =*/ nblocks2,
};
ggml_metal_encoder_set_pipeline(enc, pipeline0);
ggml_metal_encoder_set_bytes (enc, &args_v, sizeof(args_v), 0);
ggml_metal_encoder_set_buffer (enc, bid_src2, 1);
ggml_metal_encoder_set_buffer (enc, bid_v_f16, 2);
ggml_metal_encoder_dispatch_threadgroups(enc, (nblocks2 + nth - 1)/nth, 1, 1, nth, 1, 1);
}
// the pad and attention kernels read the dequantized KV
ggml_metal_op_concurrency_reset(ctx);
bid_k = bid_kv_f16;
bid_v = v_is_view_of_k ? bid_k : bid_v_f16;
// contiguous F16 layout of the dequantized K
nb10_attn = sizeof(ggml_fp16_t);
nb11_attn = nb10_attn*ne10;
nb12_attn = nb11_attn*ne11;
nb13_attn = nb12_attn*ne12;
// if V is a view of K, the dequantized V is read from the dequantized K with K's strides
if (v_is_view_of_k) {
nb20_attn = nb10_attn;
nb21_attn = nb11_attn;
nb22_attn = nb12_attn;
nb23_attn = nb13_attn;
} else {
// contiguous F16 layout of the dequantized V
nb20_attn = sizeof(ggml_fp16_t);
nb21_attn = nb20_attn*ne20;
nb22_attn = nb21_attn*ne21;
nb23_attn = nb22_attn*ne22;
}
}
if (!ggml_metal_op_flash_attn_ext_use_vec(op)) {
// half8x8 kernel
const int nqptg = OP_FLASH_ATTN_EXT_NQPSG; // queries per threadgroup
@@ -3009,12 +3194,12 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
/*.ne11 =*/ne11,
/*.ne_12_2 =*/ne12,
/*.ne_12_3 =*/ne13,
/*.nb11 =*/nb11,
/*.nb12 =*/nb12,
/*.nb13 =*/nb13,
/*.nb21 =*/nb21,
/*.nb22 =*/nb22,
/*.nb23 =*/nb23,
/*.nb11 =*/nb11_attn,
/*.nb12 =*/nb12_attn,
/*.nb13 =*/nb13_attn,
/*.nb21 =*/nb21_attn,
/*.nb22 =*/nb22_attn,
/*.nb23 =*/nb23_attn,
/*.ne31 =*/ne31,
/*.ne32 =*/ne32,
/*.ne33 =*/ne33,
@@ -3027,8 +3212,8 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
ggml_metal_encoder_set_pipeline(enc, pipeline0);
ggml_metal_encoder_set_bytes (enc, &args0, sizeof(args0), 0);
ggml_metal_encoder_set_buffer (enc, bid_src1, 1);
ggml_metal_encoder_set_buffer (enc, bid_src2, 2);
ggml_metal_encoder_set_buffer (enc, bid_k, 1);
ggml_metal_encoder_set_buffer (enc, bid_v, 2);
ggml_metal_encoder_set_buffer (enc, bid_src3, 3);
ggml_metal_encoder_set_buffer (enc, bid_pad, 4);
@@ -3073,7 +3258,7 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
ggml_metal_op_concurrency_reset(ctx);
}
const int is_q = ggml_is_quantized(op->src[1]->type) ? 1 : 0;
const int is_q = !use_kv_f16 && ggml_is_quantized(op->src[1]->type) ? 1 : 0;
// 2*(2*ncpsg)
// ncpsg soft_max values + ncpsg mask values
@@ -3104,6 +3289,9 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
const size_t smem = FATTN_SMEM(nsg);
const int32_t ns10 = nb11_attn/nb10_attn;
const int32_t ns20 = nb21_attn/nb20_attn;
ggml_metal_kargs_flash_attn_ext args = {
/*.ne01 =*/ ne01,
/*.ne02 =*/ ne02,
@@ -3114,14 +3302,14 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
/*.ne11 =*/ ne11,
/*.ne_12_2 =*/ ne12,
/*.ne_12_3 =*/ ne13,
/*.ns10 =*/ int32_t(nb11/nb10),
/*.nb11 =*/ nb11,
/*.nb12 =*/ nb12,
/*.nb13 =*/ nb13,
/*.ns20 =*/ int32_t(nb21/nb20),
/*.nb21 =*/ nb21,
/*.nb22 =*/ nb22,
/*.nb23 =*/ nb23,
/*.ns10 =*/ ns10,
/*.nb11 =*/ nb11_attn,
/*.nb12 =*/ nb12_attn,
/*.nb13 =*/ nb13_attn,
/*.ns20 =*/ ns20,
/*.nb21 =*/ nb21_attn,
/*.nb22 =*/ nb22_attn,
/*.nb23 =*/ nb23_attn,
/*.ne31 =*/ ne31,
/*.ne32 =*/ ne32,
/*.ne33 =*/ ne33,
@@ -3139,13 +3327,13 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
/*.logit_softcap =*/ logit_softcap,
};
auto pipeline = ggml_metal_library_get_pipeline_flash_attn_ext(lib, op, has_mask, has_sinks, has_bias, has_scap, has_kvpad, nsg);
auto pipeline = ggml_metal_library_get_pipeline_flash_attn_ext(lib, op, has_mask, has_sinks, has_bias, has_scap, has_kvpad, nsg, use_kv_f16, ns10, ns20);
ggml_metal_encoder_set_pipeline(enc, pipeline);
ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0);
ggml_metal_encoder_set_buffer (enc, bid_src0, 1);
ggml_metal_encoder_set_buffer (enc, bid_src1, 2);
ggml_metal_encoder_set_buffer (enc, bid_src2, 3);
ggml_metal_encoder_set_buffer (enc, bid_k, 2);
ggml_metal_encoder_set_buffer (enc, bid_v, 3);
ggml_metal_encoder_set_buffer (enc, bid_src3, 4);
ggml_metal_encoder_set_buffer (enc, bid_src4, 5);
ggml_metal_encoder_set_buffer (enc, bid_pad, 6);
@@ -3177,12 +3365,12 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
/*.ne11 =*/ne11,
/*.ne_12_2 =*/ne12,
/*.ne_12_3 =*/ne13,
/*.nb11 =*/nb11,
/*.nb12 =*/nb12,
/*.nb13 =*/nb13,
/*.nb21 =*/nb21,
/*.nb22 =*/nb22,
/*.nb23 =*/nb23,
/*.nb11 =*/nb11_attn,
/*.nb12 =*/nb12_attn,
/*.nb13 =*/nb13_attn,
/*.nb21 =*/nb21_attn,
/*.nb22 =*/nb22_attn,
/*.nb23 =*/nb23_attn,
/*.ne31 =*/ne31,
/*.ne32 =*/ne32,
/*.ne33 =*/ne33,
@@ -3195,8 +3383,8 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
ggml_metal_encoder_set_pipeline(enc, pipeline0);
ggml_metal_encoder_set_bytes (enc, &args0, sizeof(args0), 0);
ggml_metal_encoder_set_buffer (enc, bid_src1, 1);
ggml_metal_encoder_set_buffer (enc, bid_src2, 2);
ggml_metal_encoder_set_buffer (enc, bid_k, 1);
ggml_metal_encoder_set_buffer (enc, bid_v, 2);
ggml_metal_encoder_set_buffer (enc, bid_src3, 3);
ggml_metal_encoder_set_buffer (enc, bid_pad, 4);
@@ -3242,6 +3430,9 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
}
}
const int32_t ns10 = nb11_attn/nb10_attn;
const int32_t ns20 = nb21_attn/nb20_attn;
ggml_metal_kargs_flash_attn_ext_vec args = {
/*.ne01 =*/ ne01,
/*.ne02 =*/ ne02,
@@ -3252,14 +3443,14 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
/*.ne11 =*/ ne11,
/*.ne_12_2 =*/ ne12,
/*.ne_12_3 =*/ ne13,
/*.ns10 =*/ int32_t(nb11/nb10),
/*.nb11 =*/ nb11,
/*.nb12 =*/ nb12,
/*.nb13 =*/ nb13,
/*.ns20 =*/ int32_t(nb21/nb20),
/*.nb21 =*/ nb21,
/*.nb22 =*/ nb22,
/*.nb23 =*/ nb23,
/*.ns10 =*/ ns10,
/*.nb11 =*/ nb11_attn,
/*.nb12 =*/ nb12_attn,
/*.nb13 =*/ nb13_attn,
/*.ns20 =*/ ns20,
/*.nb21 =*/ nb21_attn,
/*.nb22 =*/ nb22_attn,
/*.nb23 =*/ nb23_attn,
/*.ne31 =*/ ne31,
/*.ne32 =*/ ne32,
/*.ne33 =*/ ne33,
@@ -3277,15 +3468,15 @@ int ggml_metal_op_flash_attn_ext(ggml_metal_op_t ctx, int idx) {
/*.logit_softcap =*/ logit_softcap,
};
auto pipeline = ggml_metal_library_get_pipeline_flash_attn_ext_vec(lib, op, has_mask, has_sinks, has_bias, has_scap, has_kvpad, nsg, nwg);
auto pipeline = ggml_metal_library_get_pipeline_flash_attn_ext_vec(lib, op, has_mask, has_sinks, has_bias, has_scap, has_kvpad, nsg, nwg, use_kv_f16, ns10, ns20);
GGML_ASSERT(nsg*32 <= ggml_metal_pipeline_max_theads_per_threadgroup(pipeline));
ggml_metal_encoder_set_pipeline(enc, pipeline);
ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), 0);
ggml_metal_encoder_set_buffer (enc, bid_src0, 1);
ggml_metal_encoder_set_buffer (enc, bid_src1, 2);
ggml_metal_encoder_set_buffer (enc, bid_src2, 3);
ggml_metal_encoder_set_buffer (enc, bid_k, 2);
ggml_metal_encoder_set_buffer (enc, bid_v, 3);
ggml_metal_encoder_set_buffer (enc, bid_src3, 4);
ggml_metal_encoder_set_buffer (enc, bid_src4, 5);
+1
View File
@@ -42,6 +42,7 @@ bool ggml_metal_op_flash_attn_ext_use_vec(const struct ggml_tensor * op);
size_t ggml_metal_op_flash_attn_ext_extra_pad(const struct ggml_tensor * op);
size_t ggml_metal_op_flash_attn_ext_extra_blk(const struct ggml_tensor * op);
size_t ggml_metal_op_flash_attn_ext_extra_tmp(const struct ggml_tensor * op);
size_t ggml_metal_op_flash_attn_ext_extra_kv_f16(const struct ggml_tensor * op);
int ggml_metal_op_concat (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_repeat (ggml_metal_op_t ctx, int idx);
+1
View File
@@ -225,6 +225,7 @@ static size_t ggml_backend_metal_buffer_type_get_alloc_size(ggml_backend_buffer_
res += ggml_metal_op_flash_attn_ext_extra_pad(tensor);
res += ggml_metal_op_flash_attn_ext_extra_blk(tensor);
res += ggml_metal_op_flash_attn_ext_extra_tmp(tensor);
res += ggml_metal_op_flash_attn_ext_extra_kv_f16(tensor);
} break;
case GGML_OP_CUMSUM:
case GGML_OP_ARGSORT:
+58 -4
View File
@@ -6318,6 +6318,53 @@ template [[host_name("kernel_fwht_f32_128")]] kernel kernel_fwht_t kernel_fwht_f
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>;
// dequantize a quantized KV cache tensor to contiguous F16 before running the F16 flash attention kernels
// - one thread per block; dispatched separately for K and V
// - ref: https://github.com/ggml-org/llama.cpp/pull/27390
template <
typename block_t,
short QK,
void (*deq_t4x4)(device const block_t *, short, thread float4x4 &)>
kernel void kernel_flash_attn_ext_kv_f16(
constant ggml_metal_kargs_flash_attn_ext_kv_f16 & args,
device const char * x,
device half * x_dst,
uint gid [[thread_position_in_grid]]) {
if (gid >= (uint) args.nblocks) {
return;
}
const uint nb = args.ne0/QK;
const uint i0 = gid%nb;
uint ib = gid/nb;
const uint i1 = ib%args.ne1;
ib /= args.ne1;
const uint i2 = ib%args.ne2;
const uint i3 = ib/args.ne2;
const uint64_t offs = i0*args.nb0 + i1*args.nb1 + i2*args.nb2 + i3*args.nb3;
device const block_t * src = (device const block_t *) (x + offs);
device half4 * dst = (device half4 *) x_dst + (QK/4)*gid;
for (short i = 0; i < QK/16; ++i) {
float4x4 reg;
deq_t4x4(src, i, reg);
dst[4*i + 0] = (half4) reg[0];
dst[4*i + 1] = (half4) reg[1];
dst[4*i + 2] = (half4) reg[2];
dst[4*i + 3] = (half4) reg[3];
}
}
typedef decltype(kernel_flash_attn_ext_kv_f16<block_q8_0, 32, dequantize_q8_0>) kernel_flash_attn_ext_kv_f16_t;
template [[host_name("kernel_flash_attn_ext_kv_q4_0_f16")]] kernel kernel_flash_attn_ext_kv_f16_t kernel_flash_attn_ext_kv_f16<block_q4_0, 32, dequantize_q4_0>;
template [[host_name("kernel_flash_attn_ext_kv_q4_1_f16")]] kernel kernel_flash_attn_ext_kv_f16_t kernel_flash_attn_ext_kv_f16<block_q4_1, 32, dequantize_q4_1>;
template [[host_name("kernel_flash_attn_ext_kv_q5_0_f16")]] kernel kernel_flash_attn_ext_kv_f16_t kernel_flash_attn_ext_kv_f16<block_q5_0, 32, dequantize_q5_0>;
template [[host_name("kernel_flash_attn_ext_kv_q5_1_f16")]] kernel kernel_flash_attn_ext_kv_f16_t kernel_flash_attn_ext_kv_f16<block_q5_1, 32, dequantize_q5_1>;
template [[host_name("kernel_flash_attn_ext_kv_q8_0_f16")]] kernel kernel_flash_attn_ext_kv_f16_t kernel_flash_attn_ext_kv_f16<block_q8_0, 32, dequantize_q8_0>;
constant bool FC_flash_attn_ext_pad_has_mask [[function_constant(FC_FLASH_ATTN_EXT_PAD + 0)]];
constant int32_t FC_flash_attn_ext_pad_ncpsg [[function_constant(FC_FLASH_ATTN_EXT_PAD + 25)]];
@@ -10318,9 +10365,12 @@ kernel void kernel_mul_mm(
auto tB = tensor(ptrB, dextents<int32_t, 2>(K, N), array<int, 2>({1, strideB}));
// Configure matmul operation
// note: K is dynamic_extent (clamped to the valid range in PHASE 2), since a static
// N_MM_NK_TOTAL K tile would read src1 out of bounds when K % N_MM_NK_TOTAL != 0
// ref: https://github.com/ggml-org/llama.cpp/pull/27064
mpp::tensor_ops::matmul2d<
mpp::tensor_ops::matmul2d_descriptor(
NRB, NRA, N_MM_NK_TOTAL, false, true, true,
NRB, NRA, static_cast<int>(dynamic_extent), false, true, true,
mpp::tensor_ops::matmul2d_descriptor::mode::multiply_accumulate),
execution_simdgroups<N_MM_SIMD_GROUP_X * N_MM_SIMD_GROUP_Y>> mm;
@@ -10372,10 +10422,14 @@ kernel void kernel_mul_mm(
threadgroup_barrier(mem_flags::mem_threadgroup);
// === PHASE 2: Tensor matmul ===
auto mA = tA.slice(0, 0);
auto mB = tB.slice(loop_k, rb);
// Clamp the K extent of both operand tensors to the remaining valid K range so
// the dynamic-K op never reads past the K extent of src1 (or the staged A tile).
const int kExt = min(N_MM_NK_TOTAL, K - loop_k);
mm.run(mB, mA, cT);
auto tAv = tensor(sa, dextents<int32_t, 2>(kExt, NRA), array<int, 2>({1, N_MM_NK_TOTAL}));
auto tBv = tensor(ptrB + loop_k + rb * strideB, dextents<int32_t, 2>(kExt, N - rb), array<int, 2>({1, strideB}));
mm.run(tBv, tAv, cT);
threadgroup_barrier(mem_flags::mem_threadgroup);
}
+1
View File
@@ -202,6 +202,7 @@ set(GGML_OPENCL_KERNELS
sqr
sqrt
ssm_conv
ssm_scan
gated_delta_net
sub
sum_rows
+233 -16
View File
@@ -582,6 +582,8 @@ struct ggml_backend_opencl_context {
bool adreno_use_bin_kernels;
get_adreno_bin_kernel_func_t get_adreno_bin_kernel_func = nullptr;
ggml_cl_compiler_version adreno_cl_compiler_version;
// The q6_K flat mul_mat codegen workarounds are needed by old E031 compilers only.
bool q6_k_flat_old_compiler;
std::string kernel_compile_opts; // cached for lazy-compiled kernels.
@@ -866,6 +868,9 @@ struct ggml_backend_opencl_context {
// [size_idx][kda][tgpp] where size_idx: 0=S_V=16, 1=32, 2=64, 3=128; kda: 0 or 1.
// tgpp 0 = TG variant (COLS_PER_LANE_GROUP=1), tgpp 1 = prefill variant (COLS_PER_LANE_GROUP=4).
cl_kernel kernel_gated_delta_net_f32[4][2][2] = {};
cl_kernel kernel_ssm_scan_f32_mamba2_d128 = nullptr;
cl_kernel kernel_ssm_scan_f32_mamba2_d256 = nullptr;
cl_kernel kernel_timestep_embedding;
cl_kernel kernel_gemv_moe_q4_0_f32_ns, kernel_gemm_moe_q4_0_f32_ns, kernel_gemm_moe_q4_0_f32_ns_bin;
cl_kernel kernel_gemm_moe_q8_0_f32_ns;
@@ -892,6 +897,7 @@ struct ggml_backend_opencl_context {
cl_kernel kernel_gemm_moe_q4_0_q8_1_dp4a = nullptr; // dp4a (int8) q4_0 MoE prefill GEMM
cl_kernel kernel_moe_reorder_b;
cl_kernel kernel_moe_histogram, kernel_moe_scan, kernel_moe_fill, kernel_moe_scatter;
cl_kernel kernel_moe_scatter_stable = nullptr; // deterministic slot assignment
cl_kernel kernel_moe_combine_f32 = nullptr; // fused router-weight mul + cross-expert sum
cl_kernel kernel_mul_mv_id_q4_0_f32_8x_flat;
cl_kernel kernel_mul_mv_id_q8_0_f32, kernel_mul_mv_id_q8_0_f32_flat;
@@ -1927,8 +1933,14 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx) {
#else
const std::string kernel_src = read_file("mul_mv_q6_k_f32_flat.cl");
#endif
// The codegen workarounds in this kernel are a measured 13-20% loss on
// compilers that do not need them, so only the affected ones build them;
// everyone else gets the original source.
const std::string q6k_opts = backend_ctx->q6_k_flat_old_compiler
? compile_opts + " -DADRENO_OLD_COMPILER=1"
: compile_opts;
cl_program prog =
build_program_from_source(backend_ctx, kernel_src.c_str(), compile_opts);
build_program_from_source(backend_ctx, kernel_src.c_str(), q6k_opts);
CL_CHECK((backend_ctx->kernel_mul_mv_q6_K_f32_flat = clCreateKernel(prog, "kernel_mul_mv_q6_K_f32_flat", &err), err));
CL_CHECK(clReleaseProgram(prog));
@@ -3154,6 +3166,24 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx) {
GGML_LOG_CONT(".");
}
// ssm_scan (Mamba-2 fused per-token recurrent step; d_state in {128, 256})
{
#ifdef GGML_OPENCL_EMBED_KERNELS
const std::string kernel_src {
#include "ssm_scan.cl.h"
};
#else
const std::string kernel_src = read_file("ssm_scan.cl");
#endif
cl_program prog =
build_program_from_source(backend_ctx, kernel_src.c_str(), compile_opts);
CL_CHECK((backend_ctx->kernel_ssm_scan_f32_mamba2_d128 = clCreateKernel(prog, "kernel_ssm_scan_f32_mamba2_d128", &err), err));
CL_CHECK((backend_ctx->kernel_ssm_scan_f32_mamba2_d256 = clCreateKernel(prog, "kernel_ssm_scan_f32_mamba2_d256", &err), err));
CL_CHECK(clReleaseProgram(prog));
GGML_LOG_CONT(".");
}
// gated_delta_net: one kernel per (S_V, KDA, tgpp) triple.
{
#ifdef GGML_OPENCL_EMBED_KERNELS
@@ -4442,6 +4472,7 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx) {
CL_CHECK((backend_ctx->kernel_moe_scan = clCreateKernel(prog, "kernel_moe_scan", &err), err));
CL_CHECK((backend_ctx->kernel_moe_fill = clCreateKernel(prog, "kernel_moe_fill", &err), err));
CL_CHECK((backend_ctx->kernel_moe_scatter = clCreateKernel(prog, "kernel_moe_scatter", &err), err));
CL_CHECK((backend_ctx->kernel_moe_scatter_stable = clCreateKernel(prog, "kernel_moe_scatter_stable", &err), err));
CL_CHECK(clReleaseProgram(prog));
GGML_LOG_CONT(".");
}
@@ -5894,6 +5925,16 @@ static ggml_backend_opencl_context * ggml_cl_init(ggml_backend_dev_t dev) {
(backend_ctx->adreno_cl_compiler_version.type == E031 && backend_ctx->adreno_cl_compiler_version.major >= 47) ||
(backend_ctx->adreno_cl_compiler_version.type == DX && backend_ctx->adreno_cl_compiler_version.major >= 17);
// The q6_K flat mul_mat miscompile is a defect of the older E031 compilers, not a
// property of any GPU generation: it reproduces on E031.38 (Adreno 642L) and E031.41
// (Adreno 740) and is fixed by E031.45 (Adreno 619). Gate on the compiler so parts
// that do not need the workarounds do not pay for them. The explicit type check is
// required: newer_than_or_same() is false for every non-E031 compiler, so negating it
// alone would enable the workarounds on E17/DX.
backend_ctx->q6_k_flat_old_compiler =
backend_ctx->adreno_cl_compiler_version.type == E031 &&
!backend_ctx->adreno_cl_compiler_version.newer_than_or_same(E031, 45, 0, 0);
size_t ext_str_size;
clGetDeviceInfo(device, CL_DEVICE_EXTENSIONS, 0, NULL, &ext_str_size);
char *ext_buffer = (char *)alloca(ext_str_size + 1);
@@ -7301,6 +7342,23 @@ static bool ggml_opencl_supports_op(ggml_backend_dev_t dev, const struct ggml_te
(op->src[0]->type == GGML_TYPE_F16 && op->src[1]->type == GGML_TYPE_F32 && op->type == GGML_TYPE_F32);
case GGML_OP_SSM_CONV:
return (op->src[0]->type == GGML_TYPE_F32 && op->src[1]->type == GGML_TYPE_F32 && op->type == GGML_TYPE_F32);
case GGML_OP_SSM_SCAN: {
// Mamba-2 fused per-token scan. Requires src3->ne[0] == 1 (scalar
// A per head); d_state in {128, 256}; all sources f32. Falls back
// to CPU otherwise (incl. Mamba-1 element-wise A).
for (int i = 0; i < 6; ++i) {
if (op->src[i]->type != GGML_TYPE_F32) {
return false;
}
}
if (op->type != GGML_TYPE_F32) {
return false;
}
const int K = ggml_get_op_params_i32(op, 0);
const int d_state = (int) op->src[0]->ne[0];
const bool is_mamba2 = (op->src[3]->ne[0] == 1);
return is_mamba2 && (d_state == 128 || d_state == 256) && (K == 1);
}
case GGML_OP_GATED_DELTA_NET:
{
// Match the Vulkan backend: only F32 -> F32, S_v in {16, 32, 64, 128}.
@@ -7376,9 +7434,6 @@ static bool ggml_opencl_supports_op(ggml_backend_dev_t dev, const struct ggml_te
case GGML_OP_DIAG_MASK_INF:
return op->ne[3] == 1;
case GGML_OP_ROPE: {
if (((const int32_t *) op->op_params)[15] != 0) {
return false; // FIXME: support ggml_rope_set_offset
}
const int mode = ((const int32_t *) op->op_params)[2];
const bool is_mrope = mode & GGML_ROPE_TYPE_MROPE;
const bool is_vision = mode == GGML_ROPE_TYPE_VISION;
@@ -7456,6 +7511,7 @@ static bool ggml_opencl_supports_op(ggml_backend_dev_t dev, const struct ggml_te
v->type == GGML_TYPE_F16 && op->type == GGML_TYPE_F16;
const bool is_f32_f16 = q->type == GGML_TYPE_F32 && k->type == GGML_TYPE_F16 &&
v->type == GGML_TYPE_F16 && op->type == GGML_TYPE_F32;
const bool is_f32_q8_0 = q->type == GGML_TYPE_F32 && k->type == GGML_TYPE_Q8_0 &&
v->type == GGML_TYPE_Q8_0 && op->type == GGML_TYPE_F32 &&
dk % 32 == 0 && dv % 32 == 0;
@@ -7463,6 +7519,21 @@ static bool ggml_opencl_supports_op(ggml_backend_dev_t dev, const struct ggml_te
v->type == GGML_TYPE_Q4_0 && op->type == GGML_TYPE_F32 &&
dk % 32 == 0 && dv % 32 == 0;
// A7X (Adreno 740, compiler E031.41) SIGSEGVs inside clBuildProgram
// building the flash_attn programs whose KV path is mixed-type or
// dequantized — f32_f16, q8_0, q4_0 (reproduced at DK=40 and DK=64; it
// is DK-independent). It is a driver crash, not codegen-wrong-output, so
// it cannot be caught in-process (fatal=false only handles clean compile
// errors). The uniform f16_f16 / f32_f32 programs compile fine on this
// compiler, so decline only the KV-convert variants; ggml then runs
// those (f16-KV / quant-KV) attention layers on the CPU backend.
