CUDA: extend K-type validation to V-types for flash attention (#24403)

* CUDA: extend K-type validation to V-types for flash attention

* reorder

ggml/src/ggml-cpu/arch/arm/quants.c

@@ -812,10 +812,10 @@ void ggml_vec_dot_nvfp4_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
         const float dy0 = GGML_CPU_FP16_TO_FP32(y[2*ib].d);
         const float dy1 = GGML_CPU_FP16_TO_FP32(y[2*ib+1].d);
         const float32x4_t nvsc = {
-            ggml_ue4m3_to_fp32(x[ib].d[0]),
-            ggml_ue4m3_to_fp32(x[ib].d[1]),
-            ggml_ue4m3_to_fp32(x[ib].d[2]),
-            ggml_ue4m3_to_fp32(x[ib].d[3])
+            GGML_CPU_UE4M3_TO_FP32(x[ib].d[0]),
+            GGML_CPU_UE4M3_TO_FP32(x[ib].d[1]),
+            GGML_CPU_UE4M3_TO_FP32(x[ib].d[2]),
+            GGML_CPU_UE4M3_TO_FP32(x[ib].d[3])
         };
         const float32x4_t scales = vmulq_f32(nvsc, (float32x4_t){dy0, dy0, dy1, dy1});
 

ggml/src/ggml-cpu/llamafile/sgemm.cpp

@@ -2321,24 +2321,28 @@ class tinyBLAS_Q0_PPC {
     }
 
     void matmul(int64_t m, int64_t n) {
-    #if defined(_AIX) || defined(__BIG_ENDIAN__)
-        mnpack(0, m, 0, n);
-    #else
-        const int64_t mc = 64;
-        const int64_t kc = 64;
+        int64_t mc = 64;
         int64_t nc = 64;
+        int64_t kc = 64;
+        int64_t n_chunk = 64;
+    #if defined(_AIX) || defined(__BIG_ENDIAN__)
+        mc = 32;
+        nc = 32;
+        kc = 32;
+        n_chunk = 32
+    #endif
         int64_t n_aligned = 0;
-        if (n % 64 == 0) {
+        if (n % n_chunk == 0) {
             n_aligned = n;
         } else if (n == 4) {
             n_aligned = 4;
-        } else if (n < 64) {
+        } else if (n < n_chunk) {
             n_aligned = (n / 8) * 8;
         } else {
-            n_aligned = (n / 64) * 64;
+            n_aligned = (n / n_chunk) * n_chunk;
         }
         if (n_aligned > 0) {
-            if (n_aligned % 64 == 0)      nc = 64;
+            if (n_aligned % n_chunk == 0) nc = n_chunk;
             else if (n_aligned == n)      nc = n;
             else if (n_aligned % 32 == 0) nc = 32;
             else if (n_aligned % 24 == 0) nc = 24;
@@ -2354,7 +2358,6 @@ class tinyBLAS_Q0_PPC {
         } else {
             mnpack(0, m, 0, n);
         }
-    #endif
     }
 
   private:
@@ -3195,16 +3198,19 @@ class tinyBLAS_PPC {
     }
 
     void matmul(int64_t m, int64_t n) {
+        int64_t mc = 256;
+        int64_t nc = 256;
+        int64_t kc = 256;
     #if defined(_AIX) || defined(__BIG_ENDIAN__)
-        mnpack(0, m, 0, n);
-    #else
-        int64_t mc = 256; int64_t nc = 256; int64_t kc = 256;
+        mc = 128;
+        nc = 128;
+        kc = 128;
+    #endif
         if (m % mc == 0 && n % nc == 0 && k % kc == 0) {
             matmul_tiled(m, n, mc, nc, kc);
         } else {
             mnpack(0, m, 0, n);
         }
-    #endif
     }
 
   private:

ggml/src/ggml-cpu/simd-mappings.h

@@ -131,8 +131,8 @@ extern float ggml_table_f32_ue4m3[1 << 8];
 #define GGML_CPU_E8M0_TO_FP32_HALF(x) GGML_E8M0_TO_FP32_HALF(x)
 #endif
 