// Negative compiler carve-out, same idiom as the Intel DK=512 decline
// below and the X1E driver-quirk guards.
if (backend_ctx && backend_ctx->adreno_gen == ADRENO_GPU_GEN::A7X &&
(is_f32_f16 || is_f32_q8_0 || is_f32_q4_0)) {
return false;
}
// Asymmetric KV: host-dequants both sides to F32, uses f32 kernel.
auto is_kv_type_ok = [](ggml_type t) {
return t == GGML_TYPE_F16 || t == GGML_TYPE_F32 ||
@@ -12260,6 +12331,103 @@ static void ggml_cl_mean(ggml_backend_t backend, const ggml_tensor * src0, const
backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size, dst);
}
static void ggml_cl_ssm_scan(ggml_backend_t backend, ggml_tensor * dst) {
const ggml_tensor * src0 = dst->src[0]; // s
const ggml_tensor * src1 = dst->src[1]; // x
const ggml_tensor * src2 = dst->src[2]; // dt
const ggml_tensor * src3 = dst->src[3]; // A
const ggml_tensor * src4 = dst->src[4]; // B
const ggml_tensor * src5 = dst->src[5]; // C
const ggml_tensor * src6 = dst->src[6]; // ids
GGML_ASSERT(src0 && src1 && src2 && src3 && src4 && src5 && src6 && dst);
ggml_backend_opencl_context * backend_ctx = (ggml_backend_opencl_context *) backend->context;
ggml_tensor_extra_cl * e0 = (ggml_tensor_extra_cl *) src0->extra;
ggml_tensor_extra_cl * e1 = (ggml_tensor_extra_cl *) src1->extra;
ggml_tensor_extra_cl * e2 = (ggml_tensor_extra_cl *) src2->extra;
ggml_tensor_extra_cl * e3 = (ggml_tensor_extra_cl *) src3->extra;
ggml_tensor_extra_cl * e4 = (ggml_tensor_extra_cl *) src4->extra;
ggml_tensor_extra_cl * e5 = (ggml_tensor_extra_cl *) src5->extra;
ggml_tensor_extra_cl * e6 = (ggml_tensor_extra_cl *) src6->extra;
ggml_tensor_extra_cl * ed = (ggml_tensor_extra_cl *) dst->extra;
cl_ulong o0 = e0->offset + src0->view_offs;
cl_ulong o1 = e1->offset + src1->view_offs;
cl_ulong o2 = e2->offset + src2->view_offs;
cl_ulong o3 = e3->offset + src3->view_offs;
cl_ulong o4 = e4->offset + src4->view_offs;
cl_ulong o5 = e5->offset + src5->view_offs;
cl_ulong o6 = e6->offset + src6->view_offs;
cl_ulong od = ed->offset + dst->view_offs;
const int d_state = (int) src0->ne[0];
const int head_dim = (int) src0->ne[1];
const int n_head = (int) src1->ne[1];
const int n_group = (int) src4->ne[1];
const int n_tokens = (int) src1->ne[2];
const int n_seqs = (int) src1->ne[3];
// Mirror CPU ref: s_off = ggml_nelements(src1) * sizeof(float)
const cl_ulong s_off_bytes = (cl_ulong) ggml_nelements(src1) * sizeof(float);
cl_kernel kernel = (d_state == 128)
? backend_ctx->kernel_ssm_scan_f32_mamba2_d128
: backend_ctx->kernel_ssm_scan_f32_mamba2_d256;
GGML_ASSERT(kernel != nullptr);
cl_ulong s0_nb2 = src0->nb[2];
cl_ulong s0_nb3 = src0->nb[3];
cl_ulong x_nb2 = src1->nb[2];
cl_ulong x_nb3 = src1->nb[3];
cl_ulong dt_nb1 = src2->nb[1];
cl_ulong dt_nb2 = src2->nb[2];
cl_ulong A_nb1 = src3->nb[1];
cl_ulong B_nb2 = src4->nb[2];
cl_ulong B_nb3 = src4->nb[3];
cl_ulong C_nb2 = src5->nb[2];
cl_ulong C_nb3 = src5->nb[3];
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &e0->data_device));
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_ulong), &o0));
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &e1->data_device));
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_ulong), &o1));
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &e2->data_device));
CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_ulong), &o2));
CL_CHECK(clSetKernelArg(kernel, 6, sizeof(cl_mem), &e3->data_device));
CL_CHECK(clSetKernelArg(kernel, 7, sizeof(cl_ulong), &o3));
CL_CHECK(clSetKernelArg(kernel, 8, sizeof(cl_mem), &e4->data_device));
CL_CHECK(clSetKernelArg(kernel, 9, sizeof(cl_ulong), &o4));
CL_CHECK(clSetKernelArg(kernel, 10, sizeof(cl_mem), &e5->data_device));
CL_CHECK(clSetKernelArg(kernel, 11, sizeof(cl_ulong), &o5));
CL_CHECK(clSetKernelArg(kernel, 12, sizeof(cl_mem), &e6->data_device));
CL_CHECK(clSetKernelArg(kernel, 13, sizeof(cl_ulong), &o6));
CL_CHECK(clSetKernelArg(kernel, 14, sizeof(cl_mem), &ed->data_device));
CL_CHECK(clSetKernelArg(kernel, 15, sizeof(cl_ulong), &od));
CL_CHECK(clSetKernelArg(kernel, 16, sizeof(cl_ulong), &s0_nb2));
CL_CHECK(clSetKernelArg(kernel, 17, sizeof(cl_ulong), &s0_nb3));
CL_CHECK(clSetKernelArg(kernel, 18, sizeof(cl_ulong), &x_nb2));
CL_CHECK(clSetKernelArg(kernel, 19, sizeof(cl_ulong), &x_nb3));
CL_CHECK(clSetKernelArg(kernel, 20, sizeof(cl_ulong), &dt_nb1));
CL_CHECK(clSetKernelArg(kernel, 21, sizeof(cl_ulong), &dt_nb2));
CL_CHECK(clSetKernelArg(kernel, 22, sizeof(cl_ulong), &A_nb1));
CL_CHECK(clSetKernelArg(kernel, 23, sizeof(cl_ulong), &B_nb2));
CL_CHECK(clSetKernelArg(kernel, 24, sizeof(cl_ulong), &B_nb3));
CL_CHECK(clSetKernelArg(kernel, 25, sizeof(cl_ulong), &C_nb2));
CL_CHECK(clSetKernelArg(kernel, 26, sizeof(cl_ulong), &C_nb3));
CL_CHECK(clSetKernelArg(kernel, 27, sizeof(cl_ulong), &s_off_bytes));
CL_CHECK(clSetKernelArg(kernel, 28, sizeof(int), &head_dim));
CL_CHECK(clSetKernelArg(kernel, 29, sizeof(int), &n_head));
CL_CHECK(clSetKernelArg(kernel, 30, sizeof(int), &n_group));
CL_CHECK(clSetKernelArg(kernel, 31, sizeof(int), &n_tokens));
size_t global_work_size[] = { (size_t)n_head * head_dim * 64, (size_t)n_seqs, 1 };
size_t local_work_size[] = { 64, 1, 1 };
backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size, dst);
}
static void ggml_cl_ssm_conv(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
GGML_ASSERT(src0);
GGML_ASSERT(src0->extra);
@@ -12693,7 +12861,10 @@ static void ggml_cl_norm(ggml_backend_t backend, const ggml_tensor * src0, const
GGML_TENSOR_LOCALS(int, ne0, src0, ne);
GGML_TENSOR_LOCALS(cl_ulong, nb0, src0, nb);
const int nth = MIN(64, ne00);
int nth = 1;
while (nth < ne00 && nth < 64) {
nth *= 2;
}
cl_kernel kernel = backend_ctx->kernel_norm;
@@ -20443,6 +20614,12 @@ static void ggml_cl_mul_mat(ggml_backend_t backend, const ggml_tensor * src0, co
CL_CHECK(clSetKernelArg(kernel, 14, sizeof(int), &ne1));
CL_CHECK(clSetKernelArg(kernel, 15, sizeof(int), &r2));
CL_CHECK(clSetKernelArg(kernel, 16, sizeof(int), &r3));
// The optimizer-barrier arg exists only in the ADRENO_OLD_COMPILER build of
// this kernel; conformant compilers get the original 17-arg signature.
if (backend_ctx->q6_k_flat_old_compiler) {
cl_uchar q6k_mask = 0xFF; // never 0xFE in prod; see the kernel note
CL_CHECK(clSetKernelArg(kernel, 17, sizeof(cl_uchar), &q6k_mask));
}
#else
kernel = backend_ctx->kernel_mul_mv_q6_K_f32;
@@ -20728,18 +20905,42 @@ static void moe_router_reoerder(ggml_backend_t backend, const ggml_tensor * src,
size_t fill_local_size[] = {64, 1, 1};
backend_ctx->enqueue_ndrange_kernel(kernel, 3, fill_global_size, fill_local_size, src);
// Scatter
kernel = backend_ctx->kernel_moe_scatter;
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &original_router_buf));
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &post_router_buf));
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &emap_buf));
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_mem), &tile_offset_buf));
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &slot_counter_buf));
CL_CHECK(clSetKernelArg(kernel, 5, sizeof(int), &ne21));
CL_CHECK(clSetKernelArg(kernel, 6, sizeof(int), &ne20));
CL_CHECK(clSetKernelArg(kernel, 7, sizeof(int), &ne02));
// Scatter. The deterministic variant is the default: kernel_moe_scatter derives
// each token's slot from an atomic counter, so the packing inside an expert - and
// with it the output of the ragged prefill GEMM - changes from run to run. Set
// GGML_OPENCL_MOE_STABLE_SCATTER=0 to restore the atomic version.
static const bool stable_scatter = []{
const char * e = getenv("GGML_OPENCL_MOE_STABLE_SCATTER");
return !e || e[0] == '\0' || e[0] != '0';
}();
backend_ctx->enqueue_ndrange_kernel(kernel, 3, histogram_global_size, histogram_local_size, src);
if (stable_scatter) {
kernel = backend_ctx->kernel_moe_scatter_stable;
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &original_router_buf));
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &post_router_buf));
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &emap_buf));
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_mem), &tile_offset_buf));
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(int), &ne21));
CL_CHECK(clSetKernelArg(kernel, 5, sizeof(int), &ne20));
CL_CHECK(clSetKernelArg(kernel, 6, sizeof(int), &ne02));
// one workgroup (one wave) per expert; each ranks its own tokens
size_t scatter_global_size[] = {64, (size_t)ne02};
size_t scatter_local_size[] = {64, 1};
backend_ctx->enqueue_ndrange_kernel(kernel, 2, scatter_global_size, scatter_local_size, src);
} else {
kernel = backend_ctx->kernel_moe_scatter;
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &original_router_buf));
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &post_router_buf));
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &emap_buf));
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_mem), &tile_offset_buf));
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &slot_counter_buf));
CL_CHECK(clSetKernelArg(kernel, 5, sizeof(int), &ne21));
CL_CHECK(clSetKernelArg(kernel, 6, sizeof(int), &ne20));
CL_CHECK(clSetKernelArg(kernel, 7, sizeof(int), &ne02));
backend_ctx->enqueue_ndrange_kernel(kernel, 3, histogram_global_size, histogram_local_size, src);
}
// [MOE_TILES] env-gated padding probe: read back total_tiles (= Sum_e
// ceil(k_e/n_tile_size)) and compare to the ideal tile count for the real
@@ -23706,6 +23907,7 @@ static void ggml_cl_rope(ggml_backend_t backend, const ggml_tensor * src0, const
const int n_dims = ((int *) dst->op_params)[1];
const int mode = ((int *) dst->op_params)[2];
const int n_ctx_orig = ((int32_t *) dst->op_params)[4];
const int n_offs = ((int32_t *) dst->op_params)[15];
float freq_base;
float freq_scale;
@@ -23734,6 +23936,7 @@ static void ggml_cl_rope(ggml_backend_t backend, const ggml_tensor * src0, const
if (is_vision) {
GGML_ASSERT(n_dims == ne00/2);
GGML_ASSERT(n_offs == 0); // offset not supported for vision, as the rotated pairs span the whole row
}
cl_kernel kernel;
@@ -23825,6 +24028,12 @@ static void ggml_cl_rope(ggml_backend_t backend, const ggml_tensor * src0, const
if (is_mrope && !is_vision) {
CL_CHECK(clSetKernelArg(kernel, 34, sizeof(int), &is_imrope));
}
// norm and neox have n_offs after beta_slow, mrope has it after is_imrope
if (!is_mrope && !is_vision) {
CL_CHECK(clSetKernelArg(kernel, 33, sizeof(int), &n_offs));
} else if (is_mrope && !is_vision) {
CL_CHECK(clSetKernelArg(kernel, 35, sizeof(int), &n_offs));
}
size_t global_work_size[] = {(size_t)ne01*nth, (size_t)ne02, (size_t)ne03};
size_t local_work_size[] = {(size_t)nth, 1, 1};
@@ -24746,6 +24955,14 @@ bool ggml_cl_compute_forward(ggml_backend_t backend, struct ggml_tensor * tensor
}
func = ggml_cl_ssm_conv;
break;
case GGML_OP_SSM_SCAN:
if (!any_on_device) {
return false;
}
// SSM_SCAN has 7 source tensors, so it cannot use the standard
// (src0, src1, dst) func signature. Dispatch directly and return.
ggml_cl_ssm_scan(backend, tensor);
return true;
case GGML_OP_GATED_DELTA_NET:
if (!any_on_device) {
return false;
@@ -68,6 +68,79 @@ __kernel void kernel_moe_scatter(
emap[tile_idx] = val;
}
// Deterministic replacement for kernel_moe_scatter.
//
// kernel_moe_scatter takes each token's slot from atomic_inc(slot_counter[expert]),
// so the token -> slot packing inside an expert depends on which work-item wins the
// atomic and changes from run to run. The ragged prefill GEMM path is sensitive to
// that packing (the non-ragged path is not, since its padded slots alias slot 0 and
// are overwritten last), which makes MoE prompt processing non-reproducible: the same
// binary on the same prompt returns one of several outputs.
//
// Here the slot is the token's rank in flat (n, k) order among the tokens routed to
// the same expert - a fixed function of the routing input. One workgroup per expert
// walks the flat routing list in blocks of 64 and ranks its own tokens with a
// workgroup scan, carrying a running count between blocks. Cost is one pass over the
// routing list per expert; the list is a few KiB and stays in cache.
__kernel void kernel_moe_scatter_stable(
__global const int * input,
__global int * post_router,
__global ushort * emap,
__global const int * tile_offset,
int N,
int topK,
uint n_experts
) {
const int e = get_group_id(1);
const int lid = get_local_id(0);
const int M = N * topK;
__local int scan[64];
__local int running;
if (lid == 0) {
running = 0;
}
barrier(CLK_LOCAL_MEM_FENCE);
for (int base = 0; base < M; base += 64) {
const int j = base + lid;
int pred = 0;
if (j < M) {
const int n = j / topK;
const int k = j - n * topK;
pred = (input[n * (int)n_experts + k] == e) ? 1 : 0;
}
scan[lid] = pred;
barrier(CLK_LOCAL_MEM_FENCE);
// Hillis-Steele inclusive scan over the 64 lanes
for (int off = 1; off < 64; off <<= 1) {
int add = (lid >= off) ? scan[lid - off] : 0;
barrier(CLK_LOCAL_MEM_FENCE);
scan[lid] += add;
barrier(CLK_LOCAL_MEM_FENCE);
}
if (pred) {
const int local_slot = running + (scan[lid] - 1); // exclusive rank
const int tile_idx = tile_offset[e] + (local_slot >> 5);
const int lane = local_slot & 31;
post_router[tile_idx * 32 + lane] = j;
emap[tile_idx] = (ushort)e;
}
barrier(CLK_LOCAL_MEM_FENCE);
if (lid == 63) {
running += scan[63];
}
barrier(CLK_LOCAL_MEM_FENCE);
}
}
__kernel void kernel_moe_fill(
__global int * post_router,
__global int * total_tiles,
@@ -28,6 +28,13 @@
#define QK_K 256
// ADRENO_OLD_COMPILER is defined by the host (-D) only for the Adreno E031
// compilers older than E031.45, which miscompile several constructs this kernel
// used (confirmed on E031.38 and E031.41; E031.45 is clean). Every other
// compiler -- newer E031, E17, DX, Intel, and every non-Adreno device that
// builds this program -- takes the #else branches, which are the original
// source: the workarounds below cost ~13% on the q6_K flat n=1 GEMV where they
// are not needed.
inline float block_q_6_K_dot_y_flat(
global uchar * blk_ql,
global uchar * blk_qh,
@@ -37,6 +44,9 @@ inline float block_q_6_K_dot_y_flat(
int ip,
int is,
int l0,
#if defined(ADRENO_OLD_COMPILER)
int dbg,
#endif
float4 y0,
float4 y1,
float4 y2,
@@ -48,10 +58,40 @@ inline float block_q_6_K_dot_y_flat(
global uchar * q1 = blk_ql + ib*128 + q_offset_l;
global uchar * q2 = q1 + QK_K/8;
global uchar * qh = blk_qh + ib*64 + q_offset_h;
global char * sc = blk_scales + ib*16 + is;
float dall = blk_d[ib];
#if defined(ADRENO_OLD_COMPILER)
// The vectorized dequant (int4/float4 bit-ops, convert_*4, dot()) and vload4
// are miscompiled here -> garbage weights. Reconstruct the 6-bit weights and
// take the dot product scalar. q4_K/q5_K flat already use scalar paths, which
// is why q6_K was the only flat GEMV that failed.
// Scales are SIGNED int8; read as uchar and sign-extend arithmetically so the
// result does not depend on whether the compiler treats `char` as signed.
global uchar * sc = (global uchar *)(blk_scales + ib*16 + is);
int s0 = (int)sc[0] - 256*(sc[0] >> 7);
int s2 = (int)sc[2] - 256*(sc[2] >> 7);
int s4 = (int)sc[4] - 256*(sc[4] >> 7);
int s6 = (int)sc[6] - 256*(sc[6] >> 7);
// one 6-bit weight: low/high nibble of a ql byte OR'd with a 2-bit qh plane
// (plane p in {0,1,2,3} selects qh bits 2p..2p+1) placed at bits 4-5, minus 32.
#define Q6W(qb, sh, hb, p) ((float)((((int)(qb) >> (sh)) & 15) | ((((int)(hb) >> (2*(p))) & 3) << 4)) - 32.f)
float d0 = y0.s0*Q6W(q1[0],0,qh[0],0) + y0.s1*Q6W(q1[1],0,qh[1],0) + y0.s2*Q6W(q1[2],0,qh[2],0) + y0.s3*Q6W(q1[3],0,qh[3],0);
float d1 = y1.s0*Q6W(q2[0],0,qh[0],1) + y1.s1*Q6W(q2[1],0,qh[1],1) + y1.s2*Q6W(q2[2],0,qh[2],1) + y1.s3*Q6W(q2[3],0,qh[3],1);
float d2 = y2.s0*Q6W(q1[0],4,qh[0],2) + y2.s1*Q6W(q1[1],4,qh[1],2) + y2.s2*Q6W(q1[2],4,qh[2],2) + y2.s3*Q6W(q1[3],4,qh[3],2);
float d3 = y3.s0*Q6W(q2[0],4,qh[0],3) + y3.s1*Q6W(q2[1],4,qh[1],3) + y3.s2*Q6W(q2[2],4,qh[2],3) + y3.s3*Q6W(q2[3],4,qh[3],3);
#undef Q6W
if (dbg) printf("HELPER dall=%f s=[%d %d %d %d] d=[%f %f %f %f] ql0=%d qh0=%d y00=%f\n",
dall, s0, s2, s4, s6, d0, d1, d2, d3, (int)q1[0], (int)qh[0], y0.s0);
return dall * (d0 * s0 + d1 * s2 + d2 * s4 + d3 * s6);
#else
global char * sc = blk_scales + ib*16 + is;
// Vectorized loads: 3 uchar4 weight loads instead of 12 scalar byte reads.
// q_offset_l/h are 4-aligned, so these are aligned vector loads.
uchar4 q1v = vload4(0, q1);
@@ -72,6 +112,7 @@ inline float block_q_6_K_dot_y_flat(
return dall * (dot(y0, w0) * sc[0] + dot(y1, w1) * sc[2] +
dot(y2, w2) * sc[4] + dot(y3, w3) * sc[6]);
#endif
}
#undef N_DST
@@ -113,6 +154,11 @@ kernel void kernel_mul_mv_q6_K_f32_flat(
int ne1,
int r2,
int r3
#if defined(ADRENO_OLD_COMPILER)
,
uchar q6k_mask // runtime 0xFF; the host passes it so the compiler cannot
// constant-fold the printf guards below into nothing
#endif
) {
src1 = (global float*)((global char*)src1 + offset1);
dst = (global float*)((global char*)dst + offsetd);
@@ -128,6 +174,22 @@ kernel void kernel_mul_mv_q6_K_f32_flat(
int first_row = (N_SIMDGROUP * r0 + get_sub_group_id()) * N_DST;
#if defined(ADRENO_OLD_COMPILER)
// 64-bit `ulong` integer arithmetic is miscompiled here -> the base-pointer byte
// offsets came out wrong, so EVERY weight/scale read hit the wrong address. This
// was the primary cause of the q6_K flat failure (q5_K uses int offsets and is
// unaffected). Compute the block index in `int` and widen to `ulong` only inside
// the pointer expression: the byte offset stays 64-bit, but there is no ulong
// arithmetic chain to miscompile. The int index would overflow past ~2^31 blocks,
// which no realistic weight reaches -- but that is a narrowing, so keep it off the
// conformant path, which retains full ulong arithmetic.
int offset_src0 = first_row*nb + (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02);
global uchar * blk_ql = (global uchar *) src0_ql + (ulong)offset_src0 * 128;
global uchar * blk_qh = (global uchar *) src0_qh + (ulong)offset_src0 * 64;
global char * blk_scales = (global char *) src0_s + (ulong)offset_src0 * 16;
global half * blk_d = (global half *) src0_d + offset_src0;
#else
ulong offset_src0 = first_row*nb + (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02);
ulong offset_src0_ql = offset_src0 * 128;
ulong offset_src0_qh = offset_src0 * 64;
@@ -138,6 +200,7 @@ kernel void kernel_mul_mv_q6_K_f32_flat(
global uchar * blk_qh = (global uchar *) src0_qh + offset_src0_qh;
global char * blk_scales = (global char *) src0_s + offset_src0_s;
global half * blk_d = (global half *) src0_d + offset_src0_d;
#endif
global float * yy = (global float *) src1 + r1*ne10 + im*ne00*ne1;
int tid = get_sub_group_local_id()%(N_SIMDWIDTH/BLOCK_STRIDE); // within-super-block part, 0..15
@@ -155,24 +218,55 @@ kernel void kernel_mul_mv_q6_K_f32_flat(
for (int ib = ix; ib < nb; ib += BLOCK_STRIDE) {
global float * y = yy + ib * QK_K + 128*ip + l0;
#if defined(ADRENO_OLD_COMPILER)
// vload4 of f32 is miscompiled here; index the lanes scalar instead.
float4 y0 = (float4)(y[ 0], y[ 1], y[ 2], y[ 3]);
float4 y1 = (float4)(y[32], y[33], y[34], y[35]);
float4 y2 = (float4)(y[64], y[65], y[66], y[67]);
float4 y3 = (float4)(y[96], y[97], y[98], y[99]);
#else
float4 y0 = vload4(0, y + 0);
float4 y1 = vload4(0, y + 32);
float4 y2 = vload4(0, y + 64);
float4 y3 = vload4(0, y + 96);
#endif
for (int row = 0; row < N_DST; row++) {
if (first_row + row < ne01) {
#if defined(ADRENO_OLD_COMPILER)
int dbg = (q6k_mask==0xFE && r0==0 && r1==0 && im==0 && row==0 && ib==0 &&
ne00==256 && ne01==16 && get_sub_group_local_id()==0) ? 1 : 0;
sumf[row] += block_q_6_K_dot_y_flat(
blk_ql + row*nb*128, blk_qh + row*nb*64, blk_scales + row*nb*16, blk_d + row*nb,
ib, ip, is, l0, dbg, y0, y1, y2, y3);
#else
sumf[row] += block_q_6_K_dot_y_flat(
blk_ql + row*nb*128, blk_qh + row*nb*64, blk_scales + row*nb*16, blk_d + row*nb,
ib, ip, is, l0, y0, y1, y2, y3);
#endif
}
}
}
#if defined(ADRENO_OLD_COMPILER)
// Optimizer barrier. This compiler drops the sumf partials unless a side effect
// forces them to materialize. q6k_mask is a kernel arg the compiler cannot prove
// is never 0xFE (the host always passes 0xFF), so the printf survives compilation
// but never executes. FRAGILE: the exact set and placement of these guarded
// printfs is load-bearing on E031.41 -- removing any one re-breaks q6_K.
if (q6k_mask==0xFE && r0==0 && r1==0 && im==0 && ne00==256 && ne01==16 && get_sub_group_local_id()<16) {
printf("Q6KLANE lane=%d ip=%d il=%d is=%d l0=%d sumf0=%f\n",
get_sub_group_local_id(), ip, il, is, l0, sumf[0]);
}
#endif
for (int row = 0; row < N_DST; row++) {
float tot = sub_group_reduce_add(sumf[row]);
if (get_sub_group_local_id() == 0 && first_row + row < ne01) {
dst[r1*ne0 + im*ne0*ne1 + first_row + row] = tot;
#if defined(ADRENO_OLD_COMPILER)
if (q6k_mask==0xFE && r0==0 && r1==0 && im==0 && row==0 && ne00==256 && ne01==16)
printf("Q6KTOT tot=%f\n", tot);
#endif
}
}
}
+52 -40
View File
@@ -75,7 +75,8 @@ kernel void kernel_rope_norm_f32(
float ext_factor,
float attn_factor,
float beta_fast,
float beta_slow
float beta_slow,
int n_offs
) {
src0 = (global void*)((global char*)src0 + offset0);
src1 = (global int*)((global char*)src1 + offset1);
@@ -94,14 +95,15 @@ kernel void kernel_rope_norm_f32(
float inv_ndims = -1.f/n_dims;
for (int i0 = 2*get_local_id(0); i0 < ne0; i0 += 2*get_local_size(0)) {
if (i0 < n_dims) {
int ic = i0/2;
if (i0 >= n_offs && i0 < n_offs + n_dims) {
int iw = i0 - n_offs; // relative idx
int ic = iw/2;
float theta = theta_base * pow(freq_base, inv_ndims*i0);
float theta = theta_base * pow(freq_base, inv_ndims*iw);
float freq_factor = src2 != src0 ? src2[ic] : 1.0f;
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor);
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, iw, ext_factor, attn_factor);
global float * src = (global float *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00);
global float * dst_data = (global float *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
@@ -154,7 +156,8 @@ kernel void kernel_rope_norm_f16(
float ext_factor,
float attn_factor,
float beta_fast,
float beta_slow
float beta_slow,
int n_offs
) {
src0 = (global void*)((global char*)src0 + offset0);
src1 = (global int*)((global char*)src1 + offset1);
@@ -173,14 +176,15 @@ kernel void kernel_rope_norm_f16(
float inv_ndims = -1.f/n_dims;
for (int i0 = 2*get_local_id(0); i0 < ne0; i0 += 2*get_local_size(0)) {
if (i0 < n_dims) {
int ic = i0/2;
if (i0 >= n_offs && i0 < n_offs + n_dims) {
int iw = i0 - n_offs; // relative idx
int ic = iw/2;
float theta = theta_base * pow(freq_base, inv_ndims*i0);
float theta = theta_base * pow(freq_base, inv_ndims*iw);
float freq_factor = src2 != src0 ? src2[ic] : 1.0f;
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor);
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, iw, ext_factor, attn_factor);
global half * src = (global half *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00);
global half * dst_data = (global half *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
@@ -233,7 +237,8 @@ kernel void kernel_rope_neox_f32(
float ext_factor,
float attn_factor,
float beta_fast,
float beta_slow
float beta_slow,
int n_offs
) {
src0 = (global void*)((global char*)src0 + offset0);
src1 = (global int*)((global char*)src1 + offset1);
@@ -252,17 +257,18 @@ kernel void kernel_rope_neox_f32(
float inv_ndims = -1.f/n_dims;
for (int i0 = 2*get_local_id(0); i0 < ne0; i0 += 2*get_local_size(0)) {
if (i0 < n_dims) {
int ic = i0/2;
if (i0 >= n_offs && i0 < n_offs + n_dims) {
int iw = i0 - n_offs; // relative idx
int ic = iw/2;
const float theta = theta_base * pow(freq_base, inv_ndims*i0);
const float theta = theta_base * pow(freq_base, inv_ndims*iw);
const float freq_factor = src2 != src0 ? src2[ic] : 1.0f;
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor);
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, iw, ext_factor, attn_factor);
global float * src = (global float *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + ic*nb00);
global float * dst_data = (global float *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + ic*nb0);
global float * src = (global float *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + (n_offs + ic)*nb00);
global float * dst_data = (global float *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + (n_offs + ic)*nb0);
const float x0 = src[0];
const float x1 = src[n_dims/2];
@@ -312,7 +318,8 @@ kernel void kernel_rope_neox_f16(
float ext_factor,
float attn_factor,
float beta_fast,
float beta_slow
float beta_slow,
int n_offs
) {
src0 = (global void*)((global char*)src0 + offset0);
src1 = (global int*)((global char*)src1 + offset1);
@@ -331,17 +338,18 @@ kernel void kernel_rope_neox_f16(
float inv_ndims = -1.f/n_dims;
for (int i0 = 2*get_local_id(0); i0 < ne0; i0 += 2*get_local_size(0)) {
if (i0 < n_dims) {
int ic = i0/2;
if (i0 >= n_offs && i0 < n_offs + n_dims) {
int iw = i0 - n_offs; // relative idx
int ic = iw/2;
const float theta = theta_base * pow(freq_base, inv_ndims*i0);
const float theta = theta_base * pow(freq_base, inv_ndims*iw);
const float freq_factor = src2 != src0 ? src2[ic] : 1.0f;
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor);
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, iw, ext_factor, attn_factor);
global half * src = (global half *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + ic*nb00);
global half * dst_data = (global half *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + ic*nb0);
global half * src = (global half *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + (n_offs + ic)*nb00);
global half * dst_data = (global half *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + (n_offs + ic)*nb0);
const float x0 = src[0];
const float x1 = src[n_dims/2];
@@ -393,7 +401,8 @@ kernel void kernel_rope_multi_f32(
float beta_fast,
float beta_slow,
int4 sections,
int is_imrope
int is_imrope,
int n_offs
) {
src0 = (global void*)((global char*)src0 + offset0);
src1 = (global int*)((global char*)src1 + offset1);
@@ -414,10 +423,11 @@ kernel void kernel_rope_multi_f32(
float inv_ndims = -1.f/n_dims;
for (int i0 = 2*get_local_id(0); i0 < ne0; i0 += 2*get_local_size(0)) {
if (i0 < n_dims) {
int ic = i0/2;
if (i0 >= n_offs && i0 < n_offs + n_dims) {
int iw = i0 - n_offs; // relative idx
int ic = iw/2;
const int sector = (i0 / 2) % sect_dims;
const int sector = ic % sect_dims;
float theta_base = 0.0f;
if (is_imrope) {
@@ -445,14 +455,14 @@ kernel void kernel_rope_multi_f32(
}
}
const float theta = theta_base * pow(freq_base, inv_ndims*i0);
const float theta = theta_base * pow(freq_base, inv_ndims*iw);
const float freq_factor = src2 != src0 ? src2[ic] : 1.0f;
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor);
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, iw, ext_factor, attn_factor);
global float * src = (global float *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + ic*nb00);
global float * dst_data = (global float *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + ic*nb0);
global float * src = (global float *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + (n_offs + ic)*nb00);
global float * dst_data = (global float *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + (n_offs + ic)*nb0);
const float x0 = src[0];
const float x1 = src[n_dims/2];
@@ -504,7 +514,8 @@ kernel void kernel_rope_multi_f16(
float beta_fast,
float beta_slow,
int4 sections,
int is_imrope
int is_imrope,
int n_offs
) {
src0 = (global void*)((global char*)src0 + offset0);
src1 = (global int*)((global char*)src1 + offset1);
@@ -525,10 +536,11 @@ kernel void kernel_rope_multi_f16(
float inv_ndims = -1.f/n_dims;
for (int i0 = 2*get_local_id(0); i0 < ne0; i0 += 2*get_local_size(0)) {
if (i0 < n_dims) {
int ic = i0/2;
if (i0 >= n_offs && i0 < n_offs + n_dims) {
int iw = i0 - n_offs; // relative idx
int ic = iw/2;
const int sector = (i0 / 2) % sect_dims;
const int sector = ic % sect_dims;
float theta_base = 0.0f;
if (is_imrope) {
@@ -556,14 +568,14 @@ kernel void kernel_rope_multi_f16(
}
}
const float theta = theta_base * pow(freq_base, inv_ndims*i0);
const float theta = theta_base * pow(freq_base, inv_ndims*iw);
const float freq_factor = src2 != src0 ? src2[ic] : 1.0f;
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor);
float2 cos_sin_theta = rope_yarn(theta/freq_factor, freq_scale, corr_dims, iw, ext_factor, attn_factor);
global half * src = (global half *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + ic*nb00);
global half * dst_data = (global half *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + ic*nb0);
global half * src = (global half *)((global char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + (n_offs + ic)*nb00);
global half * dst_data = (global half *)((global char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + (n_offs + ic)*nb0);
const float x0 = src[0];
const float x1 = src[n_dims/2];
+216
View File
@@ -0,0 +1,216 @@
// Mamba2 fused SSM scan kernel. One workgroup per (head, dim, seq); WG size =
// 64 threads. Each thread owns c_factor = d_state/64 state elements in
// private registers; the state stays resident across the n_tokens t-loop
//
// References:
// ggml/src/ggml-cuda/ssm-scan.cu:117 ssm_scan_f32_group
// ggml/src/ggml-cpu/ops.cpp:9368 ggml_compute_forward_ssm_scan_f32
#pragma OPENCL EXTENSION cl_khr_fp16 : enable
#ifdef cl_khr_subgroups
#pragma OPENCL EXTENSION cl_khr_subgroups : enable
#endif
#if defined(cl_qcom_reqd_sub_group_size)
#pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
#define REQD_SUBGROUP_SIZE_64 __attribute__((qcom_reqd_sub_group_size("half")))
#else
#define REQD_SUBGROUP_SIZE_64
#endif
inline float softplus_f32(float x) {
return (x <= 20.0f) ? log(1.0f + exp(x)) : x;
}
// d_state = 128 (most Mamba-2 models, e.g. mamba2-2.7B, Codestral-Mamba).
// WG = 64 threads, each holds 2 state elements (tid and tid+64).
REQD_SUBGROUP_SIZE_64
kernel void kernel_ssm_scan_f32_mamba2_d128(
global const char * src0_base, ulong src0_off,
global const char * src1_base, ulong src1_off,
global const char * src2_base, ulong src2_off,
global const char * src3_base, ulong src3_off,
global const char * src4_base, ulong src4_off,
global const char * src5_base, ulong src5_off,
global const char * src6_base, ulong src6_off,
global char * dst_base, ulong dst_off,
ulong s0_nb2, ulong s0_nb3,
ulong x_nb2, ulong x_nb3,
ulong dt_nb1, ulong dt_nb2,
ulong A_nb1,
ulong B_nb2, ulong B_nb3,
ulong C_nb2, ulong C_nb3,
ulong s_off_bytes,
int head_dim, int n_head, int n_group, int n_tokens
) {
const int d_state = 128;
const int tid = (int) get_local_id(0);
const int wg_x = (int) get_group_id(0);
const int seq_id = (int) get_group_id(1);
const int head_id = wg_x / head_dim;
const int dim_id = wg_x - head_id * head_dim;
const int g = head_id / (n_head / n_group);
src0_base += src0_off;
src1_base += src1_off;
src2_base += src2_off;
src3_base += src3_off;
src4_base += src4_off;
src5_base += src5_off;
src6_base += src6_off;
dst_base += dst_off;
const int seq_slot = ((global const int *) src6_base)[seq_id];
const ulong state_base_off = (ulong)seq_slot * s0_nb3 + (ulong)head_id * s0_nb2
+ (ulong)dim_id * d_state * sizeof(float);
global const float * s0_warp = (global const float *)(src0_base + state_base_off);
const ulong state_out_off = (ulong)seq_id * s0_nb3 + (ulong)head_id * s0_nb2
+ (ulong)dim_id * d_state * sizeof(float);
global float * s_warp = (global float *)(dst_base + s_off_bytes + state_out_off);
global const char * x_seq = src1_base + (ulong)seq_id * x_nb3;
global const char * dt_seq = src2_base + (ulong)seq_id * dt_nb2;
global const char * B_seq = src4_base + (ulong)seq_id * B_nb3 + (ulong)g * d_state * sizeof(float);
global const char * C_seq = src5_base + (ulong)seq_id * C_nb3 + (ulong)g * d_state * sizeof(float);
const ulong y_dim_total = (ulong)n_head * head_dim;
global float * y_seq = (global float *)dst_base
+ (ulong)seq_id * (ulong)n_tokens * y_dim_total;
const float A_val = ((global const float *)src3_base)[(ulong)head_id * A_nb1 / sizeof(float)];
// c_factor = 2: each thread owns 2 state elements (tid and tid+64).
float state0 = s0_warp[tid];
float state1 = s0_warp[tid + 64];
for (int t = 0; t < n_tokens; ++t) {
const float dt_h = ((global const float *)(dt_seq + (ulong)t * dt_nb1))[head_id];
const float dt_softplus = softplus_f32(dt_h);
const float dA = exp(dt_softplus * A_val);
const float x_val = ((global const float *)(x_seq + (ulong)t * x_nb2))[(ulong)head_id * head_dim + dim_id];
const float x_dt = x_val * dt_softplus;
const float B0 = ((global const float *)(B_seq + (ulong)t * B_nb2))[tid];
const float B1 = ((global const float *)(B_seq + (ulong)t * B_nb2))[tid + 64];
const float C0 = ((global const float *)(C_seq + (ulong)t * C_nb2))[tid];
const float C1 = ((global const float *)(C_seq + (ulong)t * C_nb2))[tid + 64];
state0 = state0 * dA + B0 * x_dt;
state1 = state1 * dA + B1 * x_dt;
const float partial = state0 * C0 + state1 * C1;
const float sum = sub_group_reduce_add(partial);
if (tid == 0) {
y_seq[(ulong)t * y_dim_total + (ulong)head_id * head_dim + dim_id] = sum;
}
}
s_warp[tid] = state0;
s_warp[tid + 64] = state1;
}
// d_state = 256 (Falcon-H1). WG = 64 threads, each holds 4 state elements.
REQD_SUBGROUP_SIZE_64
kernel void kernel_ssm_scan_f32_mamba2_d256(
global const char * src0_base, ulong src0_off,
global const char * src1_base, ulong src1_off,
global const char * src2_base, ulong src2_off,
global const char * src3_base, ulong src3_off,
global const char * src4_base, ulong src4_off,
global const char * src5_base, ulong src5_off,
global const char * src6_base, ulong src6_off,
global char * dst_base, ulong dst_off,
ulong s0_nb2, ulong s0_nb3,
ulong x_nb2, ulong x_nb3,
ulong dt_nb1, ulong dt_nb2,
ulong A_nb1,
ulong B_nb2, ulong B_nb3,
ulong C_nb2, ulong C_nb3,
ulong s_off_bytes,
int head_dim, int n_head, int n_group, int n_tokens
) {
const int d_state = 256;
const int tid = (int) get_local_id(0);
const int wg_x = (int) get_group_id(0);
const int seq_id = (int) get_group_id(1);
const int head_id = wg_x / head_dim;
const int dim_id = wg_x - head_id * head_dim;
const int g = head_id / (n_head / n_group);
src0_base += src0_off;
src1_base += src1_off;
src2_base += src2_off;
src3_base += src3_off;
src4_base += src4_off;
src5_base += src5_off;
src6_base += src6_off;
dst_base += dst_off;
const int seq_slot = ((global const int *) src6_base)[seq_id];
const ulong state_base_off = (ulong)seq_slot * s0_nb3 + (ulong)head_id * s0_nb2
+ (ulong)dim_id * d_state * sizeof(float);
global const float * s0_warp = (global const float *)(src0_base + state_base_off);
const ulong state_out_off = (ulong)seq_id * s0_nb3 + (ulong)head_id * s0_nb2
+ (ulong)dim_id * d_state * sizeof(float);
global float * s_warp = (global float *)(dst_base + s_off_bytes + state_out_off);
global const char * x_seq = src1_base + (ulong)seq_id * x_nb3;
global const char * dt_seq = src2_base + (ulong)seq_id * dt_nb2;
global const char * B_seq = src4_base + (ulong)seq_id * B_nb3 + (ulong)g * d_state * sizeof(float);
global const char * C_seq = src5_base + (ulong)seq_id * C_nb3 + (ulong)g * d_state * sizeof(float);
const ulong y_dim_total = (ulong)n_head * head_dim;
global float * y_seq = (global float *)dst_base
+ (ulong)seq_id * (ulong)n_tokens * y_dim_total;
const float A_val = ((global const float *)src3_base)[(ulong)head_id * A_nb1 / sizeof(float)];
// c_factor = 4: each thread owns 4 state elements.
float state0 = s0_warp[tid];
float state1 = s0_warp[tid + 64];
float state2 = s0_warp[tid + 128];
float state3 = s0_warp[tid + 192];
for (int t = 0; t < n_tokens; ++t) {
const float dt_h = ((global const float *)(dt_seq + (ulong)t * dt_nb1))[head_id];
const float dt_softplus = softplus_f32(dt_h);
const float dA = exp(dt_softplus * A_val);
const float x_val = ((global const float *)(x_seq + (ulong)t * x_nb2))[(ulong)head_id * head_dim + dim_id];
const float x_dt = x_val * dt_softplus;
global const float * B_t = (global const float *)(B_seq + (ulong)t * B_nb2);
global const float * C_t = (global const float *)(C_seq + (ulong)t * C_nb2);
const float B0 = B_t[tid];
const float B1 = B_t[tid + 64];
const float B2 = B_t[tid + 128];
const float B3 = B_t[tid + 192];
const float C0 = C_t[tid];
const float C1 = C_t[tid + 64];
const float C2 = C_t[tid + 128];
const float C3 = C_t[tid + 192];
state0 = state0 * dA + B0 * x_dt;
state1 = state1 * dA + B1 * x_dt;
state2 = state2 * dA + B2 * x_dt;
state3 = state3 * dA + B3 * x_dt;
const float partial = state0 * C0 + state1 * C1 + state2 * C2 + state3 * C3;
const float sum = sub_group_reduce_add(partial);
if (tid == 0) {
y_seq[(ulong)t * y_dim_total + (ulong)head_id * head_dim + dim_id] = sum;
}
}
s_warp[tid] = state0;
s_warp[tid + 64] = state1;
s_warp[tid + 128] = state2;
s_warp[tid + 192] = state3;
}
-2
View File
@@ -6242,8 +6242,6 @@ static bool do_ggml_backend_sycl_device_supports_op(ggml_backend_dev_t dev, cons
}
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
// FIXME: support ggml_rope_set_offset
return ((const int32_t *) op->op_params)[15] == 0;
case GGML_OP_IM2COL:
case GGML_OP_IM2COL_3D:
case GGML_OP_UPSCALE:
+58 -48
View File
@@ -41,7 +41,7 @@ template <bool forward, bool has_ff, typename T, typename D>
static void rope_norm(const T *x, D *dst, const int ne00, const int ne01,
const int ne02, const int s01, const int s02,
const int s03, const int s1, const int s2, const int s3,
const int n_dims, const int32_t *pos,
const int n_dims, const int n_offs, const int32_t *pos,
const float freq_scale, const float ext_factor,
const float attn_factor, const rope_corr_dims corr_dims,
const float theta_scale, const float *freq_factors,
@@ -78,19 +78,21 @@ static void rope_norm(const T *x, D *dst, const int ne00, const int ne01,
ggml_sycl_memcpy_1<4>(dst + idst, &v);
}
};
if (i0 >= n_dims) {
if (i0 < n_offs || i0 >= n_offs + n_dims) {
store_coaelsced(x[ix + 0], x[ix + 1]);
return;
}
const float theta_base = pos[i2] * dpct::pow(theta_scale, i0 / 2.0f);
const int iw = i0 - n_offs; // relative idx
const float freq_factor = has_ff ? freq_factors[i0 / 2] : 1.0f;
const float theta_base = pos[i2] * dpct::pow(theta_scale, iw / 2.0f);
const float freq_factor = has_ff ? freq_factors[iw / 2] : 1.0f;
float cos_theta;
float sin_theta;
rope_yarn<forward>(theta_base / freq_factor, freq_scale, corr_dims, i0,
rope_yarn<forward>(theta_base / freq_factor, freq_scale, corr_dims, iw,
ext_factor, attn_factor, cos_theta, sin_theta);
const float x0 = x[ix + 0];
@@ -104,7 +106,7 @@ template <bool forward, bool has_ff, typename T, typename D>
static void rope_neox(const T *x, D *dst, const int ne00, const int ne01,
const int ne02, const int s01, const int s02,
const int s03, const int s1, const int s2, const int s3,
const int n_dims, const int32_t *pos,
const int n_dims, const int n_offs, const int32_t *pos,
const float freq_scale, const float ext_factor,
const float attn_factor, const rope_corr_dims corr_dims,
const float theta_scale, const float *freq_factors,
@@ -132,35 +134,38 @@ static void rope_neox(const T *x, D *dst, const int ne00, const int ne01,
idst += row_indices[i2] * set_rows_stride;
}
if (i0 >= n_dims) {
if (i0 < n_offs || i0 >= n_offs + n_dims) {
dst[idst + i0 / 2 + 0] = ggml_sycl_cast<D>(x[ix + i0 / 2 + 0]);
dst[idst + i0 / 2 + 1] = ggml_sycl_cast<D>(x[ix + i0 / 2 + 1]);
return;
}
const float theta_base = pos[i2] * dpct::pow(theta_scale, i0 / 2.0f);
const int iw = i0 - n_offs; // relative idx
const float freq_factor = has_ff ? freq_factors[i0 / 2] : 1.0f;
const float theta_base = pos[i2] * dpct::pow(theta_scale, iw / 2.0f);
const float freq_factor = has_ff ? freq_factors[iw / 2] : 1.0f;
float cos_theta;
float sin_theta;
rope_yarn<forward>(theta_base / freq_factor, freq_scale, corr_dims, i0,
rope_yarn<forward>(theta_base / freq_factor, freq_scale, corr_dims, iw,
ext_factor, attn_factor, cos_theta, sin_theta);
const float x0 = x[ix + 0];
const float x1 = x[ix + n_dims / 2];
// idst/ix point at channel i0/2; the first channel of the rotated pair is n_offs + iw/2 = i0/2 + n_offs/2
const float x0 = x[ix + n_offs / 2 + 0];
const float x1 = x[ix + n_offs / 2 + n_dims / 2];
dst[idst + 0] = ggml_sycl_cast<D>(x0 * cos_theta - x1 * sin_theta);
dst[idst + n_dims / 2] = ggml_sycl_cast<D>(x0 * sin_theta + x1 * cos_theta);
dst[idst + n_offs / 2 + 0] = ggml_sycl_cast<D>(x0 * cos_theta - x1 * sin_theta);
dst[idst + n_offs / 2 + n_dims / 2] = ggml_sycl_cast<D>(x0 * sin_theta + x1 * cos_theta);
}
template <bool forward, bool has_ff, typename T>
static void rope_multi(const T *x, T *dst, const int ne00, const int ne01,
const int ne02, const int s01, const int s02,
const int s03, const int s1, const int s2, const int s3,
const int n_dims, const int32_t *pos,
const int n_dims, const int n_offs, const int32_t *pos,
const float freq_scale, const float ext_factor,
const float attn_factor, const rope_corr_dims corr_dims,
const float theta_scale, const float *freq_factors,
@@ -183,54 +188,57 @@ static void rope_multi(const T *x, T *dst, const int ne00, const int ne01,
int idst = i0 / 2 + i1 * s1 + i2 * s2 + i3 * s3;
const int ix = i0 / 2 + i1 * s01 + i2 * s02 + i3 * s03;
if (i0 >= n_dims) {
if (i0 < n_offs || i0 >= n_offs + n_dims) {
dst[idst + i0 / 2 + 0] = x[ix + i0 / 2 + 0];
dst[idst + i0 / 2 + 1] = x[ix + i0 / 2 + 1];
return;
}
const int iw = i0 - n_offs; // relative idx
const int sect_dims =
sections.v[0] + sections.v[1] + sections.v[2] + sections.v[3];
const int sec_w = sections.v[1] + sections.v[0];
const int sector = (i0 / 2) % sect_dims;
const int sector = (iw / 2) % sect_dims;
float theta_base = 0.0;
if (is_imrope) {
if (sector % 3 == 1 && sector < 3 * sections.v[1]) { // h
theta_base = pos[i2 + ne02 * 1] * dpct::pow(theta_scale, i0 / 2.0f);
theta_base = pos[i2 + ne02 * 1] * dpct::pow(theta_scale, iw / 2.0f);
} else if (sector % 3 == 2 && sector < 3 * sections.v[2]) { // w
theta_base = pos[i2 + ne02 * 2] * dpct::pow(theta_scale, i0 / 2.0f);
theta_base = pos[i2 + ne02 * 2] * dpct::pow(theta_scale, iw / 2.0f);
} else if (sector % 3 == 0 && sector < 3 * sections.v[0]) { // t
theta_base = pos[i2] * dpct::pow(theta_scale, i0 / 2.0f);
theta_base = pos[i2] * dpct::pow(theta_scale, iw / 2.0f);
} else {
theta_base = pos[i2 + ne02 * 3] * dpct::pow(theta_scale, i0 / 2.0f);
theta_base = pos[i2 + ne02 * 3] * dpct::pow(theta_scale, iw / 2.0f);
}
} else {
if (sector < sections.v[0]) {
theta_base = pos[i2] * dpct::pow(theta_scale, i0 / 2.0f);
theta_base = pos[i2] * dpct::pow(theta_scale, iw / 2.0f);
} else if (sector >= sections.v[0] && sector < sec_w) {
theta_base = pos[i2 + ne02 * 1] * dpct::pow(theta_scale, i0 / 2.0f);
theta_base = pos[i2 + ne02 * 1] * dpct::pow(theta_scale, iw / 2.0f);
} else if (sector >= sec_w && sector < sec_w + sections.v[2]) {
theta_base = pos[i2 + ne02 * 2] * dpct::pow(theta_scale, i0 / 2.0f);
theta_base = pos[i2 + ne02 * 2] * dpct::pow(theta_scale, iw / 2.0f);
} else if (sector >= sec_w + sections.v[2]) {
theta_base = pos[i2 + ne02 * 3] * dpct::pow(theta_scale, i0 / 2.0f);
theta_base = pos[i2 + ne02 * 3] * dpct::pow(theta_scale, iw / 2.0f);
}
}
const float freq_factor = has_ff ? freq_factors[i0 / 2] : 1.0f;
const float freq_factor = has_ff ? freq_factors[iw / 2] : 1.0f;
float cos_theta;
float sin_theta;
rope_yarn<forward>(theta_base / freq_factor, freq_scale, corr_dims, i0,
rope_yarn<forward>(theta_base / freq_factor, freq_scale, corr_dims, iw,
ext_factor, attn_factor, cos_theta, sin_theta);
const float x0 = x[ix + 0];
const float x1 = x[ix + n_dims / 2];
// idst/ix point at channel i0/2; the first channel of the rotated pair is n_offs + iw/2 = i0/2 + n_offs/2
const float x0 = x[ix + n_offs / 2 + 0];
const float x1 = x[ix + n_offs / 2 + n_dims / 2];
dst[idst + 0] = x0 * cos_theta - x1 * sin_theta;
dst[idst + n_dims / 2] = x0 * sin_theta + x1 * cos_theta;
dst[idst + n_offs / 2 + 0] = x0 * cos_theta - x1 * sin_theta;
dst[idst + n_offs / 2 + n_dims / 2] = x0 * sin_theta + x1 * cos_theta;
}
template <bool forward, bool has_ff, typename T>
@@ -293,7 +301,7 @@ static void
rope_norm_sycl(const T *x, D *dst, const int ne00, const int ne01,
const int ne02, const int s01, const int s02, const int s03,
const int s1, const int s2, const int s3, const int n_dims,
const int nr, const int32_t *pos, const float freq_scale,
const int n_offs, const int nr, const int32_t *pos, const float freq_scale,
const float freq_base, const float ext_factor,
const float attn_factor, const rope_corr_dims corr_dims,
const float *freq_factors, const int64_t *row_indices,
@@ -313,7 +321,7 @@ rope_norm_sycl(const T *x, D *dst, const int ne00, const int ne01,
GGML_UNUSED(item_ct1);
rope_norm<forward, false>(
x, dst, ne00, ne01, ne02, s01, s02, s03, s1, s2, s3, n_dims,
pos, freq_scale, ext_factor, attn_factor, corr_dims,
n_offs, pos, freq_scale, ext_factor, attn_factor, corr_dims,
theta_scale, freq_factors, row_indices, set_rows_stride);
});
} else {
@@ -323,7 +331,7 @@ rope_norm_sycl(const T *x, D *dst, const int ne00, const int ne01,
GGML_UNUSED(item_ct1);
rope_norm<forward, true>(
x, dst, ne00, ne01, ne02, s01, s02, s03, s1, s2, s3, n_dims,
pos, freq_scale, ext_factor, attn_factor, corr_dims,
n_offs, pos, freq_scale, ext_factor, attn_factor, corr_dims,
theta_scale, freq_factors, row_indices, set_rows_stride);
});
}
@@ -334,7 +342,7 @@ static void
rope_neox_sycl(const T *x, D *dst, const int ne00, const int ne01,
const int ne02, const int s01, const int s02, const int s03,
const int s1, const int s2, const int s3, const int n_dims,
const int nr, const int32_t *pos, const float freq_scale,
const int n_offs, const int nr, const int32_t *pos, const float freq_scale,
const float freq_base, const float ext_factor,
const float attn_factor, const rope_corr_dims corr_dims,
const float *freq_factors, const int64_t *row_indices,
@@ -354,7 +362,7 @@ rope_neox_sycl(const T *x, D *dst, const int ne00, const int ne01,
GGML_UNUSED(item_ct1);
rope_neox<forward, false>(
x, dst, ne00, ne01, ne02, s01, s02, s03, s1, s2, s3, n_dims,
pos, freq_scale, ext_factor, attn_factor, corr_dims,
n_offs, pos, freq_scale, ext_factor, attn_factor, corr_dims,
theta_scale, freq_factors, row_indices, set_rows_stride);
});
} else {
@@ -364,7 +372,7 @@ rope_neox_sycl(const T *x, D *dst, const int ne00, const int ne01,
GGML_UNUSED(item_ct1);
rope_neox<forward, true>(
x, dst, ne00, ne01, ne02, s01, s02, s03, s1, s2, s3, n_dims,
pos, freq_scale, ext_factor, attn_factor, corr_dims,
n_offs, pos, freq_scale, ext_factor, attn_factor, corr_dims,
theta_scale, freq_factors, row_indices, set_rows_stride);
});
}
@@ -375,7 +383,7 @@ static void
rope_multi_sycl(const T *x, T *dst, const int ne00, const int ne01,
const int ne02, const int s01, const int s02, const int s03,
const int s1, const int s2, const int s3, const int n_dims,
const int nr, const int32_t *pos, const float freq_scale,
const int n_offs, const int nr, const int32_t *pos, const float freq_scale,
const float freq_base, const float ext_factor,
const float attn_factor, const rope_corr_dims corr_dims,
const float *freq_factors, const mrope_sections sections,
@@ -395,7 +403,7 @@ rope_multi_sycl(const T *x, T *dst, const int ne00, const int ne01,
GGML_UNUSED(item_ct1);
rope_multi<forward, false, T>(
x, dst, ne00, ne01, ne02, s01, s02, s03, s1, s2, s3, n_dims,
pos, freq_scale, ext_factor, attn_factor, corr_dims,
n_offs, pos, freq_scale, ext_factor, attn_factor, corr_dims,
theta_scale, freq_factors, sections, is_imrope);
});
} else {
@@ -405,7 +413,7 @@ rope_multi_sycl(const T *x, T *dst, const int ne00, const int ne01,
GGML_UNUSED(item_ct1);
rope_multi<forward, true, T>(
x, dst, ne00, ne01, ne02, s01, s02, s03, s1, s2, s3, n_dims,
pos, freq_scale, ext_factor, attn_factor, corr_dims,
n_offs, pos, freq_scale, ext_factor, attn_factor, corr_dims,
theta_scale, freq_factors, sections, is_imrope);
});
}
@@ -497,6 +505,7 @@ void ggml_sycl_op_rope_impl(ggml_backend_sycl_context &ctx, ggml_tensor *dst,
const int n_dims = ((int32_t *)dst->op_params)[1];
const int mode = ((int32_t *)dst->op_params)[2];
const int n_ctx_orig = ((int32_t *)dst->op_params)[4];
const int n_offs = ((int32_t *)dst->op_params)[15];
mrope_sections sections;
float freq_base;
@@ -526,6 +535,7 @@ void ggml_sycl_op_rope_impl(ggml_backend_sycl_context &ctx, ggml_tensor *dst,
if (is_vision) {
GGML_ASSERT(n_dims == ne00 / 2);
GGML_ASSERT(n_offs == 0); // offset not supported for vision, as the rotated pairs span the whole row
}
const int32_t *pos = (const int32_t *)src1_d;
@@ -545,19 +555,19 @@ void ggml_sycl_op_rope_impl(ggml_backend_sycl_context &ctx, ggml_tensor *dst,
if (src0->type == GGML_TYPE_F32 && dst_type == GGML_TYPE_F32) {
rope_neox_sycl<forward, float, float>(
(const float *)src0_d, (float *)dst_d, ne00, ne01, ne02, s01,
s02, s03, s1, s2, s3, n_dims, nr, pos, freq_scale, freq_base,
s02, s03, s1, s2, s3, n_dims, n_offs, nr, pos, freq_scale, freq_base,
ext_factor, attn_factor, corr_dims, freq_factors, row_indices,
set_rows_stride, stream);
} else if (src0->type == GGML_TYPE_F32 && dst_type == GGML_TYPE_F16) {
rope_neox_sycl<forward, float, sycl::half>(
(const float *)src0_d, (sycl::half *)dst_d, ne00, ne01, ne02,
s01, s02, s03, s1, s2, s3, n_dims, nr, pos, freq_scale,
s01, s02, s03, s1, s2, s3, n_dims, n_offs, nr, pos, freq_scale,
freq_base, ext_factor, attn_factor, corr_dims, freq_factors,
row_indices, set_rows_stride, stream);
} else if (src0->type == GGML_TYPE_F16 && dst_type == GGML_TYPE_F16) {
rope_neox_sycl<forward, sycl::half, sycl::half>(
(const sycl::half *)src0_d, (sycl::half *)dst_d, ne00, ne01,
ne02, s01, s02, s03, s1, s2, s3, n_dims, nr, pos, freq_scale,
ne02, s01, s02, s03, s1, s2, s3, n_dims, n_offs, nr, pos, freq_scale,
freq_base, ext_factor, attn_factor, corr_dims, freq_factors,
row_indices, set_rows_stride, stream);
} else {
@@ -568,13 +578,13 @@ void ggml_sycl_op_rope_impl(ggml_backend_sycl_context &ctx, ggml_tensor *dst,
if (src0->type == GGML_TYPE_F32) {
rope_multi_sycl<forward>((const float *)src0_d, (float *)dst_d,
ne00, ne01, ne02, s01, s02, s03, s1, s2,
s3, n_dims, nr, pos, freq_scale, freq_base,
s3, n_dims, n_offs, nr, pos, freq_scale, freq_base,
ext_factor, attn_factor, corr_dims,
freq_factors, sections, is_imrope, stream);
} else if (src0->type == GGML_TYPE_F16) {
rope_multi_sycl<forward>(
(const sycl::half *)src0_d, (sycl::half *)dst_d, ne00, ne01,
ne02, s01, s02, s03, s1, s2, s3, n_dims, nr, pos, freq_scale,
ne02, s01, s02, s03, s1, s2, s3, n_dims, n_offs, nr, pos, freq_scale,
freq_base, ext_factor, attn_factor, corr_dims, freq_factors,
sections, is_imrope, stream);
} else {
@@ -602,19 +612,19 @@ void ggml_sycl_op_rope_impl(ggml_backend_sycl_context &ctx, ggml_tensor *dst,
if (src0->type == GGML_TYPE_F32 && dst_type == GGML_TYPE_F32) {
rope_norm_sycl<forward, float, float>(
(const float *)src0_d, (float *)dst_d, ne00, ne01, ne02, s01,
s02, s03, s1, s2, s3, n_dims, nr, pos, freq_scale, freq_base,
s02, s03, s1, s2, s3, n_dims, n_offs, nr, pos, freq_scale, freq_base,
ext_factor, attn_factor, corr_dims, freq_factors, row_indices,
set_rows_stride, stream);
} else if (src0->type == GGML_TYPE_F32 && dst_type == GGML_TYPE_F16) {
rope_norm_sycl<forward, float, sycl::half>(
(const float *)src0_d, (sycl::half *)dst_d, ne00, ne01, ne02,
s01, s02, s03, s1, s2, s3, n_dims, nr, pos, freq_scale,
s01, s02, s03, s1, s2, s3, n_dims, n_offs, nr, pos, freq_scale,
freq_base, ext_factor, attn_factor, corr_dims, freq_factors,
row_indices, set_rows_stride, stream);
} else if (src0->type == GGML_TYPE_F16 && dst_type == GGML_TYPE_F16) {
rope_norm_sycl<forward, sycl::half, sycl::half>(
(const sycl::half *)src0_d, (sycl::half *)dst_d, ne00, ne01,
ne02, s01, s02, s03, s1, s2, s3, n_dims, nr, pos, freq_scale,
ne02, s01, s02, s03, s1, s2, s3, n_dims, n_offs, nr, pos, freq_scale,
freq_base, ext_factor, attn_factor, corr_dims, freq_factors,
row_indices, set_rows_stride, stream);
} else {
+6
View File
@@ -200,8 +200,11 @@ if (Vulkan_FOUND)
set (_ggml_vk_header "${CMAKE_CURRENT_BINARY_DIR}/ggml-vulkan-shaders.hpp")
set (_ggml_vk_input_dir "${CMAKE_CURRENT_SOURCE_DIR}/vulkan-shaders")
set (_ggml_vk_output_dir "${CMAKE_CURRENT_BINARY_DIR}/vulkan-shaders.spv")
set (_ggml_vk_generated_shader_files ${_ggml_vk_header})
file(GLOB _ggml_vk_shader_files CONFIGURE_DEPENDS "${_ggml_vk_input_dir}/*.comp")
set_source_files_properties(${_ggml_vk_shader_files} PROPERTIES HEADER_FILE_ONLY TRUE)
target_sources(ggml-vulkan PRIVATE ${_ggml_vk_shader_files})
# Because external projects do not provide source-level tracking,
# the vulkan-shaders-gen sources need to be explicitly added to
@@ -241,8 +244,11 @@ if (Vulkan_FOUND)
COMMENT "Generate vulkan shaders for ${file}"
)
target_sources(ggml-vulkan PRIVATE ${_ggml_vk_target_cpp})
list(APPEND _ggml_vk_generated_shader_files ${_ggml_vk_target_cpp})
endforeach()
source_group("Vulkan shaders" FILES ${_ggml_vk_shader_files})
source_group("Generated Vulkan shaders" FILES ${_ggml_vk_generated_shader_files})
else()
message(WARNING "Vulkan not found")
endif()
@@ -121,13 +121,13 @@ void main() {
const uint buf_ib = r * qf_stride + d / 8;
const uint buf_iqs = d % 8;
FLOAT_TYPEV4 vals = is_in_bounds ? FLOAT_TYPEV4(data_qv4[q_offset / 4 + (i * Br + r) * q_stride / 4 + d] * p.scale) : FLOAT_TYPEV4(0.0f);
const FLOAT_TYPEV4 abs_vals = abs(vals);
vec4 vals = is_in_bounds ? data_qv4[q_offset / 4 + (i * Br + r) * q_stride / 4 + d] * p.scale : vec4(0.0f);
const vec4 abs_vals = abs(vals);
const FLOAT_TYPE thread_max = max(max(abs_vals.x, abs_vals.y), max(abs_vals.z, abs_vals.w));
const FLOAT_TYPE amax = subgroupClusteredMax(thread_max, 8);
const FLOAT_TYPE qd = amax / FLOAT_TYPE(127.0);
const FLOAT_TYPE qd_inv = qd != FLOAT_TYPE(0.0) ? FLOAT_TYPE(1.0) / qd : FLOAT_TYPE(0.0);
const float thread_max = max(max(abs_vals.x, abs_vals.y), max(abs_vals.z, abs_vals.w));
const float amax = subgroupClusteredMax(thread_max, 8);
const float qd = amax / 127.0f;
const float qd_inv = qd != 0.0f ? 1.0f / qd : 0.0f;
vals = round(vals * qd_inv);
Qf[buf_ib].qs[buf_iqs] = pack32(i8vec4(vals));
@@ -136,11 +136,11 @@ void main() {
// the row-sum scaled by qd, used in k_dot_correction.