-// Use lookup table for UE4M3 on x86 (faster than bit manipulation)
-#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
+// Use lookup table for UE4M3 on x86 and ARM (faster than bit manipulation)
+#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__) || defined(__ARM_NEON)
 #define GGML_CPU_UE4M3_TO_FP32(x) ggml_table_f32_ue4m3[(uint8_t)(x)]
 #else
 #define GGML_CPU_UE4M3_TO_FP32(x) ggml_ue4m3_to_fp32(x)

ggml/src/ggml-cuda/conv-transpose-1d.cu

@@ -11,30 +11,32 @@ static  __global__ void conv_transpose_1d_kernel(
         return;
     }
 
-    int out_index = global_index / dst_ne0;
+    int out_t = global_index % dst_ne0;
+    int out_ch = (global_index / dst_ne0) % dst_ne1;
+    int plane = global_index / (dst_ne0 * dst_ne1);
 
     float accumulator = 0;
 
     for (int c = 0; c < src0_ne2; c++) {
-        int idx = global_index % dst_ne0;
+        int kernel_offset = src0_ne0 * (out_ch + src0_ne1 * c);
+        int input_offset = src1_ne0 * (c + src1_ne1 * plane);
 
-        int kernel_offset = (src0_ne0 * src0_ne1 * c) + (out_index * src0_ne0);
-        int input_offset = src1_ne0 * c;
-
-        for (int i = 0; i < src1_ne0; i++) {
-            if (!(idx >= i*s0 && idx < i*s0 + src0_ne0)) {
+        for (int k = 0; k < src0_ne0; k++) {
+            int input_numer = out_t + p0 - k*d0;
+            if (input_numer < 0 || input_numer % s0 != 0) {
                 continue;
             }
-            int weight_idx = idx - i*s0;
 
-            float kernel_weight = src0[kernel_offset + weight_idx];
-            float input_value =  src1[input_offset+i];
+            int input_t = input_numer / s0;
+            if (input_t >= src1_ne0) {
+                continue;
+            }
 
-            accumulator += kernel_weight * input_value;
+            accumulator += src0[kernel_offset + k] * src1[input_offset + input_t];
         }
     }
     dst[global_index] = accumulator;
-    GGML_UNUSED_VARS(p0, d0, src0_ne3, src1_ne3, dst_ne3, src1_ne1, dst_ne1, src1_ne2, dst_ne2);
+    GGML_UNUSED_VARS(src0_ne3, src1_ne2, src1_ne3, dst_ne2, dst_ne3);
 }
 
 static void conv_transpose_1d_f32_f32_cuda(

ggml/src/ggml-cuda/fattn.cu

@@ -337,6 +337,26 @@ enum best_fattn_kernel {
     BEST_FATTN_KERNEL_MMA_F16  = 400,
 };
 
+static bool ggml_cuda_fattn_kv_type_supported(ggml_type type) {
+    switch (type) {
+        case GGML_TYPE_F32:
+        case GGML_TYPE_F16:
+            return true;
+        case GGML_TYPE_Q4_1:
+        case GGML_TYPE_Q5_0:
+        case GGML_TYPE_Q5_1:
+#ifndef GGML_CUDA_FA_ALL_QUANTS
+            return false;
+#endif // GGML_CUDA_FA_ALL_QUANTS
+        case GGML_TYPE_Q4_0:
+        case GGML_TYPE_Q8_0:
+        case GGML_TYPE_BF16:
+            return true;
+        default:
+            return false;
+    }
+}
+
 static best_fattn_kernel ggml_cuda_get_best_fattn_kernel(const int device, const ggml_tensor * dst) {
 #ifndef FLASH_ATTN_AVAILABLE
     GGML_UNUSED(device); GGML_UNUSED(dst);
@@ -427,22 +447,8 @@ static best_fattn_kernel ggml_cuda_get_best_fattn_kernel(const int device, const
     }
 #endif // GGML_CUDA_FA_ALL_QUANTS
 
-    switch (K->type) {
-        case GGML_TYPE_F32:
-        case GGML_TYPE_F16:
-            break;
-        case GGML_TYPE_Q4_1:
-        case GGML_TYPE_Q5_0:
-        case GGML_TYPE_Q5_1:
-#ifndef GGML_CUDA_FA_ALL_QUANTS
-            return BEST_FATTN_KERNEL_NONE;
-#endif // GGML_CUDA_FA_ALL_QUANTS
-        case GGML_TYPE_Q4_0:
-        case GGML_TYPE_Q8_0:
-        case GGML_TYPE_BF16:
-            break;
-        default:
-            return BEST_FATTN_KERNEL_NONE;
+    if (!ggml_cuda_fattn_kv_type_supported(K->type) || !ggml_cuda_fattn_kv_type_supported(V->type)) {
+        return BEST_FATTN_KERNEL_NONE;
     }
 