if (FaTypeK == FA_TYPE_Q8_0) {
if (buf_iqs == 0) {
Qf[buf_ib].ds = FLOAT_TYPEV2(qd, 0.0);
Qf[buf_ib].ds = FLOAT_TYPEV2(qd, 0.0f);
}
} else {
const FLOAT_TYPE thread_sum = vals.x + vals.y + vals.z + vals.w;
const FLOAT_TYPE sum = subgroupClusteredAdd(thread_sum, 8);
const float thread_sum = vals.x + vals.y + vals.z + vals.w;
const float sum = subgroupClusteredAdd(thread_sum, 8);
if (buf_iqs == 0) {
Qf[buf_ib].ds = FLOAT_TYPEV2(qd, sum * qd);
+4 -4
View File
@@ -2714,6 +2714,7 @@ static webgpu_encoded_op ggml_webgpu_rope(webgpu_context & ctx,
const int n_dims = ((int32_t *) dst->op_params)[1];
const int mode = ((int32_t *) dst->op_params)[2];
const int n_ctx_orig = ((int32_t *) dst->op_params)[4];
const int n_offs = ((int32_t *) dst->op_params)[15];
float freq_base;
float freq_scale;
@@ -2762,7 +2763,8 @@ static webgpu_encoded_op ggml_webgpu_rope(webgpu_context & ctx,
(uint32_t) sections[0],
(uint32_t) sections[1],
(uint32_t) sections[2],
(uint32_t) sections[3]
(uint32_t) sections[3],
(uint32_t) n_offs
};
std::vector<wgpu::BindGroupEntry> entries = { ggml_webgpu_make_tensor_bind_group_entry(ctx, 0, src0),
@@ -4472,9 +4474,7 @@ static bool ggml_backend_webgpu_device_supports_op(ggml_backend_dev_t dev, const
supports_op = (op->type == GGML_TYPE_F32 && src0->type == GGML_TYPE_F32) && ggml_is_contiguous_rows(src0);
break;
case GGML_OP_ROPE:
// FIXME: support ggml_rope_set_offset
supports_op =
(op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16) && ((const int32_t *) op->op_params)[15] == 0;
supports_op = op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16;
break;
case GGML_OP_GLU:
switch (ggml_get_glu_op(op)) {
+11 -7
View File
@@ -38,7 +38,8 @@ struct Params {
sections0: u32,
sections1: u32,
sections2: u32,
sections3: u32
sections3: u32,
n_offs: u32
};
@group(0) @binding(0)
@@ -126,7 +127,8 @@ fn rope_yarn(theta_extrap: f32, i: u32) -> vec2<f32> {
fn pair_base(i0: u32, div_2: bool) -> u32 {
if (div_2) {
return i0 / 2;
// first channel of the rotated pair: n_offs + (i0 - n_offs)/2
return i0 / 2 + params.n_offs / 2;
} else {
return i0;
}
@@ -165,20 +167,22 @@ fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
let i_src_row = params.offset_src0 + i3 * params.stride_src03 + i2 * params.stride_src02 + i1 * params.stride_src01;
let i_dst_row = params.offset_dst + i3 * params.stride_dst3 + i2 * params.stride_dst2 + i1 * params.stride_dst1;
if (i0 >= params.n_dims && !is_vision) {
if ((i0 < params.n_offs || i0 >= params.n_offs + params.n_dims) && !is_vision) {
let i_src = i_src_row + i0;
let i_dst = i_dst_row + i0;
rotate(i_dst, i_dst + 1, f32(src0[i_src]), f32(src0[i_src + 1]));
return;
}
let iw = i0 - params.n_offs; // relative idx
var theta_base_mult: u32 = 0;
var theta_scale_pwr: u32 = i0 / 2;
var theta_scale_pwr: u32 = iw / 2;
if (is_mrope) {
let sect_dims = params.sections0 + params.sections1 + params.sections2 + params.sections3;
let sec_w = params.sections1 + params.sections0;
let sec_e = params.sections2 + sec_w;
let sector = (i0 / 2) % sect_dims;
let sector = (iw / 2) % sect_dims;
if (is_imrope) {
if (sector % 3 == 1 && sector < 3 * params.sections1) {
theta_base_mult = 1;
@@ -203,7 +207,7 @@ fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
} else if (sector >= sec_e) {
if (is_vision) {
theta_scale_pwr = sector - sec_e;
theta_scale_pwr = (i0 / 2) % sec_e;
theta_scale_pwr = (iw / 2) % sec_e;
}
theta_base_mult = 3;
} else if (is_vision) {
@@ -212,7 +216,7 @@ fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
}
}
let theta_base = f32(src1[params.offset_src1 + i2 + params.ne2 * theta_base_mult]) * pow(params.theta_scale, f32(theta_scale_pwr));
let thetas = rope_yarn(theta_base/freq_factor(i0), i0);
let thetas = rope_yarn(theta_base/freq_factor(iw), iw);
let i_src = i_src_row + pair_base(i0, is_neox || is_mrope || is_vision);
let i_dst = i_dst_row + pair_base(i0, is_neox || is_mrope || is_vision);
+2 -2
View File
@@ -86,6 +86,6 @@ endif()
target_link_libraries(ggml-zendnn PRIVATE m pthread)
if (GGML_OPENMP)
target_link_libraries(ggml-zendnn PRIVATE OpenMP::OpenMP_CXX)
if (GGML_OPENMP_ENABLED)
target_link_libraries(ggml-zendnn PRIVATE ${GGML_OPENMP_TARGET_CXX})
endif()
+2
View File
@@ -1032,6 +1032,8 @@ bool llm_arch_supports_rs_rollback(const llm_arch & arch) {
case LLM_ARCH_DEEPSEEK4:
case LLM_ARCH_NEMOTRON_H:
case LLM_ARCH_NEMOTRON_H_MOE:
case LLM_ARCH_LFM2:
case LLM_ARCH_LFM2MOE:
return true;
default:
return false;
+1 -3
View File
@@ -3099,8 +3099,6 @@ ggml_tensor * llm_graph_context::build_attn(
int il) const {
const bool is_swa = hparams.is_swa(il);
GGML_UNUSED(v_cur);
auto * k_rot = is_swa ? inp->self_k_rot_swa : inp->self_k_rot;
if (k_rot) {
@@ -3133,7 +3131,7 @@ ggml_tensor * llm_graph_context::build_attn(
// MLA-style attention: the cached K is used as V
ggml_tensor * q = q_cur;
ggml_tensor * k = mctx_cur->get_k(ctx0, il);
ggml_tensor * v = k;
ggml_tensor * v = ggml_view_4d(ctx0, k, v_cur->ne[0], k->ne[1], k->ne[2], k->ne[3], k->nb[1], k->nb[2], k->nb[3], 0);
ggml_tensor * cur = build_attn_mha(q, k, v, kq_b, kq_mask, sinks, v_mla, kq_scale, il);
cb(cur, "kqv_out", il);
+1 -1
View File
@@ -1225,7 +1225,7 @@ ggml_tensor * llama_model_deepseek4::graph::build_attention_impl(
if (inp_mtp) {
out = build_attn(inp_mtp,
nullptr, nullptr, nullptr,
q, kv, nullptr,
q, kv, kv,
nullptr, layer.attn_sinks, nullptr,
1.0f/sqrtf(float(n_embd_head)), il);
cb(out, "attn_raw", il);
+17 -8
View File
@@ -2,6 +2,8 @@
#include "../llama-memory-hybrid-iswa.h"
#include "../llama-memory-hybrid.h"
#include <algorithm>
void llama_model_lfm2::load_arch_hparams(llama_model_loader & ml) {
ml.get_key(LLM_KV_SHORTCONV_L_CACHE, hparams.n_shortconv_l_cache);
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
@@ -202,15 +204,20 @@ llama_model_lfm2::graph<iswa>::graph(const llama_model & model, const llm_graph_
}
GGML_ASSERT(bx->ne[0] > conv->ne[0]);
// last d_conv columns is a new conv state
auto * new_conv = ggml_view_3d(ctx0, bx, conv->ne[0], bx->ne[1], bx->ne[2], bx->nb[1], bx->nb[2],
(bx->ne[0] - conv->ne[0]) * ggml_element_size(bx));
GGML_ASSERT(ggml_are_same_shape(conv, new_conv));
// write conv states: slot 0 = the final state, slot s = the state s tokens back (partial rollback)
const int64_t K = hparams.causal_attn && cparams.n_rs_seq > 0 ? (int64_t) cparams.n_rs_seq + 1 : 1;
const int64_t n_written = std::min<int64_t>(n_seq_tokens, K);
const auto mem_size = mctx_cur->get_size();
const size_t row_size = ggml_row_size(conv_state->type, (int64_t) d_conv * n_embd);
// write new conv conv state
ggml_build_forward_expand(gf, ggml_cpy(ctx0, new_conv,
ggml_view_1d(ctx0, conv_state, ggml_nelements(new_conv),
kv_head * d_conv * n_embd * ggml_element_size(new_conv))));
for (int64_t slot = 0; slot < n_written; ++slot) {
auto * conv_snap = ggml_view_3d(ctx0, bx, d_conv, bx->ne[1], bx->ne[2], bx->nb[1], bx->nb[2],
(bx->ne[0] - d_conv - slot) * ggml_element_size(bx));
ggml_build_forward_expand(gf, ggml_cpy(ctx0, conv_snap,
ggml_view_2d(ctx0, conv_state, (int64_t) d_conv * n_embd, n_seqs,
conv_state->nb[1],
((size_t) slot * mem_size + kv_head) * row_size)));
}
auto * conv_kernel = model.layers[il].shortconv.conv;
auto * conv_out = ggml_ssm_conv(ctx0, bx, conv_kernel);
@@ -242,6 +249,8 @@ llama_model_lfm2::graph<iswa>::graph(const llama_model & model, const llm_graph_
ggml_tensor * inp_out_ids = build_inp_out_ids();
for (int il = 0; il < n_layer; ++il) {
res->t_layer_inp[il] = cur;
const bool is_moe_layer = il >= static_cast<int>(hparams.n_layer_dense_lead);
auto * prev_cur = cur;
+37
View File
@@ -9298,6 +9298,14 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_Q8_0, GGML_TYPE_F32, 6, 4096, 5120, {1, 1}, {1, 1}));
// K not a multiple of 32
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F16, 64, 32, 65, {1, 1}, {1, 1}));
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F16, 64, 32, 80, {1, 1}, {1, 1}));
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F32, 64, 32, 80, {1, 1}, {1, 1}));
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F32, GGML_TYPE_F32, 64, 32, 80, {1, 1}, {1, 1}));
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F16, 64, 32, 588, {1, 1}, {1, 1})); // 14*14*3, e.g. conv_2d im2col
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F16, 64, 32, 80, {4, 1}, {1, 1}));
#if 0
// test the mat-mat path for Metal
for (int k = 1; k < 512; ++k) {
@@ -9934,6 +9942,20 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
test_cases.emplace_back(new test_flash_attn_ext(64, 128, 4, {1, 1}, 128, 2, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q4_0, GGML_TYPE_Q2_0));
test_cases.emplace_back(new test_flash_attn_ext(128, 64, 4, {1, 1}, 64, 2, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q2_0, GGML_TYPE_F16));
// q8_0 KV cases: decode and prompt batches, KV pad, permuted KV, feature flags, and long context
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 113, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 1024, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 1024, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0, {0, 2, 1, 3}));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 2}, 1025, 1, true, true, 8, 30, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 1025, 64, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0, {0, 2, 1, 3}));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 16384, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
// MLA shape (V is a view of K) with quantized KV
// (the test harness builds V as a view of K for this shape; see build_graph)
test_cases.emplace_back(new test_flash_attn_ext(576, 512, 1, {20, 1}, 113, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(576, 512, 1, {20, 1}, 1024, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(576, 512, 1, {20, 1}, 1024, 64, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
// large-KV F16 cases (Qwen3.6-27B geometry and a llama-class control): the upstream matrix
// stops at kv=1024, blind to long-context FA bugs (e.g. the oneDNN SDPA ordering race on BMG).
for (int64_t kv : { 4096, 16384 }) {
@@ -10325,6 +10347,21 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_perf() {
test_cases.emplace_back(new test_flash_attn_ext(64, 64, 8, {8, 1}, 7680, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(64, 64, 8, {8, 1}, 7680, 512, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
// q8_0 KV cases with long context (decode and prompt)
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 128, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 512, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 1024, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 2048, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 4096, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 10000, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 20000, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 10000, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_F16, GGML_TYPE_F16));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 20000, 1, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_F16, GGML_TYPE_F16));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 10000, 512, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 20000, 512, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_Q8_0, GGML_TYPE_Q8_0));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 10000, 512, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_F16, GGML_TYPE_F16));
test_cases.emplace_back(new test_flash_attn_ext(256, 256, 2, {16, 1}, 20000, 512, true, false, 0, 0, GGML_PREC_F32, GGML_TYPE_F16, GGML_TYPE_F16));
for (int kv : { 4096, 8192, 16384, }) {
for (int hs : { 64, 128, }) {
for (int nr : { 1, 4, }) {
+64
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@@ -1564,6 +1564,70 @@ int main() {
space ::= | " " | "\n"{1,2} [ \t]{0,20}
)""",
});
run({
SUCCESS,
"unanchored regexp",
R"""({
"type": "string",
"pattern": "[0-9]+"
})""",
R"""(
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
root ::= string
space ::= | " " | "\n"{1,2} [ \t]{0,20}
string ::= "\"" char* "\""
)""",
});
// the rules of the partial conversion (here "root-0") must not leak into the grammar
run({
SUCCESS,
"regexp with unsupported shorthand",
R"""({
"type": "string",
"pattern": "^[0-9]{3}\\w$"
})""",
R"""(
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
root ::= string
space ::= | " " | "\n"{1,2} [ \t]{0,20}
string ::= "\"" char* "\""
)""",
});
// a regexp that is invalid under any flavor is still an error
run({
FAILURE,
"regexp with unbalanced parentheses",
R"""({
"type": "string",
"pattern": "^(a$"
})""",
""
});
// only the property with the bad pattern degrades
run({
SUCCESS,
"unsupported regexp in a property",
R"""({
"type": "object",
"properties": {
"a": { "type": "string", "pattern": "^[a-z\\-]+$" }
},
"required": ["a"],
"additionalProperties": false
})""",
R"""(
a ::= string
a-kv ::= "\"a\"" space ":" space a
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
root ::= "{" space a-kv space "}"
space ::= | " " | "\n"{1,2} [ \t]{0,20}
string ::= "\"" char* "\""
)""",
});
}
if (getenv("LLAMA_SKIP_TESTS_SLOW_ON_EMULATOR")) {
+1
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@@ -162,6 +162,7 @@
| `-mmu, --mmproj-url URL` | URL to a multimodal projector file. see tools/mtmd/README.md<br/>(env: LLAMA_ARG_MMPROJ_URL) |
| `--mmproj-auto, --no-mmproj, --no-mmproj-auto` | whether to use multimodal projector file (if available), useful when using -hf (default: enabled)<br/>(env: LLAMA_ARG_MMPROJ_AUTO) |
| `--mmproj-offload, --no-mmproj-offload` | whether to enable GPU offloading for multimodal projector (default: enabled)<br/>(env: LLAMA_ARG_MMPROJ_OFFLOAD) |
| `-mmdev, --mmproj-device DEVICE` | device to use for multimodal projector (none = don't offload, default: auto)<br/>use --list-devices to see a list of available devices<br/>(env: MTMD_BACKEND_DEVICE) |
| `--image, --audio, --video FILE` | path to an image, audio, or video file. use with multimodal models, use comma-separated values for multiple files |
| `--image-min-tokens N` | minimum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)<br/>(env: LLAMA_ARG_IMAGE_MIN_TOKENS) |
| `--image-max-tokens N` | maximum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)<br/>(env: LLAMA_ARG_IMAGE_MAX_TOKENS) |
+5 -6
View File
@@ -186,14 +186,13 @@ struct clip_ctx {
throw std::runtime_error("failed to initialize CPU backend");
}
if (ctx_params.use_gpu) {
auto * backend_name = std::getenv("MTMD_BACKEND_DEVICE");
if (backend_name != nullptr) {
backend = ggml_backend_init_by_name(backend_name, nullptr);
if (ctx_params.device != nullptr) {
backend = ggml_backend_dev_init(ctx_params.device, nullptr);
if (!backend) {
LOG_WRN("%s: Warning: Failed to initialize \"%s\" backend, falling back to default GPU backend\n", __func__, backend_name);
throw std::runtime_error(string_format("%s: failed to initialize \"%s\" backend\n",
__func__, ggml_backend_dev_name(ctx_params.device)));
}
}
if (!backend) {
} else {
backend = ggml_backend_init_by_type(GGML_BACKEND_DEVICE_TYPE_GPU, nullptr);
backend = backend ? backend : ggml_backend_init_by_type(GGML_BACKEND_DEVICE_TYPE_IGPU, nullptr);
}
+1
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@@ -48,6 +48,7 @@ enum clip_flash_attn_type {
struct clip_context_params {
bool use_gpu;
ggml_backend_dev_t device;
enum clip_flash_attn_type flash_attn_type;
int image_min_tokens;
int image_max_tokens;
+1
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@@ -84,6 +84,7 @@ int main(int argc, char ** argv) {
const char * clip_path = params.mmproj.path.c_str();
mtmd_context_params mparams = mtmd_context_params_default();
mparams.use_gpu = params.mmproj_use_gpu;
mparams.device = params.mmproj_device;
mparams.print_timings = true;
mparams.n_threads = params.cpuparams.n_threads;
mparams.flash_attn_type = params.flash_attn_type;
+1
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@@ -154,6 +154,7 @@ struct mtmd_cli_context {
const char * clip_path = params.mmproj.path.c_str();
mtmd_context_params mparams = mtmd_context_params_default();
mparams.use_gpu = params.mmproj_use_gpu;
mparams.device = params.mmproj_device;
mparams.print_timings = true;
mparams.n_threads = params.cpuparams.n_threads;
mparams.flash_attn_type = params.flash_attn_type;
+2
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@@ -456,6 +456,7 @@ static clip_flash_attn_type mtmd_get_clip_flash_attn_type(enum llama_flash_attn_
mtmd_context_params mtmd_context_params_default() {
mtmd_context_params params {
/* use_gpu */ true,
/* device */ nullptr,
/* print_timings */ true,
/* n_threads */ 4,
/* image_marker */ nullptr,
@@ -564,6 +565,7 @@ struct mtmd_context {
clip_context_params ctx_clip_params {
/* use_gpu */ ctx_params.use_gpu,
/* device */ ctx_params.device,
/* flash_attn_type */ mtmd_get_clip_flash_attn_type(ctx_params.flash_attn_type),
/* image_min_tokens */ ctx_params.image_min_tokens,
/* image_max_tokens */ ctx_params.image_max_tokens,
+1
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@@ -89,6 +89,7 @@ typedef bool (*mtmd_progress_callback)(float progress, void * user_data);
struct mtmd_context_params {
bool use_gpu;
ggml_backend_dev_t device;
bool print_timings;
int n_threads;
const char * image_marker; // deprecated, use media_marker instead
+4 -3
View File
@@ -178,6 +178,7 @@ For the full list of features, please refer to [server's changelog](https://gith
| `-mmu, --mmproj-url URL` | URL to a multimodal projector file. see tools/mtmd/README.md<br/>(env: LLAMA_ARG_MMPROJ_URL) |
| `--mmproj-auto, --no-mmproj, --no-mmproj-auto` | whether to use multimodal projector file (if available), useful when using -hf (default: enabled)<br/>(env: LLAMA_ARG_MMPROJ_AUTO) |
| `--mmproj-offload, --no-mmproj-offload` | whether to enable GPU offloading for multimodal projector (default: enabled)<br/>(env: LLAMA_ARG_MMPROJ_OFFLOAD) |
| `-mmdev, --mmproj-device DEVICE` | device to use for multimodal projector (none = don't offload, default: auto)<br/>use --list-devices to see a list of available devices<br/>(env: MTMD_BACKEND_DEVICE) |
| `--image-min-tokens N` | minimum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)<br/>(env: LLAMA_ARG_IMAGE_MIN_TOKENS) |
| `--image-max-tokens N` | maximum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)<br/>(env: LLAMA_ARG_IMAGE_MAX_TOKENS) |
| `--mtmd-batch-max-tokens N` | maximum number of image tokens per batch when encoding images (default: 1024)<br/>(env: LLAMA_ARG_MTMD_BATCH_MAX_TOKENS) |
@@ -196,11 +197,11 @@ For the full list of features, please refer to [server's changelog](https://gith
| `--ui-config, --webui-config JSON` | JSON that provides default UI settings (overrides UI defaults)<br/>(env: LLAMA_ARG_UI_CONFIG) |
| `--ui-config-file, --webui-config-file PATH` | JSON file that provides default UI settings (overrides UI defaults)<br/>(env: LLAMA_ARG_UI_CONFIG_FILE) |
| `--ui-mcp-proxy, --webui-mcp-proxy, --no-ui-mcp-proxy, --no-webui-mcp-proxy` | experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: disabled)<br/>(env: LLAMA_ARG_UI_MCP_PROXY) |
| `--tools TOOL1,TOOL2,...` | experimental: whether to enable server tools for AI agents - do not enable in untrusted environments (default: no tools)<br/>specify "all" to enable all tools<br/>available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, get_info<br/>note: for security reasons, this will limit --cors-origins to localhost by default<br/>(env: LLAMA_ARG_TOOLS) |
| `--tools TOOL1,TOOL2,...` | experimental: whether to enable built-in tools for AI agents - do not enable in untrusted environments (default: no tools)<br/>specify "all" to enable all tools<br/>available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, get_info<br/>note: for security reasons, this will limit --cors-origins to localhost by default<br/>(env: LLAMA_ARG_TOOLS) |
| `--tools-runtime OPTION` | experimental: run tools in a separate runtime environment (default: none, use host environment)<br/>available options:<br/> 'docker:<image>', 'podman:<image>': spin up a new container and reuse it for all invocations, clean up on server exit<br/> 'docker-container:<id>', 'podman-container:<id>': use an existing container by ID, won't stop on server exit<br/> 'ssh:<target>': run tools on a remote POSIX host over SSH, key-based auth and a trusted host key are required<br/><br/>(env: LLAMA_ARG_TOOLS_RUNTIME) |
| `--mcp-servers-config PATH` | experimental: path to JSON file with MCP server definitions (Cursor-compatible format) - do not enable in untrusted environments (default: none)<br/>note: for security reasons, this will limit --cors-origins to localhost by default<br/>(env: LLAMA_ARG_MCP_SERVERS_CONFIG) |
| `--mcp-servers-json JSON` | experimental: inline JSON with MCP server definitions (Cursor-compatible format) - do not enable in untrusted environments (default: none)<br/>note: for security reasons, this will limit --cors-origins to localhost by default<br/>(env: LLAMA_ARG_MCP_SERVERS_JSON) |
| `-ag, --agent, -no-ag, --no-agent` | whether to enable CORS proxy and all server tools - do not enable in untrusted environments (default: disabled)<br/>note: for security reasons, this will limit --cors-origins to localhost by default<br/>(env: LLAMA_ARG_AGENT) |
| `-ag, --agent, -no-ag, --no-agent` | whether to enable CORS proxy and all built-in tools - do not enable in untrusted environments (default: disabled)<br/>note: for security reasons, this will limit --cors-origins to localhost by default<br/>(env: LLAMA_ARG_AGENT) |
| `--ui, --webui, --no-ui, --no-webui` | whether to enable the Web UI (default: enabled)<br/>(env: LLAMA_ARG_UI) |
| `--embedding, --embeddings` | restrict to only support embedding use case; use only with dedicated embedding models (default: disabled)<br/>(env: LLAMA_ARG_EMBEDDINGS) |
| `--rerank, --reranking` | enable reranking endpoint on server (default: disabled)<br/>(env: LLAMA_ARG_RERANKING) |
@@ -1757,7 +1758,7 @@ The precedence rule for preset options is as follows:
3. **Global options** defined in the preset file (`[*]`)
We also offer additional options that are exclusive to presets (these aren't treated as command-line arguments):
- `load-on-startup` (boolean): Controls whether the model loads automatically when the server starts
- `load-on-startup` (boolean): Controls whether the model loads automatically when the server starts. Only applies at startup: if the model list is reloaded later (for example after editing the preset file), a newly added model is listed but not loaded
- `stop-timeout` (int, seconds): After requested unload, wait for this many seconds before forcing termination (default: 10)
- `dedup-cache-models` (boolean): When the preset uses `hf-repo` pointing to a model that is already downloaded, hide the corresponding cached model entry from `GET /models` (the preset entry remains visible). Set it in the `[*]` section to apply to all presets.
+1
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@@ -998,6 +998,7 @@ private:
mtmd_context_params mparams = mtmd_context_params_default();
if (has_mmproj) {
mparams.use_gpu = params_base.mmproj_use_gpu;
mparams.device = params_base.mmproj_device;
mparams.print_timings = false;
mparams.n_threads = params_base.cpuparams.n_threads;
mparams.flash_attn_type = params_base.flash_attn_type;
+35 -35
View File
@@ -672,24 +672,26 @@ void server_models::load_models() {
apply_hidden();
log_available_models();
std::vector<std::string> models_to_load;
for (const auto & [name, inst] : mapping) {
std::string val;
if (inst.meta.preset.get_option(COMMON_ARG_PRESET_LOAD_ON_STARTUP, val) && common_arg_utils::is_truthy(val)) {
models_to_load.push_back(name);
// skipped on reload, see startup_models
if (startup_models.has_value()) {
std::vector<std::string> models_to_load;
for (const auto & [name, inst] : mapping) {
std::string val;
if (inst.meta.preset.get_option(COMMON_ARG_PRESET_LOAD_ON_STARTUP, val) && common_arg_utils::is_truthy(val)) {
models_to_load.push_back(name);
}
}
}
if ((int)models_to_load.size() > base_params.models_max) {
throw std::runtime_error(string_format(
"number of models to load on startup (%zu) exceeds models_max (%d)",
models_to_load.size(), base_params.models_max));
if ((int)models_to_load.size() > base_params.models_max) {
throw std::runtime_error(string_format(
"number of models to load on startup (%zu) exceeds models_max (%d)",
models_to_load.size(), base_params.models_max));
}
// to be lazy-loaded after main() setup phase is completed
startup_models = std::move(models_to_load);
}
lk.unlock();
for (const auto & name : models_to_load) {
SRV_INF("(startup) loading model %s\n", name.c_str());
load(name);
}
} else {
// RELOAD: diff the new preset list against the current mapping and reconcile
is_reloading = true;
@@ -819,8 +821,8 @@ void server_models::load_models() {
inst.meta.update_caps();
}
// add models that are new in this reload
std::vector<std::string> newly_added;
// add models that are new in this reload, load-on-startup is not honored here since a
// reload never spawns an instance
for (const auto & [name, preset] : final_presets) {
if (mapping.find(name) == mapping.end()) {
server_model_meta meta{
@@ -841,42 +843,40 @@ void server_models::load_models() {
// /* need_download */ false,
};
add_model(std::move(meta));
newly_added.push_back(name);
}
}
apply_stop_timeout();
apply_hidden();
// clear reload flag before unlocking for autoload - load() blocks on !is_reloading,
// so clearing it here (while still locked) prevents a deadlock in the autoload calls below
// clear reload flag under the lock, this releases the load() calls waiting on !is_reloading
is_reloading = false;
cv.notify_all();
log_available_models();
// collect autoload candidates while still under the lock
std::vector<std::string> to_autoload;
for (const auto & name : newly_added) {
auto it = mapping.find(name);
if (it != mapping.end()) {
std::string val;
if (it->second.meta.preset.get_option(COMMON_ARG_PRESET_LOAD_ON_STARTUP, val) && common_arg_utils::is_truthy(val)) {
to_autoload.push_back(name);
}
}
}
lk.unlock();
for (const auto & name : to_autoload) {
SRV_INF("(reload) loading new model %s\n", name.c_str());
load(name);
}
notify_sse("models_reload", "*");
}
}
void server_models::load_startup_models() {
std::vector<std::string> to_load;
{
std::lock_guard<std::mutex> lk(mutex);
if (!startup_models.has_value()) {
return; // already drained
}
to_load = std::move(*startup_models);
startup_models.reset();
}
for (const auto & name : to_load) {
SRV_INF("(startup) loading model %s\n", name.c_str());
load(name);
}
}
void server_models::update_meta(const std::string & name, const server_model_meta & meta) {
std::lock_guard<std::mutex> lk(mutex);
auto it = mapping.find(name);
+7
View File
@@ -136,6 +136,10 @@ private:
// if true, the next get_meta() will trigger a reload of model list
bool need_reload = false;
// models marked with load-on-startup, unset once load_startup_models() drains it
// no value means the startup phase is over, so a reload must not queue anything
std::optional<std::vector<std::string>> startup_models{std::in_place};
// conv_id -> model name that currently serves its stream session, lets the resumable stream
// routes go straight to the owning child instead of polling every one. populated when
// proxy_request forwards a POST carrying an X-Conversation-Id. best effort: a stale entry just
@@ -231,6 +235,9 @@ public:
// - if a model is not running, it will be added or updated according to the source
void load_models();
// lazy-load startup_models, to be called after main() setup phase
void load_startup_models();
// check if a model instance exists (thread-safe)
bool has_model(const std::string & name);
+14 -1
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@@ -133,7 +133,8 @@ int llama_server(common_params & params, int argc, char ** argv) {
// router server never loads a model and must not touch the GPU
const bool is_router_server = params.model.path.empty()
&& params.model.hf_repo.empty();
&& params.model.hf_repo.empty()
&& params.model.docker_repo.empty();
// skip device enumeration so the CUDA primary context stays uncreated
common_params_print_info(params, !is_router_server);
@@ -423,6 +424,18 @@ int llama_server(common_params & params, int argc, char ** argv) {
ctx_http.stop();
};
try {
models_routes->models.load_startup_models();
} catch (const std::exception & e) {
SRV_ERR("failed to load models on startup: %s\n", e.what());
ctx_http.stop();
if (ctx_http.thread.joinable()) {
ctx_http.thread.join();
}
clean_up();
return 1;
}
} else {
// setup clean up function, to be called before exit
clean_up = [&ctx_http, &ctx_server, &mcp_mgr]() {
+1
View File
@@ -86,6 +86,7 @@ int main(int argc, char ** argv) {
mtmd_context_params mtmd_params = mtmd_context_params_default();
mtmd_params.use_gpu = params.mmproj_use_gpu;
mtmd_params.device = params.mmproj_device;
mtmd::context_ptr mctx(mtmd_init_from_file(params.mmproj.path.c_str(), model, mtmd_params));
if (!mctx) {
LOG_ERR("failed to load mmproj %s\n", params.mmproj.path.c_str());
+106 -60
View File
@@ -239,31 +239,44 @@ Routes → Components → Hooks → Stores → Services → Storage/API
### High-Level Architecture
See: [`docs/architecture/high-level-architecture-simplified.md`](docs/architecture/high-level-architecture-simplified.md)
```mermaid
flowchart TB
subgraph Routes["📍 Routes"]
R1["/ (Welcome)"]
R2["/chat/[id]"]
R3["/mcp-servers"]
R4["/search"]
R5["/settings"]
RL["+layout.svelte"]
end
subgraph Components["🧩 Components"]
C_Sidebar["ChatSidebar"]
C_Screen["ChatScreen"]
C_Form["ChatForm"]
C_Messages["ChatMessages"]
C_ModelsSelector["ModelsSelector"]
C_Sidebar["ChatSidebar"]
C_Models["ModelsSelector"]
C_Settings["ChatSettings"]
C_Mcp["McpServers"]
end
subgraph Hooks["🔌 Hooks"]
H1["use-chat-screen-active-model"]
H2["use-processing-state"]
H3["use-context-gauge"]
H4["use-models-selector"]
H5["use-tools-panel"]
end
subgraph Stores["🗄️ Stores"]
S1["chatStore"]
S2["conversationsStore"]
S3["modelsStore"]
S4["serverStore"]
S5["settingsStore"]
S4["mcpStore"]
S5["agenticStore"]
S6["serverStore"]
S7["settingsStore"]
S8["toolsStore"]
end
subgraph Services["⚙️ Services"]
@@ -271,6 +284,9 @@ flowchart TB
SV2["ModelsService"]
SV3["PropsService"]
SV4["DatabaseService"]
SV5["MCPService"]
SV6["ToolsService"]
SV7["SandboxService"]
end
subgraph Storage["💾 Storage"]
@@ -282,19 +298,28 @@ flowchart TB
API1["/v1/chat/completions"]
API2["/props"]
API3["/models/*"]
API4["/tools"]
end
R1 & R2 --> C_Screen
RL --> C_Sidebar
C_Screen --> C_Form & C_Messages & C_Settings
C_Screen --> S1 & S2
C_ModelsSelector --> S3 & S4
C_Screen --> H1 & H2 & H3
C_Models --> H4
C_Mcp --> S4
C_Screen --> S1 & S2 & S3
C_Models --> S3
H1 --> S3
S1 --> SV1 & SV4
S2 --> SV4
S3 --> SV2 & SV3
S4 --> SV5
S5 --> SV1 & SV5 & SV6 & SV7
SV4 --> ST1
SV1 --> API1
SV2 --> API3
SV3 --> API2
SV6 --> API4
```
### Layer Breakdown
@@ -303,6 +328,9 @@ flowchart TB
- **`/`** - Welcome screen, creates new conversation
- **`/chat/[id]`** - Active chat interface
- **`/mcp-servers`** - MCP server management
- **`/search`** - Conversation search
- **`/settings`** - Settings (optional `[[section]]`)
- **`+layout.svelte`** - Sidebar, navigation, global initialization
#### Components (`src/lib/components/`)
@@ -348,28 +376,68 @@ Components are organized in `app/` (application-specific) and `ui/` (shadcn-svel
#### Hooks (`src/lib/hooks/`)
- **`useModelChangeValidation`** - Validates model switch against conversation modalities
- **`useProcessingState`** - Tracks streaming progress and token generation
Hooks are the thin view-layer between components and stores: they own UI concerns (scroll, drag-and-drop, keyboard shortcuts, pickers, selection) and translate store state into view state.
| Hook | Responsibility |
| ------------------------------- | -------------------------------------------------------------- |
| `use-chat-screen-active-model` | Active model resolution + modality capability detection |
| `use-processing-state` | View over `chatStore.processing` for streaming progress/tokens |
| `use-context-gauge` | View over `contextStatsStore` for the context usage gauge |
| `use-models-selector` | Model selector dropdown state (loaded/available groups) |
| `use-tools-panel` | Tools panel state |
| `use-reasoning-menu` | Reasoning-effort menu state |
| `use-attachment-menu` | Attachment menu + modality flags |
| `use-draft-messages` | Per-chat draft message/files persistence |
| `use-chat-form-pickers` | Chat form pickers (commands, mentions) |
| `use-debounced-search` | Shared debounced async search for pickers |
| `use-picker-navigation` | Picker keyboard navigation |
| `use-chat-message-edit-context` | Message edit context (content + extras) |
| `use-chat-screen-drag-and-drop` | Drag-and-drop state machine |
| `use-chat-screen-file-upload` | File upload queue + capability validation |
| `use-chat-screen-scroll` | Scroll container binding + navigation guard |
| `use-auto-scroll` | Auto-scroll controller for streaming |
| `use-marquee-selection` | Shift+click / marquee range selection |
| `use-keyboard-shortcuts` | Global keyboard shortcuts |
| `use-settings-navigation` | Settings section navigation |
| `use-pwa` | PWA install/update + version mismatch detection |
#### Stores (`src/lib/stores/`)
| Store | Responsibility |
| -------------------- | --------------------------------------------------------- |
| `chatStore` | Message sending, streaming, abort control, error handling |
| `conversationsStore` | CRUD for conversations, message branching, navigation |
| `modelsStore` | Model list, selection, loading/unloading (ROUTER) |
| `serverStore` | Server properties, role detection, modalities |
| `settingsStore` | User preferences, parameter sync with server defaults |
Stores own reactive application state as Svelte 5 runes. Larger stores are split into directories and compose focused sub-stores behind a narrow host interface (see Architectural Patterns).
| Store | Responsibility |
| -------------------- | --------------------------------------------------------------------------------------------------------------- |
| `chatStore` | Chat lifecycle, streaming, abort control, error handling; composes `processing`, `activity`, `streams`, `flows` |
| `conversationsStore` | Conversation CRUD, message branching, navigation, import/export; composes `preferences` |
| `modelsStore` | Model list, selection, loading/unloading (ROUTER); composes `props`, `status` |
| `mcpStore` | MCP host role: multi-server lifecycle, tool routing; composes `health`, `resources` |
| `agenticStore` | Multi-turn agentic loop orchestration, tool execution; composes `gates` |
| `serverStore` | Server connection state, `/props`, role detection, modalities |
| `settingsStore` | User preferences, theme, parameter sync with server defaults |
| `toolsStore` | Tool registry: server + MCP tools, enabled set for the LLM |
| `permissionsStore` | Persisted tool permission grants |
| `contextStatsStore` | Context window usage for the active conversation |
| `draftMessagesStore` | Per-chat draft message/files |
| `deviceStore` | Browser environment signals (mobile, OS, theme) |
| `versionStore` | Build version information |
#### Services (`src/lib/services/`)
| Service | Responsibility |
| ---------------------- | ----------------------------------------------- |
| `ChatService` | API calls to`/v1/chat/completions`, SSE parsing |
| `ModelsService` | `/models`, `/models/load`, `/models/unload` |
| `PropsService` | `/props`, `/props?model=` |
| `DatabaseService` | IndexedDB operations via Dexie |
| `ParameterSyncService` | Syncs settings with server defaults |
Services are a stateless protocol layer: static methods, pure I/O, no reactive state. Stores consume them for all API and storage access.
| Service | Responsibility |
| ----------------------------- | ------------------------------------------------------------------------- |
| `ChatService` | `/v1/chat/completions` streaming + SSE parsing, message format conversion |
| `ModelsService` | `/models`, `/models/load`, `/models/unload` |
| `PropsService` | `/props`, `/props?model=` |
| `DatabaseService` | IndexedDB operations via Dexie |
| `MCPService` | MCP protocol: transports, connect, list/execute tools, prompts, resources |
| `ToolsService` | Server tool list/execute/stream (`/tools`) |
| `SandboxService` | Browser JS execution in a sandboxed worker |
| `ParameterSyncService` | Syncs settings with server defaults |
| `ConversationTransferService` | Conversation import/export JSONL + ZIP format |
| `MigrationService` | Non-destructive localStorage/IndexedDB migrations |
| `RouterService` | Dynamic route URL construction |
---
@@ -377,8 +445,6 @@ Components are organized in `app/` (application-specific) and `ui/` (shadcn-svel
### MODEL Mode (Single Model)
See: [`docs/flows/data-flow-simplified-model-mode.md`](docs/flows/data-flow-simplified-model-mode.md)
```mermaid
sequenceDiagram
participant User
@@ -388,8 +454,9 @@ sequenceDiagram
participant API as llama-server
Note over User,API: Initialization
UI->>Stores: initialize()
Stores->>DB: load conversations
UI->>Stores: initStores() (awaited by route loads)
Stores->>Stores: run migrations
Stores->>DB: load conversations (background)
Stores->>API: GET /props
API-->>Stores: server config
Stores->>API: GET /v1/models
@@ -408,8 +475,6 @@ sequenceDiagram
### ROUTER Mode (Multi-Model)
See: [`docs/flows/data-flow-simplified-router-mode.md`](docs/flows/data-flow-simplified-router-mode.md)
```mermaid
sequenceDiagram
participant User
@@ -441,17 +506,6 @@ sequenceDiagram
end
```
### Detailed Flow Diagrams
| Flow | Description | File |
| ------------- | ------------------------------------------ | ----------------------------------------------------------- |
| Chat | Message lifecycle, streaming, regeneration | [`chat-flow.md`](docs/flows/chat-flow.md) |
| Models | Loading, unloading, modality caching | [`models-flow.md`](docs/flows/models-flow.md) |
| Server | Props fetching, role detection | [`server-flow.md`](docs/flows/server-flow.md) |
| Conversations | CRUD, branching, import/export | [`conversations-flow.md`](docs/flows/conversations-flow.md) |
| Database | IndexedDB schema, operations | [`database-flow.md`](docs/flows/database-flow.md) |
| Settings | Parameter sync, user overrides | [`settings-flow.md`](docs/flows/settings-flow.md) |
---
## Architectural Patterns
@@ -505,13 +559,14 @@ Components dispatch actions to stores, stores coordinate with services for I/O,
### 3. Per-Conversation State
Enables concurrent streaming across multiple conversations:
Enables concurrent streaming across multiple conversations. Loading is tracked
per conversation by the activity ledger (`chatStore.activity`), while streaming
state and abort controllers live in per-conversation maps:
```typescript
class ChatStore {
chatLoadingStates = new Map<string, boolean>();
chatStreamingStates = new Map<string, { response: string; messageId: string }>();
abortControllers = new Map<string, AbortController>();
chatStreamingStates = new SvelteMap<string, { response: string; messageId: string }>();
abortControllers = new SvelteMap<string, AbortController>();
}
```
@@ -567,20 +622,14 @@ get isRouterMode() {
### 7. Modality Validation
Prevents sending attachments to incompatible models:
Prevents sending attachments to incompatible models. The
`use-chat-screen-active-model` hook derives the active model's capabilities
from `modelsStore.props`:
```typescript
// useModelChangeValidation hook
const validate = (modelId: string) => {
const modelModalities = modelsStore.getModelModalities(modelId);
const conversationModalities = conversationsStore.usedModalities;
// Check if model supports all used modalities
if (conversationModalities.hasImages && !modelModalities.vision) {
return { valid: false, reason: 'Model does not support images' };
}
// ...
};
// use-chat-screen-active-model hook
const hasVisionModality = $derived.by(() => modelsStore.props.modelSupportsVision(activeModelId));
const hasAudioModality = $derived.by(() => modelsStore.props.modelSupportsAudio(activeModelId));
```
### 8. Persistent Storage Strategy
@@ -673,9 +722,6 @@ tools/ui/
│ └── styles/ # Global styles
├── static/ # Static assets
├── tests/ # Test files
├── docs/ # Architecture diagrams
│ ├── architecture/ # High-level architecture
│ └── flows/ # Feature-specific flows
└── .storybook/ # Storybook configuration
```
@@ -1,145 +0,0 @@
```mermaid
flowchart TB
subgraph Routes["📍 Routes"]
R1["/ (Welcome)"]
R2["/chat/[id]"]
RL["+layout.svelte"]
end
subgraph Components["🧩 Components"]
C_Sidebar["ChatSidebar"]
C_Screen["ChatScreen"]
C_Form["ChatForm"]
C_Messages["ChatMessages"]
C_Message["ChatMessage"]
C_ChatMessageAgenticContent["ChatMessageAgenticContent"]
C_MessageEditForm["ChatMessageEditForm"]
C_ModelsSelector["ModelsSelector"]
C_Settings["ChatSettings"]
C_McpSettings["McpServersSettings"]
C_McpResourceBrowser["McpResourceBrowser"]
C_McpServersSelector["McpServersSelector"]
end
subgraph Hooks["🪝 Hooks"]
H1["useModelChangeValidation"]
H2["useProcessingState"]
end
subgraph Stores["🗄️ Stores"]
S1["chatStore<br/><i>Chat interactions & streaming</i>"]
SA["agenticStore<br/><i>Multi-turn agentic loop orchestration</i>"]
S2["conversationsStore<br/><i>Conversation data, messages & MCP overrides</i>"]
S3["modelsStore<br/><i>Model selection & loading</i>"]
S4["serverStore<br/><i>Server props & role detection</i>"]
S5["settingsStore<br/><i>User configuration incl. MCP</i>"]
S6["mcpStore<br/><i>MCP servers, tools, prompts</i>"]
S7["mcpResourceStore<br/><i>MCP resources & attachments</i>"]
end
subgraph Services["⚙️ Services"]
SV1["ChatService"]
SV2["ModelsService"]
SV3["PropsService"]
SV4["DatabaseService"]
SV5["ParameterSyncService"]
SV6["MCPService<br/><i>protocol operations</i>"]
end
subgraph Storage["💾 Storage"]
ST1["IndexedDB<br/><i>conversations, messages</i>"]
ST2["LocalStorage<br/><i>config, userOverrides, mcpServers</i>"]
end
subgraph APIs["🌐 llama-server API"]
API1["/v1/chat/completions"]
API2["/props"]
API3["/models/*"]
API4["/v1/models"]
end
subgraph ExternalMCP["🔌 External MCP Servers"]
EXT1["MCP Server 1<br/><i>WebSocket/HTTP/SSE</i>"]
EXT2["MCP Server N"]
end
%% Routes → Components
R1 & R2 --> C_Screen
RL --> C_Sidebar
%% Layout runs MCP health checks
RL --> S6
%% Component hierarchy
C_Screen --> C_Form & C_Messages & C_Settings
C_Messages --> C_Message
C_Message --> C_ChatMessageAgenticContent
C_Message --> C_MessageEditForm
C_Form & C_MessageEditForm --> C_ModelsSelector
C_Form --> C_McpServersSelector
C_Settings --> C_McpSettings
C_McpSettings --> C_McpResourceBrowser
%% Components → Hooks → Stores
C_Form & C_Messages --> H1 & H2
H1 --> S3 & S4
H2 --> S1 & S5
%% Components → Stores
C_Screen --> S1 & S2
C_Sidebar --> S2
C_ModelsSelector --> S3 & S4
C_Settings --> S5
C_McpSettings --> S6
C_McpResourceBrowser --> S6 & S7
C_McpServersSelector --> S6
C_Form --> S6
%% chatStore → agenticStore → mcpStore (agentic loop)
S1 --> SA
SA --> SV1
SA --> S6
%% Stores → Services
S1 --> SV1 & SV4
S2 --> SV4
S3 --> SV2 & SV3
S4 --> SV3
S5 --> SV5
S6 --> SV6
S7 --> SV6
%% Services → Storage
SV4 --> ST1
SV5 --> ST2
%% Services → APIs
SV1 --> API1
SV2 --> API3 & API4
SV3 --> API2
%% MCP → External Servers
SV6 --> EXT1 & EXT2
%% Styling
classDef routeStyle fill:#e1f5fe,stroke:#01579b,stroke-width:2px
classDef componentStyle fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
classDef hookStyle fill:#fff8e1,stroke:#ff8f00,stroke-width:2px
classDef storeStyle fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef serviceStyle fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px
classDef storageStyle fill:#fce4ec,stroke:#c2185b,stroke-width:2px
classDef apiStyle fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
classDef mcpStyle fill:#e0f2f1,stroke:#00695c,stroke-width:2px
classDef agenticStyle fill:#e8eaf6,stroke:#283593,stroke-width:2px
classDef externalStyle fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px,stroke-dasharray: 5 5
class R1,R2,RL routeStyle
class C_Sidebar,C_Screen,C_Form,C_Messages,C_Message,C_ChatMessageAgenticContent,C_MessageEditForm,C_ModelsSelector,C_Settings componentStyle
class C_McpSettings,C_McpResourceBrowser,C_McpServersSelector componentStyle
class H1,H2 hookStyle
class S1,S2,S3,S4,S5,SA,S6,S7 storeStyle
class SV1,SV2,SV3,SV4,SV5,SV6 serviceStyle
class ST1,ST2 storageStyle
class API1,API2,API3,API4 apiStyle
class EXT1,EXT2 externalStyle
```
@@ -1,373 +0,0 @@
```mermaid
flowchart TB
subgraph Routes["📍 Routes"]
R1["/ (+page.svelte)"]
R2["/chat/[id]"]
RL["+layout.svelte"]
end
subgraph Components["🧩 Components"]
direction TB
subgraph LayoutComponents["Layout"]
C_Sidebar["ChatSidebar"]
C_Screen["ChatScreen"]
end
subgraph ChatUIComponents["Chat UI"]
C_Form["ChatForm"]
C_Messages["ChatMessages"]
C_Message["ChatMessage"]
C_MessageUser["ChatMessageUser"]
C_MessageEditForm["ChatMessageEditForm"]
C_Attach["ChatAttachments"]
C_ModelsSelector["ModelsSelector"]
C_Settings["ChatSettings"]
end
subgraph MCPComponents["MCP UI"]
C_McpSettings["McpServersSettings"]
C_McpServerCard["McpServerCard"]
C_McpResourceBrowser["McpResourceBrowser"]
C_McpResourcePreview["McpResourcePreview"]
C_McpServersSelector["McpServersSelector"]
end
end
subgraph Hooks["🪝 Hooks"]
H1["useModelChangeValidation"]
H2["useProcessingState"]
H3["isMobile"]
end
subgraph Stores["🗄️ Stores"]
direction TB
subgraph S1["chatStore"]
S1State["<b>State:</b><br/>isLoading, currentResponse<br/>errorDialogState<br/>activeProcessingState<br/>chatLoadingStates<br/>chatStreamingStates<br/>abortControllers<br/>processingStates<br/>activeConversationId<br/>isStreamingActive"]
S1LoadState["<b>Loading State:</b><br/>setChatLoading()<br/>isChatLoading()<br/>syncLoadingStateForChat()<br/>clearUIState()<br/>isChatLoadingPublic()<br/>getAllLoadingChats()<br/>getAllStreamingChats()"]
S1ProcState["<b>Processing State:</b><br/>setActiveProcessingConversation()<br/>getProcessingState()<br/>clearProcessingState()<br/>getActiveProcessingState()<br/>updateProcessingStateFromTimings()<br/>getCurrentProcessingStateSync()<br/>restoreProcessingStateFromMessages()"]
S1Stream["<b>Streaming:</b><br/>streamChatCompletion()<br/>startStreaming()<br/>stopStreaming()<br/>stopGeneration()<br/>isStreaming()"]
S1Error["<b>Error Handling:</b><br/>showErrorDialog()<br/>dismissErrorDialog()<br/>isAbortError()"]
S1Msg["<b>Message Operations:</b><br/>addMessage()<br/>sendMessage()<br/>updateMessage()<br/>deleteMessage()<br/>getDeletionInfo()"]
S1Regen["<b>Regeneration:</b><br/>regenerateMessage()<br/>regenerateMessageWithBranching()<br/>continueAssistantMessage()"]
S1Edit["<b>Editing:</b><br/>editAssistantMessage()<br/>editUserMessagePreserveResponses()<br/>editMessageWithBranching()<br/>clearEditMode()<br/>isEditModeActive()<br/>getAddFilesHandler()<br/>setEditModeActive()"]
S1Utils["<b>Utilities:</b><br/>getApiOptions()<br/>parseTimingData()<br/>getOrCreateAbortController()<br/>getConversationModel()"]
end
subgraph SA["agenticStore"]
SAState["<b>State:</b><br/>sessions (Map)<br/>isAnyRunning"]
SASession["<b>Session Management:</b><br/>getSession()<br/>updateSession()<br/>clearSession()<br/>getActiveSessions()<br/>isRunning()<br/>currentTurn()<br/>totalToolCalls()<br/>lastError()<br/>streamingToolCall()"]
SAConfig["<b>Configuration:</b><br/>getConfig()<br/>maxTurns, maxToolPreviewLines"]
SAFlow["<b>Agentic Loop:</b><br/>runAgenticFlow()<br/>executeAgenticLoop()<br/>normalizeToolCalls()<br/>emitToolCallResult()<br/>extractBase64Attachments()"]
end
subgraph S2["conversationsStore"]
S2State["<b>State:</b><br/>conversations<br/>activeConversation<br/>activeMessages<br/>isInitialized<br/>pendingMcpServerOverrides<br/>titleUpdateConfirmationCallback"]
S2Lifecycle["<b>Lifecycle:</b><br/>initialize()<br/>loadConversations()<br/>clearActiveConversation()"]
S2ConvCRUD["<b>Conversation CRUD:</b><br/>createConversation()<br/>loadConversation()<br/>deleteConversation()<br/>deleteAll()<br/>updateConversationName()<br/>updateConversationTitleWithConfirmation()"]
S2MsgMgmt["<b>Message Management:</b><br/>refreshActiveMessages()<br/>addMessageToActive()<br/>updateMessageAtIndex()<br/>findMessageIndex()<br/>sliceActiveMessages()<br/>removeMessageAtIndex()<br/>getConversationMessages()"]
S2Nav["<b>Navigation:</b><br/>navigateToSibling()<br/>updateCurrentNode()<br/>updateConversationTimestamp()"]
S2McpOverrides["<b>MCP Per-Chat Overrides:</b><br/>getMcpServerOverride()<br/>getAllMcpServerOverrides()<br/>setMcpServerOverride()<br/>toggleMcpServerForChat()<br/>removeMcpServerOverride()<br/>isMcpServerEnabledForChat()<br/>clearPendingMcpServerOverrides()"]
S2Export["<b>Import/Export:</b><br/>downloadConversation()<br/>exportAllConversations()<br/>importConversations()<br/>importConversationsData()<br/>triggerDownload()"]
S2Utils["<b>Utilities:</b><br/>setTitleUpdateConfirmationCallback()"]
end
subgraph S3["modelsStore"]
S3State["<b>State:</b><br/>models, routerModels<br/>selectedModelId<br/>selectedModelName<br/>loading, updating, error<br/>modelLoadingStates<br/>modelPropsCache<br/>modelPropsFetching<br/>propsCacheVersion"]
S3Getters["<b>Computed Getters:</b><br/>selectedModel<br/>loadedModelIds<br/>loadingModelIds<br/>singleModelName"]
S3Modal["<b>Modalities:</b><br/>getModelModalities()<br/>modelSupportsVision()<br/>modelSupportsAudio()<br/>getModelModalitiesArray()<br/>getModelProps()<br/>updateModelModalities()"]