     if (mask && mask->ne[2] != 1) {

ggml/src/ggml-hip/CMakeLists.txt

@@ -155,3 +155,5 @@ if (GGML_HIP_RCCL)
 endif()
 
 target_link_libraries(ggml-hip PRIVATE ggml-base hip::host roc::rocblas roc::hipblas)
+
+target_compile_options(ggml-hip PRIVATE "$<$<COMPILE_LANGUAGE:HIP>:-ffast-math>")

ggml/src/ggml-vulkan/ggml-vulkan.cpp

@@ -129,7 +129,7 @@ typedef struct VkPhysicalDeviceShaderMixedFloatDotProductFeaturesVALVE {
 #endif
 
 #define ROUNDUP_POW2(M, N) (((M) + (N) - 1) & ~((N) - 1))
-#define CEIL_DIV(M, N) (((M) + (N)-1) / (N))
+#define CEIL_DIV(M, N) (((M) / (N)) + (((M) % (N)) != 0))
 static bool is_pow2(uint32_t x) { return x > 1 && (x & (x-1)) == 0; }
 
 #define VK_VENDOR_ID_AMD 0x1002

scripts/ui-assets.cmake

@@ -186,6 +186,12 @@ function(hf_download version out_var out_resolved)
 
     set(archive "${UI_BINARY_DIR}/dist.tar.gz")
 
+    # Use HF_TOKEN to benefit from higher rate limits
+    set(auth_headers "")
+    if(DEFINED ENV{HF_TOKEN} AND NOT "$ENV{HF_TOKEN}" STREQUAL "")
+        list(APPEND auth_headers "HTTPHEADER" "Authorization: Bearer $ENV{HF_TOKEN}")
+    endif()
+
     set(candidates "")
     if(NOT "${version}" STREQUAL "")
         list(APPEND candidates "${version}")
@@ -198,7 +204,7 @@ function(hf_download version out_var out_resolved)
         message(STATUS "UI: downloading from ${resolved}: ${base}/dist.tar.gz")
 
         file(DOWNLOAD "${base}/dist.tar.gz?download=true" "${archive}"
-            STATUS status TIMEOUT 300
+            STATUS status TIMEOUT 300 ${auth_headers}
         )
         list(GET status 0 rc)
         if(NOT rc EQUAL 0)
@@ -208,7 +214,7 @@ function(hf_download version out_var out_resolved)
         endif()
 
         file(DOWNLOAD "${base}/dist.tar.gz.sha256?download=true" "${archive}.sha256"
-            STATUS status TIMEOUT 30
+            STATUS status TIMEOUT 30 ${auth_headers}
         )
         list(GET status 0 rc)
         if(NOT rc EQUAL 0)

src/llama-model.cpp

@@ -1012,9 +1012,17 @@ struct llama_model::impl {
     std::vector<layer_dev> dev_layer;
 
     bool has_tensor_overrides;
+
+    std::vector<float> tensor_split_owned;
 };
 
 llama_model::llama_model(const llama_model_params & params) : params(params), pimpl(std::make_unique<impl>()) {
+    if (params.tensor_split != nullptr) {
+        // llama_model_params stores tensor_split as a borrowed pointer, but the model
+        // may need it later for tensor-parallel KV-cache split metadata.
+        pimpl->tensor_split_owned.assign(params.tensor_split, params.tensor_split + llama_max_devices());
+        this->params.tensor_split = pimpl->tensor_split_owned.data();
+    }
     pimpl->has_tensor_overrides = params.tensor_buft_overrides && params.tensor_buft_overrides[0].pattern;
 }
 

tools/server/tests/unit/test_router.py

@@ -314,6 +314,7 @@ def _wait_for_sse_event(collected: list, event_type: str, model: str, timeout: i
     return False
 
 
+@pytest.mark.skip(reason="sse_thread sometimes hangs on GH actions, to be investigated")
 def test_router_download_model():
     """Case 1: download a model, verify SSE events and GET /models."""
     global server
@@ -357,6 +358,7 @@ def test_router_download_model():
     assert MODEL_DOWNLOAD_ID in ids, f"{MODEL_DOWNLOAD_ID} not found in /models after download"
 