S3Status["<b>Status Queries:</b><br/>isModelLoaded()<br/>isModelOperationInProgress()<br/>getModelStatus()<br/>isModelPropsFetching()"]
S3Fetch["<b>Data Fetching:</b><br/>fetch()<br/>fetchRouterModels()<br/>fetchModelProps()<br/>fetchModalitiesForLoadedModels()"]
S3Select["<b>Model Selection:</b><br/>selectModelById()<br/>selectModelByName()<br/>clearSelection()<br/>findModelByName()<br/>findModelById()<br/>hasModel()"]
S3LoadUnload["<b>Loading/Unloading Models:</b><br/>loadModel()<br/>unloadModel()<br/>ensureModelLoaded()<br/>waitForModelStatus()<br/>pollForModelStatus()"]
S3Utils["<b>Utilities:</b><br/>toDisplayName()<br/>clear()"]
end
subgraph S4["serverStore"]
S4State["<b>State:</b><br/>props<br/>loading, error<br/>role<br/>fetchPromise"]
S4Getters["<b>Getters:</b><br/>defaultParams<br/>contextSize<br/>isRouterMode<br/>isModelMode"]
S4Data["<b>Data Handling:</b><br/>fetch()<br/>getErrorMessage()<br/>clear()"]
S4Utils["<b>Utilities:</b><br/>detectRole()"]
end
subgraph S5["settingsStore"]
S5State["<b>State:</b><br/>config<br/>theme<br/>isInitialized<br/>userOverrides"]
S5Lifecycle["<b>Lifecycle:</b><br/>initialize()<br/>loadConfig()<br/>saveConfig()<br/>loadTheme()<br/>saveTheme()"]
S5Update["<b>Config Updates:</b><br/>updateConfig()<br/>updateMultipleConfig()<br/>updateTheme()"]
S5Reset["<b>Reset:</b><br/>resetConfig()<br/>resetTheme()<br/>resetAll()<br/>resetParameterToServerDefault()"]
S5Sync["<b>Server Sync:</b><br/>syncWithServerDefaults()<br/>forceSyncWithServerDefaults()"]
S5Utils["<b>Utilities:</b><br/>getConfig()<br/>getAllConfig()<br/>getParameterInfo()<br/>getParameterDiff()<br/>getServerDefaults()<br/>clearAllUserOverrides()"]
end
subgraph S6["mcpStore"]
S6State["<b>State:</b><br/>isInitializing, error<br/>toolCount, connectedServers<br/>healthChecks (Map)<br/>connections (Map)<br/>toolsIndex (Map)"]
S6Lifecycle["<b>Lifecycle:</b><br/>ensureInitialized()<br/>initialize()<br/>shutdown()<br/>acquireConnection()<br/>releaseConnection()"]
S6Health["<b>Health Checks:</b><br/>runHealthCheck()<br/>runHealthChecksForServers()<br/>updateHealthCheck()<br/>getHealthCheckState()<br/>clearHealthCheck()"]
S6Servers["<b>Server Management:</b><br/>getServers()<br/>addServer()<br/>updateServer()<br/>removeServer()<br/>getServerById()<br/>getServerDisplayName()"]
S6Tools["<b>Tool Operations:</b><br/>getToolDefinitionsForLLM()<br/>getToolNames()<br/>hasTool()<br/>getToolServer()<br/>executeTool()<br/>executeToolByName()"]
S6Prompts["<b>Prompt Operations:</b><br/>getAllPrompts()<br/>getPrompt()<br/>hasPromptsCapability()<br/>getPromptCompletions()"]
end
subgraph S7["mcpResourceStore"]
S7State["<b>State:</b><br/>serverResources (Map)<br/>cachedResources (Map)<br/>subscriptions (Map)<br/>attachments[]<br/>isLoading"]
S7Resources["<b>Resource Discovery:</b><br/>setServerResources()<br/>getServerResources()<br/>getAllResourceInfos()<br/>getAllTemplateInfos()<br/>clearServerResources()"]
S7Cache["<b>Caching:</b><br/>cacheResourceContent()<br/>getCachedContent()<br/>invalidateCache()<br/>clearCache()"]
S7Subs["<b>Subscriptions:</b><br/>addSubscription()<br/>removeSubscription()<br/>isSubscribed()<br/>handleResourceUpdate()"]
S7Attach["<b>Attachments:</b><br/>addAttachment()<br/>updateAttachmentContent()<br/>removeAttachment()<br/>clearAttachments()<br/>toMessageExtras()"]
end
subgraph ReactiveExports["⚡ Reactive Exports"]
direction LR
subgraph ChatExports["chatStore"]
RE1["isLoading()"]
RE2["currentResponse()"]
RE3["errorDialog()"]
RE4["activeProcessingState()"]
RE5["isChatStreaming()"]
RE6["isChatLoading()"]
RE7["getChatStreaming()"]
RE8["getAllLoadingChats()"]
RE9["getAllStreamingChats()"]
RE9a["isEditModeActive()"]
RE9b["getAddFilesHandler()"]
RE9c["setEditModeActive()"]
RE9d["clearEditMode()"]
end
subgraph AgenticExports["agenticStore"]
REA1["agenticIsRunning()"]
REA2["agenticCurrentTurn()"]
REA3["agenticTotalToolCalls()"]
REA4["agenticLastError()"]
REA5["agenticStreamingToolCall()"]
REA6["agenticIsAnyRunning()"]
end
subgraph ConvExports["conversationsStore"]
RE10["conversations()"]
RE11["activeConversation()"]
RE12["activeMessages()"]
RE13["isConversationsInitialized()"]
end
subgraph ModelsExports["modelsStore"]
RE15["modelOptions()"]
RE16["routerModels()"]
RE17["modelsLoading()"]
RE18["modelsUpdating()"]
RE19["modelsError()"]
RE20["selectedModelId()"]
RE21["selectedModelName()"]
RE22["selectedModelOption()"]
RE23["loadedModelIds()"]
RE24["loadingModelIds()"]
RE25["propsCacheVersion()"]
RE26["singleModelName()"]
end
subgraph ServerExports["serverStore"]
RE27["serverProps()"]
RE28["serverLoading()"]
RE29["serverError()"]
RE30["serverRole()"]
RE31["defaultParams()"]
RE32["contextSize()"]
RE33["isRouterMode()"]
RE34["isModelMode()"]
end
subgraph SettingsExports["settingsStore"]
RE35["config()"]
RE36["theme()"]
RE37["isInitialized()"]
end
subgraph MCPExports["mcpStore / mcpResourceStore"]
RE38["mcpResources()"]
RE39["mcpResourceAttachments()"]
RE40["mcpHasResourceAttachments()"]
RE41["mcpTotalResourceCount()"]
RE42["mcpResourcesLoading()"]
end
end
end
subgraph Services["⚙️ Services"]
direction TB
subgraph SV1["ChatService"]
SV1Msg["<b>Messaging:</b><br/>sendMessage()"]
SV1Stream["<b>Streaming:</b><br/>handleStreamResponse()<br/>handleNonStreamResponse()"]
SV1Convert["<b>Conversion:</b><br/>convertDbMessageToApiChatMessageData()<br/>mergeToolCallDeltas()"]
SV1Utils["<b>Utilities:</b><br/>stripReasoningContent()<br/>extractModelName()<br/>parseErrorResponse()"]
end
subgraph SV2["ModelsService"]
SV2List["<b>Listing:</b><br/>list()<br/>listRouter()"]
SV2LoadUnload["<b>Load/Unload:</b><br/>load()<br/>unload()"]
SV2Status["<b>Status:</b><br/>isModelLoaded()<br/>isModelLoading()"]
end
subgraph SV3["PropsService"]
SV3Fetch["<b>Fetching:</b><br/>fetch()<br/>fetchForModel()"]
end
subgraph SV4["DatabaseService"]
SV4Conv["<b>Conversations:</b><br/>createConversation()<br/>getConversation()<br/>getAllConversations()<br/>updateConversation()<br/>deleteConversation()"]
SV4Msg["<b>Messages:</b><br/>createMessageBranch()<br/>createRootMessage()<br/>createSystemMessage()<br/>getConversationMessages()<br/>updateMessage()<br/>deleteMessage()<br/>deleteMessageCascading()"]
SV4Node["<b>Navigation:</b><br/>updateCurrentNode()"]
SV4Import["<b>Import:</b><br/>importConversations()"]
end
subgraph SV5["ParameterSyncService"]
SV5Extract["<b>Extraction:</b><br/>extractServerDefaults()"]
SV5Merge["<b>Merging:</b><br/>mergeWithServerDefaults()"]
SV5Info["<b>Info:</b><br/>getParameterInfo()<br/>canSyncParameter()<br/>getSyncableParameterKeys()<br/>validateServerParameter()"]
SV5Diff["<b>Diff:</b><br/>createParameterDiff()"]
end
subgraph SV6["MCPService"]
SV6Transport["<b>Transport:</b><br/>createTransport()<br/>WebSocket / StreamableHTTP / SSE"]
SV6Conn["<b>Connection:</b><br/>connect()<br/>disconnect()"]
SV6Tools["<b>Tools:</b><br/>listTools()<br/>callTool()"]
SV6Prompts["<b>Prompts:</b><br/>listPrompts()<br/>getPrompt()"]
SV6Resources["<b>Resources:</b><br/>listResources()<br/>listResourceTemplates()<br/>readResource()<br/>subscribeResource()<br/>unsubscribeResource()"]
SV6Complete["<b>Completions:</b><br/>complete()"]
end
end
subgraph ExternalMCP["🔌 External MCP Servers"]
EXT1["MCP Server 1<br/>(WebSocket/StreamableHTTP/SSE)"]
EXT2["MCP Server N"]
end
subgraph Storage["💾 Storage"]
ST1["IndexedDB"]
ST2["conversations"]
ST3["messages"]
ST5["LocalStorage"]
ST6["config"]
ST7["userOverrides"]
ST8["mcpServers"]
end
subgraph APIs["🌐 llama-server API"]
API1["/v1/chat/completions"]
API2["/props<br/>/props?model="]
API3["/models<br/>/models/load<br/>/models/unload"]
API4["/v1/models"]
end
%% Routes render Components
R1 --> C_Screen
R2 --> C_Screen
RL --> C_Sidebar
%% Layout runs MCP health checks on startup
RL --> S6
%% Component hierarchy
C_Screen --> C_Form & C_Messages & C_Settings
C_Messages --> C_Message
C_Message --> C_MessageUser
C_MessageUser --> C_MessageEditForm
C_MessageEditForm --> C_ModelsSelector
C_MessageEditForm --> C_Attach
C_Form --> C_ModelsSelector
C_Form --> C_Attach
C_Form --> C_McpServersSelector
C_Message --> C_Attach
%% MCP Components hierarchy
C_Settings --> C_McpSettings
C_McpSettings --> C_McpServerCard
C_McpServerCard --> C_McpResourceBrowser
C_McpResourceBrowser --> C_McpResourcePreview
%% Components use Hooks
C_Form --> H1
C_Message --> H1 & H2
C_MessageEditForm --> H1
C_Screen --> H2
%% Hooks use Stores
H1 --> S3 & S4
H2 --> S1 & S5
%% Components use Stores
C_Screen --> S1 & S2
C_Messages --> S2
C_Message --> S1 & S2 & S3
C_Form --> S1 & S3 & S6
C_Sidebar --> S2
C_ModelsSelector --> S3 & S4
C_Settings --> S5
C_McpSettings --> S6
C_McpServerCard --> S6
C_McpResourceBrowser --> S6 & S7
C_McpServersSelector --> S6
%% Stores export Reactive State
S1 -. exports .-> ChatExports
SA -. exports .-> AgenticExports
S2 -. exports .-> ConvExports
S3 -. exports .-> ModelsExports
S4 -. exports .-> ServerExports
S5 -. exports .-> SettingsExports
S6 -. exports .-> MCPExports
S7 -. exports .-> MCPExports
%% chatStore → agenticStore (agentic loop orchestration)
S1 --> SA
SA --> SV1
SA --> S6
%% Stores use Services
S1 --> SV1 & SV4
S2 --> SV4
S3 --> SV2 & SV3
S4 --> SV3
S5 --> SV5
S6 --> SV6
S7 --> SV6
%% Services to Storage
SV4 --> ST1
ST1 --> ST2 & ST3
SV5 --> ST5
ST5 --> ST6 & ST7 & ST8
%% Services to APIs
SV1 --> API1
SV2 --> API3 & API4
SV3 --> API2
%% MCP → External Servers
SV6 --> EXT1 & EXT2
%% Styling
classDef routeStyle fill:#e1f5fe,stroke:#01579b,stroke-width:2px
classDef componentStyle fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
classDef componentGroupStyle fill:#e1bee7,stroke:#7b1fa2,stroke-width:1px
classDef hookStyle fill:#fff8e1,stroke:#ff8f00,stroke-width:2px
classDef storeStyle fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef stateStyle fill:#ffe0b2,stroke:#e65100,stroke-width:1px
classDef methodStyle fill:#ffecb3,stroke:#e65100,stroke-width:1px
classDef reactiveStyle fill:#fffde7,stroke:#f9a825,stroke-width:1px
classDef serviceStyle fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px
classDef serviceMStyle fill:#c8e6c9,stroke:#2e7d32,stroke-width:1px
classDef externalStyle fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px,stroke-dasharray: 5 5
classDef storageStyle fill:#fce4ec,stroke:#c2185b,stroke-width:2px
classDef apiStyle fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
class R1,R2,RL routeStyle
class C_Sidebar,C_Screen,C_Form,C_Messages,C_Message,C_MessageUser,C_MessageEditForm componentStyle
class C_ModelsSelector,C_Settings componentStyle
class C_Attach componentStyle
class C_McpSettings,C_McpServerCard,C_McpResourceBrowser,C_McpResourcePreview,C_McpServersSelector componentStyle
class H1,H2,H3 hookStyle
class LayoutComponents,ChatUIComponents,MCPComponents componentGroupStyle
class Hooks hookStyle
classDef agenticStyle fill:#e8eaf6,stroke:#283593,stroke-width:2px
classDef agenticMethodStyle fill:#c5cae9,stroke:#283593,stroke-width:1px
class S1,S2,S3,S4,S5,SA,S6,S7 storeStyle
class S1State,S2State,S3State,S4State,S5State,SAState,S6State,S7State stateStyle
class S1Msg,S1Regen,S1Edit,S1Stream,S1LoadState,S1ProcState,S1Error,S1Utils methodStyle
class SASession,SAConfig,SAFlow methodStyle
class S2Lifecycle,S2ConvCRUD,S2MsgMgmt,S2Nav,S2McpOverrides,S2Export,S2Utils methodStyle
class S3Getters,S3Modal,S3Status,S3Fetch,S3Select,S3LoadUnload,S3Utils methodStyle
class S4Getters,S4Data,S4Utils methodStyle
class S5Lifecycle,S5Update,S5Reset,S5Sync,S5Utils methodStyle
class S6Lifecycle,S6Health,S6Servers,S6Tools,S6Prompts methodStyle
class S7Resources,S7Cache,S7Subs,S7Attach methodStyle
class ChatExports,AgenticExports,ConvExports,ModelsExports,ServerExports,SettingsExports,MCPExports reactiveStyle
class SV1,SV2,SV3,SV4,SV5,SV6 serviceStyle
class SV6Transport,SV6Conn,SV6Tools,SV6Prompts,SV6Resources,SV6Complete serviceMStyle
class EXT1,EXT2 externalStyle
class SV1Msg,SV1Stream,SV1Convert,SV1Utils serviceMStyle
class SV2List,SV2LoadUnload,SV2Status serviceMStyle
class SV3Fetch serviceMStyle
class SV4Conv,SV4Msg,SV4Node,SV4Import serviceMStyle
class SV5Extract,SV5Merge,SV5Info,SV5Diff serviceMStyle
class ST1,ST2,ST3,ST5,ST6,ST7,ST8 storageStyle
class API1,API2,API3,API4 apiStyle
```
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```mermaid
sequenceDiagram
participant UI as 🧩 ChatForm / ChatMessage
participant chatStore as 🗄️ chatStore
participant agenticStore as 🗄️ agenticStore
participant convStore as 🗄️ conversationsStore
participant settingsStore as 🗄️ settingsStore
participant mcpStore as 🗄️ mcpStore
participant ChatSvc as ⚙️ ChatService
participant DbSvc as ⚙️ DatabaseService
participant API as 🌐 /v1/chat/completions
Note over chatStore: State:<br/>isLoading, currentResponse<br/>errorDialogState, activeProcessingState<br/>chatLoadingStates (Map)<br/>chatStreamingStates (Map)<br/>abortControllers (Map)<br/>processingStates (Map)
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 💬 SEND MESSAGE
%% ═══════════════════════════════════════════════════════════════════════════
UI->>chatStore: sendMessage(content, extras)
activate chatStore
chatStore->>chatStore: setChatLoading(convId, true)
chatStore->>chatStore: clearChatStreaming(convId)
alt no active conversation
chatStore->>convStore: createConversation()
Note over convStore: → see conversations-flow.mmd
end
chatStore->>mcpStore: consumeResourceAttachmentsAsExtras()
Note right of mcpStore: Converts pending MCP resource<br/>attachments into message extras
chatStore->>chatStore: addMessage("user", content, extras)
chatStore->>DbSvc: createMessageBranch(userMsg, parentId)
chatStore->>convStore: addMessageToActive(userMsg)
chatStore->>convStore: updateCurrentNode(userMsg.id)
chatStore->>chatStore: createAssistantMessage(userMsg.id)
chatStore->>DbSvc: createMessageBranch(assistantMsg, userMsg.id)
chatStore->>convStore: addMessageToActive(assistantMsg)
chatStore->>chatStore: streamChatCompletion(messages, assistantMsg)
deactivate chatStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 🌊 STREAMING (with agentic flow detection)
%% ═══════════════════════════════════════════════════════════════════════════
activate chatStore
chatStore->>chatStore: startStreaming()
Note right of chatStore: isStreamingActive = true
chatStore->>chatStore: setActiveProcessingConversation(convId)
chatStore->>chatStore: getOrCreateAbortController(convId)
Note right of chatStore: abortControllers.set(convId, new AbortController())
chatStore->>chatStore: getApiOptions()
Note right of chatStore: Merge from settingsStore.config:<br/>temperature, max_tokens, top_p, etc.
alt agenticConfig.enabled && mcpStore has connected servers
chatStore->>agenticStore: runAgenticFlow(convId, messages, assistantMsg, options, signal)
Note over agenticStore: Multi-turn agentic loop:<br/>1. Call ChatService.sendMessage()<br/>2. If response has tool_calls → execute via mcpStore<br/>3. Append tool results as messages<br/>4. Loop until no more tool_calls or maxTurns<br/>→ see agentic flow details below
agenticStore-->>chatStore: final response with timings
else standard (non-agentic) flow
chatStore->>ChatSvc: sendMessage(messages, options, signal)
end
activate ChatSvc
ChatSvc->>ChatSvc: convertDbMessageToApiChatMessageData(messages)
Note right of ChatSvc: DatabaseMessage[] → ApiChatMessageData[]<br/>Process attachments (images, PDFs, audio)
ChatSvc->>API: POST /v1/chat/completions
Note right of API: {messages, model?, stream: true, ...params}
loop SSE chunks
API-->>ChatSvc: data: {"choices":[{"delta":{...}}]}
ChatSvc->>ChatSvc: handleStreamResponse(response)
alt content chunk
ChatSvc-->>chatStore: onChunk(content)
chatStore->>chatStore: setChatStreaming(convId, response, msgId)
Note right of chatStore: currentResponse = $state(accumulated)
chatStore->>convStore: updateMessageAtIndex(idx, {content})
end
alt reasoning chunk
ChatSvc-->>chatStore: onReasoningChunk(reasoning)
chatStore->>convStore: updateMessageAtIndex(idx, {thinking})
end
alt tool_calls chunk
ChatSvc-->>chatStore: onToolCallChunk(toolCalls)
chatStore->>convStore: updateMessageAtIndex(idx, {toolCalls})
end
alt model info
ChatSvc-->>chatStore: onModel(modelName)
chatStore->>chatStore: recordModel(modelName)
chatStore->>DbSvc: updateMessage(msgId, {model})
end
alt timings (during stream)
ChatSvc-->>chatStore: onTimings(timings, promptProgress)
chatStore->>chatStore: updateProcessingStateFromTimings()
end
chatStore-->>UI: reactive $state update
end
API-->>ChatSvc: data: [DONE]
ChatSvc-->>chatStore: onComplete(content, reasoning, timings, toolCalls)
deactivate ChatSvc
chatStore->>chatStore: stopStreaming()
chatStore->>DbSvc: updateMessage(msgId, {content, timings, model})
chatStore->>convStore: updateCurrentNode(msgId)
chatStore->>chatStore: setChatLoading(convId, false)
chatStore->>chatStore: clearChatStreaming(convId)
chatStore->>chatStore: clearProcessingState(convId)
deactivate chatStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: ⏹️ STOP GENERATION
%% ═══════════════════════════════════════════════════════════════════════════
UI->>chatStore: stopGeneration()
activate chatStore
chatStore->>chatStore: savePartialResponseIfNeeded(convId)
Note right of chatStore: Save currentResponse to DB if non-empty
chatStore->>chatStore: abortControllers.get(convId).abort()
Note right of chatStore: fetch throws AbortError → caught by isAbortError()
chatStore->>chatStore: stopStreaming()
chatStore->>chatStore: setChatLoading(convId, false)
chatStore->>chatStore: clearChatStreaming(convId)
chatStore->>chatStore: clearProcessingState(convId)
deactivate chatStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 🔁 REGENERATE
%% ═══════════════════════════════════════════════════════════════════════════
UI->>chatStore: regenerateMessageWithBranching(msgId, model?)
activate chatStore
chatStore->>convStore: findMessageIndex(msgId)
chatStore->>chatStore: Get parent of target message
chatStore->>chatStore: createAssistantMessage(parentId)
chatStore->>DbSvc: createMessageBranch(newAssistantMsg, parentId)
chatStore->>convStore: refreshActiveMessages()
Note right of chatStore: Same streaming flow
chatStore->>chatStore: streamChatCompletion(...)
deactivate chatStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: ➡️ CONTINUE
%% ═══════════════════════════════════════════════════════════════════════════
UI->>chatStore: continueAssistantMessage(msgId)
activate chatStore
chatStore->>chatStore: Get existing content from message
chatStore->>chatStore: streamChatCompletion(..., existingContent)
Note right of chatStore: Appends to existing message content
deactivate chatStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: ✏️ EDIT USER MESSAGE
%% ═══════════════════════════════════════════════════════════════════════════
UI->>chatStore: editMessageWithBranching(msgId, newContent, extras)
activate chatStore
chatStore->>chatStore: Get parent of target message
chatStore->>DbSvc: createMessageBranch(editedMsg, parentId)
chatStore->>convStore: refreshActiveMessages()
Note right of chatStore: Creates new branch, original preserved
chatStore->>chatStore: createAssistantMessage(editedMsg.id)
chatStore->>chatStore: streamChatCompletion(...)
Note right of chatStore: Automatically regenerates response
deactivate chatStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: ❌ ERROR HANDLING
%% ═══════════════════════════════════════════════════════════════════════════
Note over chatStore: On stream error (non-abort):
chatStore->>chatStore: showErrorDialog(type, message)
Note right of chatStore: errorDialogState = {type: 'timeout'|'server', message}
chatStore->>convStore: removeMessageAtIndex(failedMsgIdx)
chatStore->>DbSvc: deleteMessage(failedMsgId)
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 🤖 AGENTIC LOOP (when agenticConfig.enabled)
%% ═══════════════════════════════════════════════════════════════════════════
Note over agenticStore: agenticStore.runAgenticFlow(convId, messages, assistantMsg, options, signal)
activate agenticStore
agenticStore->>agenticStore: getSession(convId) or create new
agenticStore->>agenticStore: updateSession(turn: 0, running: true)
loop executeAgenticLoop (until no tool_calls or maxTurns)
agenticStore->>agenticStore: turn++
agenticStore->>ChatSvc: sendMessage(messages, options, signal)
ChatSvc->>API: POST /v1/chat/completions
API-->>ChatSvc: response with potential tool_calls
ChatSvc-->>agenticStore: onComplete(content, reasoning, timings, toolCalls)
alt response has tool_calls
agenticStore->>agenticStore: normalizeToolCalls(toolCalls)
loop for each tool_call
agenticStore->>agenticStore: updateSession(streamingToolCall)
agenticStore->>mcpStore: executeTool(mcpCall, signal)
mcpStore-->>agenticStore: tool result
agenticStore->>agenticStore: extractBase64Attachments(result)
agenticStore->>agenticStore: emitToolCallResult(convId, ...)
agenticStore->>convStore: addMessageToActive(toolResultMsg)
agenticStore->>DbSvc: createMessageBranch(toolResultMsg)
end
agenticStore->>agenticStore: Create new assistantMsg for next turn
Note right of agenticStore: Continue loop with updated messages
else no tool_calls (final response)
agenticStore->>agenticStore: buildFinalTimings(allTurns)
Note right of agenticStore: Break loop, return final response
end
end
agenticStore->>agenticStore: updateSession(running: false)
agenticStore-->>chatStore: final content, timings, model
deactivate agenticStore
```
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```mermaid
sequenceDiagram
participant UI as 🧩 ChatSidebar / ChatScreen
participant convStore as 🗄️ conversationsStore
participant chatStore as 🗄️ chatStore
participant DbSvc as ⚙️ DatabaseService
participant IDB as 💾 IndexedDB
Note over convStore: State:<br/>conversations: DatabaseConversation[]<br/>activeConversation: DatabaseConversation | null<br/>activeMessages: DatabaseMessage[]<br/>isInitialized: boolean<br/>pendingMcpServerOverrides: Map&lt;string, McpServerOverride&gt;
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,IDB: 🚀 INITIALIZATION
%% ═══════════════════════════════════════════════════════════════════════════
Note over convStore: Auto-initialized in constructor (browser only)
convStore->>convStore: initialize()
activate convStore
convStore->>convStore: loadConversations()
convStore->>DbSvc: getAllConversations()
DbSvc->>IDB: SELECT * FROM conversations ORDER BY lastModified DESC
IDB-->>DbSvc: Conversation[]
DbSvc-->>convStore: conversations
convStore->>convStore: conversations = $state(data)
convStore->>convStore: isInitialized = true
deactivate convStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,IDB: CREATE CONVERSATION
%% ═══════════════════════════════════════════════════════════════════════════
UI->>convStore: createConversation(name?)
activate convStore
convStore->>DbSvc: createConversation(name || "New Chat")
DbSvc->>IDB: INSERT INTO conversations
IDB-->>DbSvc: conversation {id, name, lastModified, currNode: ""}
DbSvc-->>convStore: conversation
convStore->>convStore: conversations.unshift(conversation)
convStore->>convStore: activeConversation = $state(conversation)
convStore->>convStore: activeMessages = $state([])
alt pendingMcpServerOverrides has entries
loop each pending override
convStore->>DbSvc: Store MCP server override for new conversation
end
convStore->>convStore: clearPendingMcpServerOverrides()
end
deactivate convStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,IDB: 📂 LOAD CONVERSATION
%% ═══════════════════════════════════════════════════════════════════════════
UI->>convStore: loadConversation(convId)
activate convStore
convStore->>DbSvc: getConversation(convId)
DbSvc->>IDB: SELECT * FROM conversations WHERE id = ?
IDB-->>DbSvc: conversation
convStore->>convStore: activeConversation = $state(conversation)
convStore->>convStore: refreshActiveMessages()
convStore->>DbSvc: getConversationMessages(convId)
DbSvc->>IDB: SELECT * FROM messages WHERE convId = ?
IDB-->>DbSvc: allMessages[]
convStore->>convStore: filterByLeafNodeId(allMessages, currNode)
Note right of convStore: Filter to show only current branch path
convStore->>convStore: activeMessages = $state(filtered)
Note right of convStore: Route (+page.svelte) then calls:<br/>chatStore.syncLoadingStateForChat(convId)
deactivate convStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,IDB: 🌳 MESSAGE BRANCHING MODEL
%% ═══════════════════════════════════════════════════════════════════════════
Note over IDB: Message Tree Structure:<br/>- Each message has parent (null for root)<br/>- Each message has children[] array<br/>- Conversation.currNode points to active leaf<br/>- filterByLeafNodeId() traverses from root to currNode
rect rgb(240, 240, 255)
Note over convStore: Example Branch Structure:
Note over convStore: root → user1 → assistant1 → user2 → assistant2a (currNode)<br/> ↘ assistant2b (alt branch)
end
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,IDB: ↔️ BRANCH NAVIGATION
%% ═══════════════════════════════════════════════════════════════════════════
UI->>convStore: navigateToSibling(msgId, direction)
activate convStore
convStore->>convStore: Find message in activeMessages
convStore->>convStore: Get parent message
convStore->>convStore: Find sibling in parent.children[]
convStore->>convStore: findLeafNode(siblingId, allMessages)
Note right of convStore: Navigate to leaf of sibling branch
convStore->>convStore: updateCurrentNode(leafId)
convStore->>DbSvc: updateCurrentNode(convId, leafId)
DbSvc->>IDB: UPDATE conversations SET currNode = ?
convStore->>convStore: refreshActiveMessages()
deactivate convStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,IDB: 📝 UPDATE CONVERSATION
%% ═══════════════════════════════════════════════════════════════════════════
UI->>convStore: updateConversationName(convId, newName)
activate convStore
convStore->>DbSvc: updateConversation(convId, {name: newName})
DbSvc->>IDB: UPDATE conversations SET name = ?
convStore->>convStore: Update in conversations array
deactivate convStore
Note over convStore: Auto-title update (after first response):
convStore->>convStore: updateConversationTitleWithConfirmation()
convStore->>convStore: titleUpdateConfirmationCallback?()
Note right of convStore: Shows dialog if title would change
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,IDB: 🗑️ DELETE CONVERSATION
%% ═══════════════════════════════════════════════════════════════════════════
UI->>convStore: deleteConversation(convId)
activate convStore
convStore->>DbSvc: deleteConversation(convId)
DbSvc->>IDB: DELETE FROM conversations WHERE id = ?
DbSvc->>IDB: DELETE FROM messages WHERE convId = ?
convStore->>convStore: conversations.filter(c => c.id !== convId)
alt deleted active conversation
convStore->>convStore: clearActiveConversation()
end
deactivate convStore
UI->>convStore: deleteAll()
activate convStore
convStore->>DbSvc: Delete all conversations and messages
convStore->>convStore: conversations = []
convStore->>convStore: clearActiveConversation()
deactivate convStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,IDB: MCP SERVER PER-CHAT OVERRIDES
%% ═══════════════════════════════════════════════════════════════════════════
Note over convStore: Conversations can override which MCP servers are enabled.
Note over convStore: Uses pendingMcpServerOverrides before conversation<br/>is created, then persists to conversation metadata.
UI->>convStore: setMcpServerOverride(convId, serverName, override)
Note right of convStore: override = {enabled: boolean}
UI->>convStore: toggleMcpServerForChat(convId, serverName, enabled)
activate convStore
convStore->>convStore: setMcpServerOverride(convId, serverName, {enabled})
deactivate convStore
UI->>convStore: isMcpServerEnabledForChat(convId, serverName)
Note right of convStore: Check override → fall back to global MCP config
UI->>convStore: getAllMcpServerOverrides(convId)
Note right of convStore: Returns all overrides for a conversation
UI->>convStore: removeMcpServerOverride(convId, serverName)
UI->>convStore: getMcpServerOverride(convId, serverName)
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,IDB: 📤 EXPORT / 📥 IMPORT
%% ═══════════════════════════════════════════════════════════════════════════
UI->>convStore: exportAllConversations()
activate convStore
convStore->>DbSvc: getAllConversations()
loop each conversation
convStore->>DbSvc: getConversationMessages(convId)
end
convStore->>convStore: triggerDownload(JSON blob)
deactivate convStore
UI->>convStore: importConversations(file)
activate convStore
convStore->>convStore: Parse JSON file
convStore->>convStore: importConversationsData(parsed)
convStore->>DbSvc: importConversations(parsed)
Note right of DbSvc: Skips duplicate conversations<br/>(checks existing by ID)
DbSvc->>IDB: INSERT conversations + messages (skip existing)
convStore->>convStore: loadConversations()
deactivate convStore
```
@@ -1,45 +0,0 @@
```mermaid
%% MODEL Mode Data Flow (single model)
%% Detailed flows: ./flows/server-flow.mmd, ./flows/models-flow.mmd, ./flows/chat-flow.mmd
sequenceDiagram
participant User as 👤 User
participant UI as 🧩 UI
participant Stores as 🗄️ Stores
participant DB as 💾 IndexedDB
participant API as 🌐 llama-server
Note over User,API: 🚀 Initialization (see: server-flow.mmd, models-flow.mmd)
UI->>Stores: initialize()
Stores->>DB: load conversations
Stores->>API: GET /props
API-->>Stores: server config + modalities
Stores->>API: GET /v1/models
API-->>Stores: single model (auto-selected)
Note over User,API: 💬 Chat Flow (see: chat-flow.mmd)
User->>UI: send message
UI->>Stores: sendMessage()
Stores->>DB: save user message
Stores->>API: POST /v1/chat/completions (stream)
loop streaming
API-->>Stores: SSE chunks
Stores-->>UI: reactive update
end
API-->>Stores: done + timings
Stores->>DB: save assistant message
Note over User,API: 🔁 Regenerate
User->>UI: regenerate
Stores->>DB: create message branch
Note right of Stores: same streaming flow
Note over User,API: ⏹️ Stop
User->>UI: stop
Stores->>Stores: abort stream
Stores->>DB: save partial response
```
@@ -1,77 +0,0 @@
```mermaid
%% ROUTER Mode Data Flow (multi-model)
%% Detailed flows: ./flows/server-flow.mmd, ./flows/models-flow.mmd, ./flows/chat-flow.mmd
sequenceDiagram
participant User as 👤 User
participant UI as 🧩 UI
participant Stores as 🗄️ Stores
participant DB as 💾 IndexedDB
participant API as 🌐 llama-server
Note over User,API: 🚀 Initialization (see: server-flow.mmd, models-flow.mmd)
UI->>Stores: initialize()
Stores->>DB: load conversations
Stores->>API: GET /props
API-->>Stores: {role: "router"}
Stores->>API: GET /v1/models
API-->>Stores: models[] with status (loaded/available)
loop each loaded model
Stores->>API: GET /props?model=X
API-->>Stores: modalities (vision/audio)
end
Note over User,API: 🔄 Model Selection (see: models-flow.mmd)
User->>UI: select model
alt model not loaded
Stores->>API: POST /models/load
loop poll status
Stores->>API: GET /v1/models
API-->>Stores: check if loaded
end
Stores->>API: GET /props?model=X
API-->>Stores: cache modalities
end
Stores->>Stores: validate modalities vs conversation
alt valid
Stores->>Stores: select model
else invalid
Stores->>API: POST /models/unload
UI->>User: show error toast
end
Note over User,API: 💬 Chat Flow (see: chat-flow.mmd)
User->>UI: send message
UI->>Stores: sendMessage()
Stores->>DB: save user message
Stores->>API: POST /v1/chat/completions {model: X}
Note right of API: router forwards to model
loop streaming
API-->>Stores: SSE chunks + model info
Stores-->>UI: reactive update
end
API-->>Stores: done + timings
Stores->>DB: save assistant message + model used
Note over User,API: 🔁 Regenerate (optional: different model)
User->>UI: regenerate
Stores->>Stores: validate modalities up to this message
Stores->>DB: create message branch
Note right of Stores: same streaming flow
Note over User,API: ⏹️ Stop
User->>UI: stop
Stores->>Stores: abort stream
Stores->>DB: save partial response
Note over User,API: 🗑️ LRU Unloading
Note right of API: Server auto-unloads LRU models<br/>when cache full
User->>UI: select unloaded model
Note right of Stores: triggers load flow again
```
-174
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```mermaid
sequenceDiagram
participant Store as 🗄️ Stores
participant DbSvc as ⚙️ DatabaseService
participant Dexie as 📦 Dexie ORM
participant IDB as 💾 IndexedDB
Note over DbSvc: Stateless service - all methods static<br/>Database: "LlamacppWebui"
%% ═══════════════════════════════════════════════════════════════════════════
Note over Store,IDB: 📊 SCHEMA
%% ═══════════════════════════════════════════════════════════════════════════
rect rgb(240, 248, 255)
Note over IDB: conversations table:<br/>id (PK), lastModified, currNode, name
end
rect rgb(255, 248, 240)
Note over IDB: messages table:<br/>id (PK), convId (FK), type, role, timestamp,<br/>parent, children[], content, thinking,<br/>toolCalls, extra[], model, timings
end
%% ═══════════════════════════════════════════════════════════════════════════
Note over Store,IDB: 💬 CONVERSATIONS CRUD
%% ═══════════════════════════════════════════════════════════════════════════
Store->>DbSvc: createConversation(name)
activate DbSvc
DbSvc->>DbSvc: Generate UUID
DbSvc->>Dexie: db.conversations.add({id, name, lastModified, currNode: ""})
Dexie->>IDB: INSERT
IDB-->>Dexie: success
DbSvc-->>Store: DatabaseConversation
deactivate DbSvc
Store->>DbSvc: getConversation(convId)
DbSvc->>Dexie: db.conversations.get(convId)
Dexie->>IDB: SELECT WHERE id = ?
IDB-->>DbSvc: DatabaseConversation
Store->>DbSvc: getAllConversations()
DbSvc->>Dexie: db.conversations.orderBy('lastModified').reverse().toArray()
Dexie->>IDB: SELECT ORDER BY lastModified DESC
IDB-->>DbSvc: DatabaseConversation[]
Store->>DbSvc: updateConversation(convId, updates)
DbSvc->>Dexie: db.conversations.update(convId, {...updates, lastModified})
Dexie->>IDB: UPDATE
Store->>DbSvc: deleteConversation(convId)
activate DbSvc
DbSvc->>Dexie: db.conversations.delete(convId)
Dexie->>IDB: DELETE FROM conversations
DbSvc->>Dexie: db.messages.where('convId').equals(convId).delete()
Dexie->>IDB: DELETE FROM messages WHERE convId = ?
deactivate DbSvc
%% ═══════════════════════════════════════════════════════════════════════════
Note over Store,IDB: 📝 MESSAGES CRUD
%% ═══════════════════════════════════════════════════════════════════════════
Store->>DbSvc: createRootMessage(convId)
activate DbSvc
DbSvc->>DbSvc: Create root message {type: "root", parent: null}
DbSvc->>Dexie: db.messages.add(rootMsg)
Dexie->>IDB: INSERT
DbSvc-->>Store: rootMessageId
deactivate DbSvc
Store->>DbSvc: createSystemMessage(convId, content, parentId)
activate DbSvc
DbSvc->>DbSvc: Create message {role: "system", parent: parentId}
DbSvc->>Dexie: db.messages.add(systemMsg)
Dexie->>IDB: INSERT
DbSvc-->>Store: DatabaseMessage
deactivate DbSvc
Store->>DbSvc: createMessageBranch(message, parentId)
activate DbSvc
DbSvc->>DbSvc: Generate UUID for new message
DbSvc->>Dexie: db.messages.add({...message, id, parent: parentId})
Dexie->>IDB: INSERT message
alt parentId exists
DbSvc->>Dexie: db.messages.get(parentId)
Dexie->>IDB: SELECT parent
DbSvc->>DbSvc: parent.children.push(newId)
DbSvc->>Dexie: db.messages.update(parentId, {children})
Dexie->>IDB: UPDATE parent.children
end
DbSvc->>Dexie: db.conversations.update(convId, {currNode: newId})
Dexie->>IDB: UPDATE conversation.currNode
DbSvc-->>Store: DatabaseMessage
deactivate DbSvc
Store->>DbSvc: getConversationMessages(convId)
DbSvc->>Dexie: db.messages.where('convId').equals(convId).toArray()
Dexie->>IDB: SELECT WHERE convId = ?
IDB-->>DbSvc: DatabaseMessage[]
Store->>DbSvc: updateMessage(msgId, updates)
DbSvc->>Dexie: db.messages.update(msgId, updates)
Dexie->>IDB: UPDATE
Store->>DbSvc: deleteMessage(msgId)
DbSvc->>Dexie: db.messages.delete(msgId)
Dexie->>IDB: DELETE
%% ═══════════════════════════════════════════════════════════════════════════
Note over Store,IDB: 🌳 BRANCHING OPERATIONS
%% ═══════════════════════════════════════════════════════════════════════════
Store->>DbSvc: updateCurrentNode(convId, nodeId)
DbSvc->>Dexie: db.conversations.update(convId, {currNode: nodeId, lastModified})
Dexie->>IDB: UPDATE
Store->>DbSvc: deleteMessageCascading(msgId)
activate DbSvc
DbSvc->>DbSvc: findDescendantMessages(msgId, allMessages)
Note right of DbSvc: Recursively find all children
loop each descendant
DbSvc->>Dexie: db.messages.delete(descendantId)
Dexie->>IDB: DELETE
end
DbSvc->>Dexie: db.messages.delete(msgId)
Dexie->>IDB: DELETE target message
alt target message has a parent
DbSvc->>Dexie: db.messages.get(parentId)
DbSvc->>DbSvc: parent.children.filter(id !== msgId)
DbSvc->>Dexie: db.messages.update(parentId, {children})
Note right of DbSvc: Remove deleted message from parent's children[]
end
deactivate DbSvc
%% ═══════════════════════════════════════════════════════════════════════════
Note over Store,IDB: 📥 IMPORT
%% ═══════════════════════════════════════════════════════════════════════════
Store->>DbSvc: importConversations(data)
activate DbSvc
loop each conversation in data
DbSvc->>Dexie: db.conversations.get(conv.id)
alt conversation already exists
Note right of DbSvc: Skip duplicate (keep existing)
else conversation is new
DbSvc->>Dexie: db.conversations.add(conversation)
Dexie->>IDB: INSERT conversation
loop each message
DbSvc->>Dexie: db.messages.add(message)
Dexie->>IDB: INSERT message
end
end
end
deactivate DbSvc
%% ═══════════════════════════════════════════════════════════════════════════
Note over Store,IDB: 🔗 MESSAGE TREE UTILITIES
%% ═══════════════════════════════════════════════════════════════════════════
Note over DbSvc: Used by stores (imported from utils):
rect rgb(240, 255, 240)
Note over DbSvc: filterByLeafNodeId(messages, leafId)<br/>→ Returns path from root to leaf<br/>→ Used to display current branch
end
rect rgb(240, 255, 240)
Note over DbSvc: findLeafNode(startId, messages)<br/>→ Traverse to deepest child<br/>→ Used for branch navigation
end
rect rgb(240, 255, 240)
Note over DbSvc: findDescendantMessages(msgId, messages)<br/>→ Find all children recursively<br/>→ Used for cascading deletes
end
```
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```mermaid
sequenceDiagram
participant UI as 🧩 McpServersSettings / ChatForm
participant chatStore as 🗄️ chatStore
participant mcpStore as 🗄️ mcpStore
participant mcpResStore as 🗄️ mcpResourceStore
participant convStore as 🗄️ conversationsStore
participant MCPSvc as ⚙️ MCPService
participant LS as 💾 LocalStorage
participant ExtMCP as 🔌 External MCP Server
Note over mcpStore: State:<br/>isInitializing, error<br/>toolCount, connectedServers<br/>healthChecks (Map)<br/>connections (Map)<br/>toolsIndex (Map)<br/>serverConfigs (Map)
Note over mcpResStore: State:<br/>serverResources (Map)<br/>cachedResources (Map)<br/>subscriptions (Map)<br/>attachments[]
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,ExtMCP: 🚀 INITIALIZATION (App Startup)
%% ═══════════════════════════════════════════════════════════════════════════
UI->>mcpStore: ensureInitialized()
activate mcpStore
mcpStore->>LS: get(MCP_SERVERS_LOCALSTORAGE_KEY)
LS-->>mcpStore: MCPServerSettingsEntry[]
mcpStore->>mcpStore: parseServerSettings(servers)
Note right of mcpStore: Filter enabled servers<br/>Build MCPServerConfig objects<br/>Per-chat overrides checked via convStore
loop For each enabled server
mcpStore->>mcpStore: runHealthCheck(serverId)
mcpStore->>mcpStore: updateHealthCheck(id, CONNECTING)
mcpStore->>MCPSvc: connect(serverName, config, clientInfo, capabilities, onPhase)
activate MCPSvc
MCPSvc->>MCPSvc: createTransport(config)
Note right of MCPSvc: WebSocket / StreamableHTTP / SSE<br/>with optional CORS proxy
MCPSvc->>ExtMCP: Transport handshake
ExtMCP-->>MCPSvc: Connection established
MCPSvc->>ExtMCP: Initialize request
Note right of ExtMCP: Exchange capabilities<br/>Server info, protocol version
ExtMCP-->>MCPSvc: InitializeResult (serverInfo, capabilities)
MCPSvc->>ExtMCP: listTools()
ExtMCP-->>MCPSvc: Tool[]
MCPSvc-->>mcpStore: MCPConnection
deactivate MCPSvc
mcpStore->>mcpStore: connections.set(serverName, connection)
mcpStore->>mcpStore: indexTools(connection.tools, serverName)
Note right of mcpStore: toolsIndex.set(toolName, serverName)<br/>Handle name conflicts with prefixes
mcpStore->>mcpStore: updateHealthCheck(id, SUCCESS)
mcpStore->>mcpStore: _connectedServers.push(serverName)
alt Server supports resources
mcpStore->>MCPSvc: listAllResources(connection)
MCPSvc->>ExtMCP: listResources()
ExtMCP-->>MCPSvc: MCPResource[]
MCPSvc-->>mcpStore: resources
mcpStore->>MCPSvc: listAllResourceTemplates(connection)
MCPSvc->>ExtMCP: listResourceTemplates()
ExtMCP-->>MCPSvc: MCPResourceTemplate[]
MCPSvc-->>mcpStore: templates
mcpStore->>mcpResStore: setServerResources(serverName, resources, templates)
end
end
mcpStore->>mcpStore: _isInitializing = false
deactivate mcpStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,ExtMCP: 🔧 TOOL EXECUTION (Chat with Tools)
%% ═══════════════════════════════════════════════════════════════════════════
UI->>mcpStore: executeTool(mcpCall: MCPToolCall, signal?)
activate mcpStore
mcpStore->>mcpStore: toolsIndex.get(mcpCall.function.name)
Note right of mcpStore: Resolve serverName from toolsIndex<br/>MCPToolCall = {id, type, function: {name, arguments}}
mcpStore->>mcpStore: acquireConnection()
Note right of mcpStore: activeFlowCount++<br/>Prevent shutdown during execution
mcpStore->>mcpStore: connection = connections.get(serverName)
mcpStore->>MCPSvc: callTool(connection, {name, arguments}, signal)
activate MCPSvc
MCPSvc->>MCPSvc: throwIfAborted(signal)
MCPSvc->>ExtMCP: callTool(name, arguments)
alt Tool execution success
ExtMCP-->>MCPSvc: ToolCallResult (content, isError)
MCPSvc->>MCPSvc: formatToolResult(result)
Note right of MCPSvc: Handle text, image (base64),<br/>embedded resource content
MCPSvc-->>mcpStore: ToolExecutionResult
else Tool execution error
ExtMCP-->>MCPSvc: Error
MCPSvc-->>mcpStore: throw Error
else Aborted
MCPSvc-->>mcpStore: throw AbortError
end
deactivate MCPSvc
mcpStore->>mcpStore: releaseConnection()
Note right of mcpStore: activeFlowCount--
mcpStore-->>UI: ToolExecutionResult
deactivate mcpStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,ExtMCP: RESOURCE ATTACHMENT CONSUMPTION
%% ═══════════════════════════════════════════════════════════════════════════
chatStore->>mcpStore: consumeResourceAttachmentsAsExtras()
activate mcpStore
mcpStore->>mcpResStore: getAttachments()
mcpResStore-->>mcpStore: MCPResourceAttachment[]
mcpStore->>mcpStore: Convert attachments to message extras
mcpStore->>mcpResStore: clearAttachments()
mcpStore-->>chatStore: MessageExtra[] (for user message)
deactivate mcpStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,ExtMCP: 📝 PROMPT OPERATIONS
%% ═══════════════════════════════════════════════════════════════════════════
UI->>mcpStore: getAllPrompts()
activate mcpStore
loop For each connected server with prompts capability
mcpStore->>MCPSvc: listPrompts(connection)
MCPSvc->>ExtMCP: listPrompts()
ExtMCP-->>MCPSvc: Prompt[]
MCPSvc-->>mcpStore: prompts
end
mcpStore-->>UI: MCPPromptInfo[] (with serverName)
deactivate mcpStore
UI->>mcpStore: getPrompt(serverName, promptName, args?)
activate mcpStore
mcpStore->>MCPSvc: getPrompt(connection, name, args)
MCPSvc->>ExtMCP: getPrompt({name, arguments})
ExtMCP-->>MCPSvc: GetPromptResult (messages)
MCPSvc-->>mcpStore: GetPromptResult
mcpStore-->>UI: GetPromptResult
deactivate mcpStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,ExtMCP: 📁 RESOURCE OPERATIONS
%% ═══════════════════════════════════════════════════════════════════════════
UI->>mcpResStore: addAttachment(resourceInfo)
activate mcpResStore
mcpResStore->>mcpResStore: Create MCPResourceAttachment (loading: true)
mcpResStore-->>UI: attachment
UI->>mcpStore: readResource(serverName, uri)
activate mcpStore
mcpStore->>MCPSvc: readResource(connection, uri)
MCPSvc->>ExtMCP: readResource({uri})
ExtMCP-->>MCPSvc: MCPReadResourceResult (contents)
MCPSvc-->>mcpStore: contents
mcpStore-->>UI: MCPResourceContent[]
deactivate mcpStore
UI->>mcpResStore: updateAttachmentContent(attachmentId, content)
mcpResStore->>mcpResStore: cacheResourceContent(resource, content)
deactivate mcpResStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,ExtMCP: 🔄 AUTO-RECONNECTION
%% ═══════════════════════════════════════════════════════════════════════════
Note over mcpStore: On WebSocket close or connection error:
mcpStore->>mcpStore: autoReconnect(serverName, attempt)
activate mcpStore
mcpStore->>mcpStore: Calculate backoff delay
Note right of mcpStore: delay = min(30s, 1s * 2^attempt)
mcpStore->>mcpStore: Wait for delay
mcpStore->>mcpStore: reconnectServer(serverName)
alt Reconnection success
mcpStore->>mcpStore: updateHealthCheck(id, SUCCESS)
else Max attempts reached
mcpStore->>mcpStore: updateHealthCheck(id, ERROR)
end
deactivate mcpStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,ExtMCP: 🛑 SHUTDOWN
%% ═══════════════════════════════════════════════════════════════════════════
UI->>mcpStore: shutdown()
activate mcpStore
mcpStore->>mcpStore: Wait for activeFlowCount == 0
loop For each connection
mcpStore->>MCPSvc: disconnect(connection)
MCPSvc->>MCPSvc: transport.onclose = undefined
MCPSvc->>ExtMCP: close()
end
mcpStore->>mcpStore: connections.clear()
mcpStore->>mcpStore: toolsIndex.clear()
mcpStore->>mcpStore: _connectedServers = []
mcpStore->>mcpResStore: clear()
deactivate mcpStore
```
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```mermaid
sequenceDiagram
participant UI as 🧩 ModelsSelector
participant Hooks as 🪝 useModelChangeValidation
participant modelsStore as 🗄️ modelsStore
participant serverStore as 🗄️ serverStore
participant convStore as 🗄️ conversationsStore
participant ModelsSvc as ⚙️ ModelsService
participant PropsSvc as ⚙️ PropsService
participant API as 🌐 llama-server
Note over modelsStore: State:<br/>models: ModelOption[]<br/>routerModels: ApiModelDataEntry[]<br/>selectedModelId, selectedModelName<br/>loading, updating, error<br/>modelLoadingStates (Map)<br/>modelPropsCache (Map)<br/>propsCacheVersion
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 🚀 INITIALIZATION (MODEL mode)
%% ═══════════════════════════════════════════════════════════════════════════
UI->>modelsStore: fetch()
activate modelsStore
modelsStore->>modelsStore: loading = true
alt serverStore.props not loaded
modelsStore->>serverStore: fetch()
Note over serverStore: → see server-flow.mmd
end
modelsStore->>ModelsSvc: list()
ModelsSvc->>API: GET /v1/models
API-->>ModelsSvc: ApiModelListResponse {data: [model]}
modelsStore->>modelsStore: models = $state(mapped)
Note right of modelsStore: Map to ModelOption[]:<br/>{id, name, model, description, capabilities}
Note over modelsStore: MODEL mode: Get modalities from serverStore.props
modelsStore->>modelsStore: modelPropsCache.set(model.id, serverStore.props)
modelsStore->>modelsStore: models[0].modalities = props.modalities
modelsStore->>modelsStore: Auto-select single model
Note right of modelsStore: selectedModelId = models[0].id
modelsStore->>modelsStore: loading = false
deactivate modelsStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 🚀 INITIALIZATION (ROUTER mode)
%% ═══════════════════════════════════════════════════════════════════════════
UI->>modelsStore: fetch()
activate modelsStore
modelsStore->>ModelsSvc: list()
ModelsSvc->>API: GET /v1/models
API-->>ModelsSvc: ApiModelListResponse
modelsStore->>modelsStore: models = $state(mapped)
deactivate modelsStore
Note over UI: After models loaded, layout triggers:
UI->>modelsStore: fetchRouterModels()
activate modelsStore
modelsStore->>ModelsSvc: listRouter()
ModelsSvc->>API: GET /v1/models
API-->>ModelsSvc: ApiRouterModelsListResponse
Note right of API: {data: [{id, status, path, in_cache}]}
modelsStore->>modelsStore: routerModels = $state(data)
modelsStore->>modelsStore: fetchModalitiesForLoadedModels()
loop each model where status === "loaded"
modelsStore->>PropsSvc: fetchForModel(modelId)
PropsSvc->>API: GET /props?model={modelId}
API-->>PropsSvc: ApiLlamaCppServerProps
modelsStore->>modelsStore: modelPropsCache.set(modelId, props)
end
modelsStore->>modelsStore: propsCacheVersion++
deactivate modelsStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 🔄 MODEL SELECTION (ROUTER mode)
%% ═══════════════════════════════════════════════════════════════════════════
UI->>Hooks: useModelChangeValidation({getRequiredModalities, onSuccess?, onValidationFailure?})
Note over Hooks: Hook configured per-component:<br/>ChatForm: getRequiredModalities = usedModalities<br/>ChatMessage: getRequiredModalities = getModalitiesUpToMessage(msgId)
UI->>Hooks: handleModelChange(modelId, modelName)
activate Hooks
Hooks->>Hooks: previousSelectedModelId = modelsStore.selectedModelId
Hooks->>modelsStore: isModelLoaded(modelName)?
alt model NOT loaded
Hooks->>modelsStore: loadModel(modelName)
Note over modelsStore: → see LOAD MODEL section below
end
Note over Hooks: Always fetch props (from cache or API)
Hooks->>modelsStore: fetchModelProps(modelName)
modelsStore-->>Hooks: props
Hooks->>convStore: getRequiredModalities()
convStore-->>Hooks: {vision, audio}
Hooks->>Hooks: Validate: model.modalities ⊇ required?
alt validation PASSED
Hooks->>modelsStore: selectModelById(modelId)
Hooks-->>UI: return true
else validation FAILED
Hooks->>UI: toast.error("Model doesn't support required modalities")
alt model was just loaded
Hooks->>modelsStore: unloadModel(modelName)
end
alt onValidationFailure provided
Hooks->>modelsStore: selectModelById(previousSelectedModelId)
end
Hooks-->>UI: return false
end
deactivate Hooks
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: ⬆️ LOAD MODEL (ROUTER mode)
%% ═══════════════════════════════════════════════════════════════════════════
modelsStore->>modelsStore: loadModel(modelId)
activate modelsStore
alt already loaded
modelsStore-->>modelsStore: return (no-op)
end
modelsStore->>modelsStore: modelLoadingStates.set(modelId, true)
modelsStore->>ModelsSvc: load(modelId)
ModelsSvc->>API: POST /models/load {model: modelId}
API-->>ModelsSvc: {status: "loading"}
modelsStore->>modelsStore: pollForModelStatus(modelId, LOADED)
loop poll every 500ms (max 60 attempts)
modelsStore->>modelsStore: fetchRouterModels()
modelsStore->>ModelsSvc: listRouter()
ModelsSvc->>API: GET /v1/models
API-->>ModelsSvc: models[]
modelsStore->>modelsStore: getModelStatus(modelId)
alt status === LOADED
Note right of modelsStore: break loop
else status === LOADING
Note right of modelsStore: wait 500ms, continue
end
end
modelsStore->>modelsStore: updateModelModalities(modelId)
modelsStore->>PropsSvc: fetchForModel(modelId)
PropsSvc->>API: GET /props?model={modelId}
API-->>PropsSvc: props with modalities
modelsStore->>modelsStore: modelPropsCache.set(modelId, props)
modelsStore->>modelsStore: propsCacheVersion++
modelsStore->>modelsStore: modelLoadingStates.set(modelId, false)
deactivate modelsStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: ⬇️ UNLOAD MODEL (ROUTER mode)
%% ═══════════════════════════════════════════════════════════════════════════
modelsStore->>modelsStore: unloadModel(modelId)
activate modelsStore
modelsStore->>modelsStore: modelLoadingStates.set(modelId, true)
modelsStore->>ModelsSvc: unload(modelId)
ModelsSvc->>API: POST /models/unload {model: modelId}
modelsStore->>modelsStore: pollForModelStatus(modelId, UNLOADED)
loop poll until unloaded
modelsStore->>ModelsSvc: listRouter()
ModelsSvc->>API: GET /v1/models
end
modelsStore->>modelsStore: modelLoadingStates.set(modelId, false)
deactivate modelsStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 📊 COMPUTED GETTERS
%% ═══════════════════════════════════════════════════════════════════════════
Note over modelsStore: Getters:<br/>- selectedModel: ModelOption | null<br/>- loadedModelIds: string[] (from routerModels)<br/>- loadingModelIds: string[] (from modelLoadingStates)<br/>- singleModelName: string | null (MODEL mode only)
Note over modelsStore: Modality helpers:<br/>- getModelModalities(modelId): {vision, audio}<br/>- modelSupportsVision(modelId): boolean<br/>- modelSupportsAudio(modelId): boolean
```
-76
View File
@@ -1,76 +0,0 @@
```mermaid
sequenceDiagram
participant UI as 🧩 +layout.svelte
participant serverStore as 🗄️ serverStore
participant PropsSvc as ⚙️ PropsService
participant API as 🌐 llama-server
Note over serverStore: State:<br/>props: ApiLlamaCppServerProps | null<br/>loading, error<br/>role: ServerRole | null (MODEL | ROUTER)<br/>fetchPromise (deduplication)
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 🚀 INITIALIZATION
%% ═══════════════════════════════════════════════════════════════════════════
UI->>serverStore: fetch()
activate serverStore
alt fetchPromise exists (already fetching)
serverStore-->>UI: return fetchPromise
Note right of serverStore: Deduplicate concurrent calls
end
serverStore->>serverStore: loading = true
serverStore->>serverStore: fetchPromise = new Promise()
serverStore->>PropsSvc: fetch()
PropsSvc->>API: GET /props
API-->>PropsSvc: ApiLlamaCppServerProps
Note right of API: {role, model_path, model_alias,<br/>modalities, default_generation_settings, ...}
PropsSvc-->>serverStore: props
serverStore->>serverStore: props = $state(data)
serverStore->>serverStore: detectRole(props)
Note right of serverStore: role = props.role === "router"<br/> ? ServerRole.ROUTER<br/> : ServerRole.MODEL
serverStore->>serverStore: loading = false
serverStore->>serverStore: fetchPromise = null
deactivate serverStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 📊 COMPUTED GETTERS
%% ═══════════════════════════════════════════════════════════════════════════
Note over serverStore: Getters from props:
rect rgb(240, 255, 240)
Note over serverStore: defaultParams<br/>→ props.default_generation_settings.params<br/>(temperature, top_p, top_k, etc.)