 
+@pytest.mark.skip(reason="sse_thread sometimes hangs on GH actions, to be investigated")
 def test_router_delete_model():
     """Case 2: delete the downloaded model, verify it disappears from GET /models."""
     global server

tools/ui/src/lib/components/app/navigation/SidebarNavigation/SidebarNavigation.svelte

@@ -27,7 +27,10 @@
 
 	let { onSearchClick = () => {} }: Props = $props();
 
-	const { handleKeydown } = useKeyboardShortcuts({ activateSearchMode: () => onSearchClick() });
+	const { handleKeydown } = useKeyboardShortcuts({
+		activateSearchMode: () => onSearchClick(),
+		toggleSidebar: () => toggleExpandedMode()
+	});
 
 	let isExpandedMode = $state(false);
 	let hoveredTooltip = $state<string | null>(null);

tools/ui/src/lib/enums/keyboard.enums.ts

@@ -9,6 +9,7 @@ export enum KeyboardKey {
 	ARROW_LEFT = 'ArrowLeft',
 	ARROW_RIGHT = 'ArrowRight',
 	TAB = 'Tab',
+	B_LOWER = 'b',
 	D_LOWER = 'd',
 	D_UPPER = 'D',
 	E_UPPER = 'E',

tools/ui/src/lib/hooks/use-keyboard-shortcuts.svelte.ts

@@ -9,6 +9,7 @@ interface KeyboardShortcutsCallbacks {
 	deleteActiveConversation?: () => void;
 	navigateToPrevConversation?: () => void;
 	navigateToNextConversation?: () => void;
+	toggleSidebar?: () => void;
 }
 
 export function useKeyboardShortcuts(callbacks: KeyboardShortcutsCallbacks) {
@@ -21,6 +22,11 @@ export function useKeyboardShortcuts(callbacks: KeyboardShortcutsCallbacks) {
 			callbacks.onSearchActivated?.();
 		}
 
+		if (isCmdOrCtrl && event.key === KeyboardKey.B_LOWER) {
+			event.preventDefault();
+			callbacks.toggleSidebar?.();
+		}
+
 		if (
 			isCmdOrCtrl &&
 			event.shiftKey &&

tools/ui/src/lib/services/mcp.service.ts

@@ -314,6 +314,30 @@ export class MCPService {
 					)
 				);
 
+				if (method === 'DELETE' && url.includes(CORS_PROXY_ENDPOINT)) {
+					const response = new Response(null, { status: 200, statusText: 'OK' });
+
+					logIfEnabled(
+						this.createLog(
+							MCPConnectionPhase.INITIALIZING,
+							`HTTP 200 ${method} ${url} (fake response)`,
+							MCPLogLevel.INFO,
+							{
+								response: {
+									url,
+									status: response.status,
+									statusText: response.statusText,
+									durationMs: 0,
+									isFake: true
+								}
+							}
+						)
+					);
+
+					// fake response, bypass real fetch()
+					return response;
+				}
+
 				try {
 					const response = await fetch(input, {
 						...baseInit,

tools/ui/tests/unit/mcp-service.test.ts

@@ -154,6 +154,32 @@ describe('MCPService', () => {
 		});
 	});
 
+	it('DELETE request with CORS proxy should return a fake 200 response', async () => {
+		const logs: MCPConnectionLog[] = [];
+		const fetchMock = vi.fn();
+
+		vi.stubGlobal('fetch', fetchMock);
+
+		const config: MCPServerConfig = {
+			url: 'https://example.com/mcp',
+			transport: MCPTransportType.STREAMABLE_HTTP,
+			useProxy: true
+		};
+
+		const controller = createDiagnosticFetch(config, (log) => logs.push(log), {}, true);
+
+		const response = await controller.fetch(
+			'http://localhost:8080/cors-proxy?url=https%3A%2F%2Fexample.com%2Fmcp',
+			{ method: 'DELETE' }
+		);
+
+		expect(fetchMock).not.toHaveBeenCalled();
+		expect(response.status).toBe(200);
+		expect(logs.at(-1)?.details).toMatchObject({
+			response: { status: 200, isFake: true }
+		});
+	});
+
 	it('partially redacts mcp-session-id in diagnostic request and response logs', async () => {
 		const logs: MCPConnectionLog[] = [];
 		const response = new Response('{}', {