end
rect rgb(240, 255, 240)
Note over serverStore: contextSize<br/>→ props.default_generation_settings.n_ctx
end
rect rgb(255, 240, 240)
Note over serverStore: isRouterMode<br/>→ role === ServerRole.ROUTER
end
rect rgb(255, 240, 240)
Note over serverStore: isModelMode<br/>→ role === ServerRole.MODEL
end
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: 🔗 RELATIONSHIPS
%% ═══════════════════════════════════════════════════════════════════════════
Note over serverStore: Used by:
Note right of serverStore: - modelsStore: role detection, MODEL mode modalities<br/>- settingsStore: syncWithServerDefaults (defaultParams)<br/>- chatStore: contextSize for processing state<br/>- UI components: isRouterMode for conditional rendering
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,API: ❌ ERROR HANDLING
%% ═══════════════════════════════════════════════════════════════════════════
Note over serverStore: getErrorMessage(): string | null<br/>Returns formatted error for UI display
Note over serverStore: clear(): void<br/>Resets all state (props, error, loading, role)
```
-156
View File
@@ -1,156 +0,0 @@
```mermaid
sequenceDiagram
participant UI as 🧩 ChatSettings
participant settingsStore as 🗄️ settingsStore
participant serverStore as 🗄️ serverStore
participant ParamSvc as ⚙️ ParameterSyncService
participant LS as 💾 LocalStorage
Note over settingsStore: State:<br/>config: SettingsConfigType<br/>theme: string ("auto" | "light" | "dark")<br/>isInitialized: boolean<br/>userOverrides: Set&lt;string&gt;
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,LS: 🚀 INITIALIZATION
%% ═══════════════════════════════════════════════════════════════════════════
Note over settingsStore: Auto-initialized in constructor (browser only)
settingsStore->>settingsStore: initialize()
activate settingsStore
settingsStore->>settingsStore: loadConfig()
settingsStore->>LS: get("llama-config")
LS-->>settingsStore: StoredConfig | null
alt config exists
settingsStore->>settingsStore: Merge with SETTING_CONFIG_DEFAULT
Note right of settingsStore: Fill missing keys with defaults
else no config
settingsStore->>settingsStore: config = SETTING_CONFIG_DEFAULT
end
settingsStore->>LS: get("llama-userOverrides")
LS-->>settingsStore: string[] | null
settingsStore->>settingsStore: userOverrides = new Set(data)
settingsStore->>settingsStore: loadTheme()
settingsStore->>LS: get("llama-theme")
LS-->>settingsStore: theme | "auto"
settingsStore->>settingsStore: isInitialized = true
deactivate settingsStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,LS: 🔄 SYNC WITH SERVER DEFAULTS
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI: Triggered from +layout.svelte when serverStore.props loaded
UI->>settingsStore: syncWithServerDefaults()
activate settingsStore
settingsStore->>serverStore: defaultParams
serverStore-->>settingsStore: {temperature, top_p, top_k, ...}
loop each SYNCABLE_PARAMETER
alt key NOT in userOverrides
settingsStore->>settingsStore: config[key] = serverDefault[key]
Note right of settingsStore: Non-overridden params adopt server default
else key in userOverrides
Note right of settingsStore: Keep user value, skip server default
end
end
alt serverStore.props has uiSettings
settingsStore->>settingsStore: Apply uiSettings from server
Note right of settingsStore: Server-provided UI settings<br/>(e.g. showRawOutputSwitch)
end
settingsStore->>settingsStore: saveConfig()
deactivate settingsStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,LS: ⚙️ UPDATE CONFIG
%% ═══════════════════════════════════════════════════════════════════════════
UI->>settingsStore: updateConfig(key, value)
activate settingsStore
settingsStore->>settingsStore: config[key] = value
alt value matches server default for key
settingsStore->>settingsStore: userOverrides.delete(key)
Note right of settingsStore: Matches server default, remove override
else value differs from server default
settingsStore->>settingsStore: userOverrides.add(key)
Note right of settingsStore: Mark as user-modified (won't be overwritten)
end
settingsStore->>settingsStore: saveConfig()
settingsStore->>LS: set(CONFIG_LOCALSTORAGE_KEY, config)
settingsStore->>LS: set(USER_OVERRIDES_LOCALSTORAGE_KEY, [...userOverrides])
deactivate settingsStore
UI->>settingsStore: updateMultipleConfig({key1: val1, key2: val2})
activate settingsStore
Note right of settingsStore: Batch update, single save
settingsStore->>settingsStore: For each key: config[key] = value
settingsStore->>settingsStore: For each key: userOverrides.add(key)
settingsStore->>settingsStore: saveConfig()
deactivate settingsStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,LS: 🔄 RESET
%% ═══════════════════════════════════════════════════════════════════════════
UI->>settingsStore: resetConfig()
activate settingsStore
settingsStore->>settingsStore: config = {...SETTING_CONFIG_DEFAULT}
settingsStore->>settingsStore: userOverrides.clear()
Note right of settingsStore: All params reset to defaults<br/>Next syncWithServerDefaults will adopt server values
settingsStore->>settingsStore: saveConfig()
deactivate settingsStore
UI->>settingsStore: resetParameterToServerDefault(key)
activate settingsStore
settingsStore->>settingsStore: userOverrides.delete(key)
settingsStore->>serverStore: defaultParams[key]
settingsStore->>settingsStore: config[key] = serverDefault
settingsStore->>settingsStore: saveConfig()
deactivate settingsStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,LS: 🎨 THEME
%% ═══════════════════════════════════════════════════════════════════════════
UI->>settingsStore: updateTheme(newTheme)
activate settingsStore
settingsStore->>settingsStore: theme = newTheme
settingsStore->>settingsStore: saveTheme()
settingsStore->>LS: set("llama-theme", theme)
deactivate settingsStore
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,LS: 📊 PARAMETER INFO
%% ═══════════════════════════════════════════════════════════════════════════
UI->>settingsStore: getParameterInfo(key)
settingsStore->>ParamSvc: getParameterInfo(key, config, serverDefaults, userOverrides)
ParamSvc-->>settingsStore: ParameterInfo
Note right of ParamSvc: {<br/> currentValue,<br/> serverDefault,<br/> isUserOverride: boolean,<br/> canSync: boolean,<br/> isDifferentFromServer: boolean<br/>}
UI->>settingsStore: getParameterDiff()
settingsStore->>ParamSvc: createParameterDiff(config, serverDefaults, userOverrides)
ParamSvc-->>settingsStore: ParameterDiff[]
Note right of ParamSvc: Array of parameters where user != server
%% ═══════════════════════════════════════════════════════════════════════════
Note over UI,LS: 📋 CONFIG CATEGORIES
%% ═══════════════════════════════════════════════════════════════════════════
Note over settingsStore: Syncable with server (from /props):
rect rgb(240, 255, 240)
Note over settingsStore: temperature, top_p, top_k, min_p<br/>repeat_penalty, presence_penalty, frequency_penalty<br/>dynatemp_range, dynatemp_exponent<br/>typ_p, xtc_probability, xtc_threshold<br/>dry_multiplier, dry_base, dry_allowed_length, dry_penalty_last_n
end
Note over settingsStore: UI-only (not synced):
rect rgb(255, 240, 240)
Note over settingsStore: systemMessage, custom (JSON)<br/>showStatistics, enableContinueGeneration<br/>autoMicOnEmpty, disableAutoScroll<br/>apiKey, pdfAsImage, disableReasoningParsing, showRawOutputSwitch
end
```
+83 -1
View File
@@ -12,6 +12,49 @@ import { fileURLToPath } from 'node:url';
import ts from 'typescript-eslint';
const gitignorePath = fileURLToPath(new URL('./.gitignore', import.meta.url));
// Require a blank line between consecutive class accessors (get/set). The core
// `padding-line-between-statements` rule only handles statements, not class
// members, so this is enforced with a small custom rule.
const blankLineBetweenAccessors = {
create(context) {
return {
MethodDefinition(node) {
if (node.kind !== 'get' && node.kind !== 'set') return;
const body = node.parent;
if (!body || body.type !== 'ClassBody') return;
const index = body.body.indexOf(node);
if (index <= 0) return;
const prev = body.body[index - 1];
if (prev.type !== 'MethodDefinition' || (prev.kind !== 'get' && prev.kind !== 'set'))
return;
if (node.loc.start.line - prev.loc.end.line <= 1) {
context.report({
fix(fixer) {
// Insert after the previous accessor's closing brace so the blank
// line keeps the current accessor's indentation.
return fixer.insertTextAfter(prev, '\n');
},
message: 'Expected a blank line between class accessors (get/set).',
node
});
}
}
};
},
meta: {
docs: { description: 'Require a blank line between consecutive class accessors (get/set).' },
fixable: 'whitespace',
schema: [],
type: 'layout'
}
};
export default ts.config(
includeIgnoreFile(gitignorePath),
@@ -22,7 +65,11 @@ export default ts.config(
...svelte.configs.prettier,
{
languageOptions: { globals: { ...globals.browser, ...globals.node } },
plugins: { perfectionist, 'simple-import-sort': simpleImportSort },
plugins: {
local: { rules: { 'blank-line-between-accessors': blankLineBetweenAccessors } },
perfectionist,
'simple-import-sort': simpleImportSort
},
rules: {
// Snippet bodies often ignore one or more of the parent's params
// (e.g. `{#snippet children(_meta, ctx)}` when only ctx is read).
@@ -30,8 +77,11 @@ export default ts.config(
'error',
{ argsIgnorePattern: '^_', varsIgnorePattern: '^_' }
],
// Enforce empty line at end of file
'eol-last': 'error',
// Enforce a blank line between consecutive get/set accessors
'local/blank-line-between-accessors': 'error',
// typescript-eslint strongly recommend that you do not use the no-undef lint rule on TypeScript projects.
// see: https://typescript-eslint.io/troubleshooting/faqs/eslint/#i-get-errors-from-the-no-undef-rule-about-global-variables-not-being-defined-even-though-there-are-no-typescript-errors
'no-undef': 'off',
@@ -61,6 +111,38 @@ export default ts.config(
{ blankLine: 'always', next: ['return', 'throw', 'break', 'continue'], prev: '*' }
],
// Class member order: public fields -> private fields -> constructor -> getters
// -> setters -> public methods -> private methods, alphabetical within each.
// Svelte $derived fields must stay in dependency order (forward references are
// rejected), so the two stores that rely on that are exempted below.
'perfectionist/sort-classes': [
'error',
{
customGroups: [
{ groupName: 'public-field', modifiers: ['public'], selector: 'property' },
{ groupName: 'private-field', modifiers: ['private'], selector: 'property' },
{ groupName: 'get-method', selector: 'get-method' },
{ groupName: 'set-method', selector: 'set-method' },
{ groupName: 'public-method', modifiers: ['public'], selector: 'method' },
{ groupName: 'private-method', modifiers: ['private'], selector: 'method' }
],
groups: [
'public-field',
'private-field',
'constructor',
'get-method',
'set-method',
'public-method',
'private-method',
'unknown'
],
type: 'natural',
// Keep members in dependency order (Svelte rejects forward references in
// $derived fields), while still sorting the rest alphabetically.
useExperimentalDependencyDetection: true
}
],
// Alphabetical order for enum members
'perfectionist/sort-enums': ['error', { type: 'natural' }],
@@ -139,7 +139,7 @@
let fileSize = $derived(currentItem?.size ? formatFileSize(currentItem.size) : '');
let hasVisionModality = $derived(
currentItem && activeModelId ? modelsStore.modelSupportsVision(activeModelId) : false
currentItem && activeModelId ? modelsStore.props.modelSupportsVision(activeModelId) : false
);
let audioSrc = $derived(
@@ -28,7 +28,6 @@
import {
chatStore,
conversationsStore,
mcpResourceStore,
mcpStore,
modelsStore,
serverStore,
@@ -140,7 +139,9 @@
// float above the box.
let mentionAnchor: HTMLDivElement | null = $state(null);
let cwd = $derived(conversationsStore.activeConversation?.cwd ?? conversationsStore.pendingCwd);
let cwd = $derived(
conversationsStore.activeConversation?.cwd ?? conversationsStore.preferences.pendingCwd
);
const pickers = useChatFormPickers({
focusInput: refocusInput,
@@ -151,7 +152,8 @@
getShowModelSelector: () => showModelSelector,
getValue: () => value,
hasCwdTools: () => toolsStore.hasEnabledCwdTools,
hasPrompts: () => mcpStore.hasPromptsCapability(conversationsStore.getAllMcpServerOverrides()),
hasPrompts: () =>
mcpStore.hasPromptsCapability(conversationsStore.preferences.getAllMcpServerOverrides()),
openModelSelector: () => chatFormActionsRef?.openModelSelector(),
setCaretOffset: (offset) => inputRef?.setCaretOffset(offset),
setValue: (v) => {
@@ -170,7 +172,7 @@
onValueChange?.('');
}
await conversationsStore.setCwd(newDir);
await conversationsStore.preferences.setCwd(newDir);
if (conversationsStore.activeConversation) {
await chatStore.recordCwdChange(newDir?.trim() || null);
@@ -595,7 +597,7 @@
{useRichInput}
/>
{#if mcpResourceStore.hasAttachments}
{#if mcpStore.resources.hasAttachments}
<ChatFormMcpResourcesList
class="mb-3"
onResourceClick={(uri) => {
@@ -38,11 +38,11 @@
}
function isServerEnabledForChat(serverId: string): boolean {
return conversationsStore.isMcpServerEnabledForChat(serverId);
return conversationsStore.preferences.isMcpServerEnabledForChat(serverId);
}
async function toggleServerForChat(serverId: string) {
await conversationsStore.toggleMcpServerForChat(serverId);
await conversationsStore.preferences.toggleMcpServerForChat(serverId);
}
function handleMcpSubMenuOpen(open: boolean) {
@@ -218,12 +218,15 @@
{@const hasError = healthState.status === HealthCheckStatus.ERROR}
{@const displayName = mcpStore.getServerLabel(server)}
{@const faviconUrl = mcpStore.getServerFavicon(server.id)}
{@const isEnabled = conversationsStore.isMcpServerEnabledForChat(server.id)}
{@const isEnabled = conversationsStore.preferences.isMcpServerEnabledForChat(
server.id
)}
<button
type="button"
class={sheetItemRowClass}
onclick={() => !hasError && conversationsStore.toggleMcpServerForChat(server.id)}
onclick={() =>
!hasError && conversationsStore.preferences.toggleMcpServerForChat(server.id)}
disabled={hasError}
>
<div class="flex min-w-0 flex-1 items-center gap-2">
@@ -250,7 +253,8 @@
{:else}
<Switch
checked={isEnabled}
onCheckedChange={() => conversationsStore.toggleMcpServerForChat(server.id)}
onCheckedChange={() =>
conversationsStore.preferences.toggleMcpServerForChat(server.id)}
/>
{/if}
</button>
@@ -81,10 +81,10 @@
$effect(() => {
if (activeModelId) {
const cached = modelsStore.getModelProps(activeModelId);
const cached = modelsStore.props.getModelProps(activeModelId);
if (!cached) {
modelsStore.fetchModelProps(activeModelId).then(() => {
modelsStore.props.fetchModelProps(activeModelId).then(() => {
modelPropsVersion++;
});
}
@@ -94,19 +94,21 @@
$effect(() => {
void modelPropsVersion;
hasAudioModality = activeModelId ? modelsStore.modelSupportsAudio(activeModelId) : false;
hasAudioModality = activeModelId ? modelsStore.props.modelSupportsAudio(activeModelId) : false;
});
$effect(() => {
void modelPropsVersion;
hasVideoModality = activeModelId ? modelsStore.modelSupportsVideo(activeModelId) : false;
hasVideoModality = activeModelId ? modelsStore.props.modelSupportsVideo(activeModelId) : false;
});
$effect(() => {
void modelPropsVersion;
hasVisionModality = activeModelId ? modelsStore.modelSupportsVision(activeModelId) : false;
hasVisionModality = activeModelId
? modelsStore.props.modelSupportsVision(activeModelId)
: false;
});
$effect(() => {
@@ -58,13 +58,13 @@
let currentConfig = $derived(settingsStore.config);
let hasMcpPromptsSupport = $derived.by(() => {
const perChatOverrides = conversationsStore.getAllMcpServerOverrides();
const perChatOverrides = conversationsStore.preferences.getAllMcpServerOverrides();
return mcpStore.hasPromptsCapability(perChatOverrides);
});
let hasMcpResourcesSupport = $derived.by(() => {
const perChatOverrides = conversationsStore.getAllMcpServerOverrides();
const perChatOverrides = conversationsStore.preferences.getAllMcpServerOverrides();
return mcpStore.hasResourcesCapability(perChatOverrides);
});
@@ -121,7 +121,7 @@
if (!chatStore.isLoading && !chatStore.isStreaming()) return false;
const processingState = chatStore.activeProcessingState;
const processingState = chatStore.processing.activeState;
if (!processingState) return false;
@@ -16,7 +16,7 @@
$effect(() => {
const conv = conversationsStore.activeConversation;
untrack(() => chatStore.setActiveProcessingConversation(conv?.id ?? null));
untrack(() => chatStore.processing.setActiveConversation(conv?.id ?? null));
});
$effect(() => {
@@ -28,12 +28,12 @@
if (chatStore.isLoading || chatStore.isStreaming()) return;
if (messages.length === 0) {
untrack(() => chatStore.clearProcessingState(conv.id));
untrack(() => chatStore.processing.setState(conv.id, null));
return;
}
untrack(() => chatStore.restoreProcessingStateFromMessages(messages, conv.id));
untrack(() => chatStore.processing.restoreFromMessages(messages, conv.id));
});
$effect(() => {
@@ -3,7 +3,7 @@
ChatAttachmentsListItemMcpResource,
HorizontalScrollCarousel
} from '$lib/components/app';
import { mcpResourceStore, mcpStore } from '$lib/stores';
import { mcpStore } from '$lib/stores';
interface Props {
class?: string;
@@ -12,8 +12,8 @@
let { class: className, onResourceClick }: Props = $props();
const attachments = $derived(mcpResourceStore.attachments);
const hasAttachments = $derived(mcpResourceStore.hasAttachments);
const attachments = $derived(mcpStore.resources.attachments);
const hasAttachments = $derived(mcpStore.resources.hasAttachments);
function handleRemove(attachmentId: string) {
mcpStore.removeResourceAttachment(attachmentId);
@@ -87,7 +87,7 @@
isLoading = true;
try {
const perChatOverrides = conversationsStore.getAllMcpServerOverrides();
const perChatOverrides = conversationsStore.preferences.getAllMcpServerOverrides();
const initialized = await mcpStore.ensureInitialized(perChatOverrides);
if (!initialized) {
@@ -59,7 +59,7 @@
message.model ?? chatStore.getResumeModel(message.convId) ?? modelsStore.selectedModelName
);
let modelLoadProgress = $derived(
isRouter && loadTargetModel ? modelsStore.getLoadProgress(loadTargetModel) : null
isRouter && loadTargetModel ? modelsStore.status.getLoadProgress(loadTargetModel) : null
);
let modelLoadingText = $derived(modelLoadProgressText(modelLoadProgress));
@@ -31,7 +31,7 @@
pendingModel = modelId;
try {
await modelsStore.loadModel(modelId);
await modelsStore.status.load(modelId);
} finally {
pendingModel = null;
}
@@ -43,14 +43,14 @@
);
const hasReasoningError = $derived(
isLastAssistantMessage ? !!agenticStore.lastError(message.convId) : false
isLastAssistantMessage ? !!agenticStore.getLastError(message.convId) : false
);
let permissionDismissed = $state(false);
const pendingPermission = $derived(
isStreaming && isLastAssistantMessage
? agenticStore.pendingPermissionRequest(message.convId)
? agenticStore.getPendingPermissionRequest(message.convId)
: null
);
@@ -74,7 +74,7 @@
const pendingContinue = $derived(
isStreaming && isLastAssistantMessage
? agenticStore.pendingContinueRequest(message.convId)
? agenticStore.getPendingContinueRequest(message.convId)
: false
);
@@ -97,7 +97,7 @@
const sections = $derived(deriveAgenticSections(message, toolMessages, [], isStreaming));
const currentlyExecutingToolCallId = $derived(
isStreaming ? agenticStore.executingToolCallId(message.convId) : null
isStreaming ? agenticStore.getExecutingToolCallId(message.convId) : null
);
type TurnGroup = {
@@ -238,30 +238,30 @@
/>
{/each}
{#if conversationsStore.activeConversation && agenticStore.pendingSteeringMessageContent(conversationsStore.activeConversation!.id)}
{#if conversationsStore.activeConversation && agenticStore.getPendingSteeringMessageContent(conversationsStore.activeConversation!.id)}
{@const convId = conversationsStore.activeConversation!.id}
{@const pendingContent = agenticStore.pendingSteeringMessageContent(convId)}
{@const pendingContent = agenticStore.getPendingSteeringMessageContent(convId)}
{#if pendingContent}
<ChatMessageUserPending
class="mx-auto mt-12 w-full max-w-[48rem]"
content={pendingContent}
extras={agenticStore.pendingSteeringMessageExtras(convId)}
extras={agenticStore.getPendingSteeringMessageExtras(convId)}
onSendImmediately={() => chatStore.abortCurrentFlow(convId)}
onEdit={(newContent, extras) =>
agenticStore.injectSteeringMessage(convId, newContent, extras)}
onDelete={() => agenticStore.clearSteeringMessage(convId)}
/>
{/if}
{:else if conversationsStore.activeConversation && chatStore.pendingMessageContent(conversationsStore.activeConversation!.id)}
{:else if conversationsStore.activeConversation && chatStore.getPendingMessageContent(conversationsStore.activeConversation!.id)}
{@const convId = conversationsStore.activeConversation!.id}
{@const pendingContent = chatStore.pendingMessageContent(convId)}
{@const pendingContent = chatStore.getPendingMessageContent(convId)}
{#if pendingContent}
<ChatMessageUserPending
class="mx-auto mt-12 w-full max-w-[48rem]"
content={pendingContent}
extras={chatStore.pendingMessageExtras(convId)}
extras={chatStore.getPendingMessageExtras(convId)}
onSendImmediately={() => chatStore.abortCurrentFlow(convId)}
onEdit={(newContent, extras) => chatStore.injectPendingMessage(convId, newContent, extras)}
onDelete={() => chatStore.clearPendingMessage(convId)}
@@ -8,7 +8,7 @@
import { Button } from '$lib/components/ui/button';
import * as Dialog from '$lib/components/ui/dialog';
import { ICON_CLASS_DEFAULT } from '$lib/constants';
import { conversationsStore, mcpResourceStore, mcpStore } from '$lib/stores';
import { conversationsStore, mcpStore } from '$lib/stores';
import type { MCPResourceContent, MCPResourceInfo, MCPResourceTemplateInfo } from '$lib/types';
import { getResourceDisplayName } from '$lib/utils';
import { SvelteSet } from 'svelte/reactivity';
@@ -33,7 +33,7 @@
let templatePreviewLoading = $state(false);
let templatePreviewError = $state<string | null>(null);
const totalCount = $derived(mcpResourceStore.totalResourceCount);
const totalCount = $derived(mcpStore.resources.totalResourceCount);
$effect(() => {
if (open) {
@@ -48,7 +48,7 @@
});
async function loadResources() {
const perChatOverrides = conversationsStore.getAllMcpServerOverrides();
const perChatOverrides = conversationsStore.preferences.getAllMcpServerOverrides();
const initialized = await mcpStore.ensureInitialized(perChatOverrides);
if (initialized) {
@@ -126,16 +126,16 @@
isAttaching = true;
try {
const knownResource = mcpResourceStore.findResourceByUri(templatePreviewUri);
const knownResource = mcpStore.resources.findResourceByUri(templatePreviewUri);
if (knownResource) {
if (!mcpResourceStore.isAttached(knownResource.uri)) {
if (!mcpStore.resources.isAttached(knownResource.uri)) {
await mcpStore.attachResource(knownResource.uri);
}
toast.success(`Resource attached: ${knownResource.title || knownResource.name}`);
} else {
if (mcpResourceStore.isAttached(templatePreviewUri)) {
if (mcpStore.resources.isAttached(templatePreviewUri)) {
toast.info('Resource already attached');
handleOpenChange(false);
@@ -147,9 +147,9 @@
serverName: selectedTemplate.serverName,
uri: templatePreviewUri
};
const attachment = mcpResourceStore.addAttachment(resourceInfo);
const attachment = mcpStore.resources.addAttachment(resourceInfo);
mcpResourceStore.updateAttachmentContent(attachment.id, templatePreviewContent);
mcpStore.resources.updateAttachmentContent(attachment.id, templatePreviewContent);
toast.success(`Resource attached: ${resourceInfo.name}`);
}
@@ -199,7 +199,7 @@
function getAllResourcesFlatInTreeOrder(): MCPResourceInfo[] {
const allResources: MCPResourceInfo[] = [];
const resourcesMap = mcpResourceStore.serverResources;
const resourcesMap = mcpStore.resources.serverResources;
for (const [serverName, serverRes] of resourcesMap.entries()) {
for (const resource of serverRes.resources) {
@@ -234,7 +234,7 @@
useProxy: newServerUseProxy
});
conversationsStore.setMcpServerOverride(newServerId, true);
conversationsStore.preferences.setMcpServerOverride(newServerId, true);
handleOpenChange(false);
}
@@ -42,7 +42,7 @@
let modalities = $derived.by(() => {
if (!firstModel?.id) return [];
return modelsStore.getModelModalitiesArray(firstModel.id);
return modelsStore.props.getModelModalitiesArray(firstModel.id);
});
// Ensure models are fetched when dialog opens
@@ -56,7 +56,7 @@
$effect(() => {
if (open && isRouter && modelId) {
isLoadingRouterProps = true;
modelsStore
modelsStore.props
.fetchModelProps(modelId)
.then((props) => {
routerModelProps = props;
@@ -14,7 +14,9 @@
let mcpServers = $derived(mcpStore.getServers().filter((s) => s.enabled));
let enabledMcpServersForChat = $derived(
mcpServers.filter((s) => conversationsStore.isMcpServerEnabledForChat(s.id) && s.url.trim())
mcpServers.filter(
(s) => conversationsStore.preferences.isMcpServerEnabledForChat(s.id) && s.url.trim()
)
);
let healthyEnabledMcpServers = $derived(
enabledMcpServersForChat.filter((s) => {
@@ -2,7 +2,7 @@
import McpResourcesBrowserEmptyState from './McpResourcesBrowserEmptyState.svelte';
import McpResourcesBrowserHeader from './McpResourcesBrowserHeader.svelte';
import McpResourcesBrowserServerItem from './McpResourcesBrowserServerItem.svelte';
import { mcpResourceStore, mcpStore } from '$lib/stores';
import { mcpStore } from '$lib/stores';
import type { MCPResourceInfo, MCPResourceTemplateInfo, MCPServerResources } from '$lib/types';
import { parseResourcePath } from '$lib/utils';
import { SvelteMap, SvelteSet } from 'svelte/reactivity';
@@ -31,8 +31,8 @@
let expandedFolders = new SvelteSet<string>();
let searchQuery = $state('');
const resources = $derived(mcpResourceStore.serverResources);
const isLoading = $derived(mcpResourceStore.isLoading);
const resources = $derived(mcpStore.resources.serverResources);
const isLoading = $derived(mcpStore.resources.isLoading);
const filteredResources = $derived.by(() => {
if (!searchQuery.trim()) {
@@ -116,7 +116,7 @@
if (status === ServerModelStatus.LOADING) return;
await modelsStore.unloadModel(modelId);
await modelsStore.status.unload(modelId);
}
export function open() {
@@ -174,9 +174,9 @@
{@const triggerLoading =
!!triggerModel &&
(triggerStatus === ServerModelStatus.LOADING ||
modelsStore.isModelOperationInProgress(triggerModel))}
modelsStore.status.isOperationInProgress(triggerModel))}
{@const triggerLoadPercent = triggerLoading
? Math.round(modelLoadFraction(modelsStore.getLoadProgress(triggerModel)) * 100)
? Math.round(modelLoadFraction(modelsStore.status.getLoadProgress(triggerModel)) * 100)
: 0}
{#if ms.isRouter}

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