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10 Commits

Author SHA1 Message Date
Anav Prasad 5b6913c47b cuda : remove legacy copy-op pointer indirection code (#16485)
* remove legacy copy-op pointer indirection code

* further removal of copy-op indirection code

* renamed check_node_graph_compatibility_and_refresh_copy_ops function
2025-10-14 11:53:49 +02:00
Georgi Gerganov bc07349a7f server : dynamic token limit for prompt cache (#16560)
* server : dynamic token limit for prompt cache

* cont : print estimated token limit
2025-10-14 08:48:50 +03:00
Georgi Gerganov e60f241eac metal : FA support F32 K and V and head size = 32 (#16531)
* metal : FA support F32 K and V and head size = 32

* graph : remove obsolete comment [no ci]
2025-10-13 23:07:57 +03:00
Georgi Gerganov e38b7c6e9e graph : support cacheless embeddings with FA and iSWA (#16528)
* graph : support cacheless embeddings with FA and iSWA

* cont : deduplicate mask creation

* cont : fix name
2025-10-13 22:42:37 +03:00
lhez 5016b72862 opencl: fix build targeting CL 2 (#16554) 2025-10-13 11:50:37 -07:00
Johannes Gäßler 7049736b2d CUDA: fix numerical issues in tile FA kernel (#16540) 2025-10-13 17:29:45 +03:00
Jie Fu (傅杰) 01d2bdc2bc ggml : fix build broken with -march=armv9-a on MacOS (#16520)
* ggml : fix build broken with -march=armv9-a on MacOS

Signed-off-by: Jie Fu <jiefu@tencent.com>

* Add #pragma message

Signed-off-by: Jie Fu <jiefu@tencent.com>

* Address review comment.

Signed-off-by: Jie Fu <jiefu@tencent.com>

* Update ggml/src/ggml-cpu/ggml-cpu.c

---------

Signed-off-by: Jie Fu <jiefu@tencent.com>
Co-authored-by: Diego Devesa <slarengh@gmail.com>
2025-10-13 15:48:47 +03:00
Chenguang Li 56fc38b965 CANN: fix CPU memory leak in CANN backend (#16549)
This commit fixes a CPU-side memory leak issue in the CANN backend,
which occurred when intermediate aclTensorList objects were not properly
released after operator execution. The leak happened during repeated
invocations of CANN ops (e.g., FlashAttention), leading to increasing
host memory usage over time.

Proper resource cleanup (aclDestroyTensorList and related release logic)
has been added to ensure that all temporary tensors are correctly freed.
2025-10-13 17:01:24 +08:00
Pascal 1fb9504eb7 fix: add remark plugin to render raw HTML as literal text (#16505)
* fix: add remark plugin to render raw HTML as literal text

Implemented a missing MDAST stage to neutralize raw HTML like major LLM WebUIs
do ensuring consistent and safe Markdown rendering

Introduced 'remarkLiteralHtml', a plugin that converts raw HTML nodes in the
Markdown AST into plain-text equivalents while preserving indentation and
line breaks. This ensures consistent rendering and prevents unintended HTML
execution, without altering valid Markdown structure

Kept 'remarkRehype' in the pipeline since it performs the required conversion
from MDAST to HAST for KaTeX, syntax highlighting, and HTML serialization

Refined the link-enhancement logic to skip unnecessary DOM rewrites,
fixing a subtle bug where extra paragraphs were injected after the first
line due to full innerHTML reconstruction, and ensuring links open in new
tabs only when required

Final pipeline: remarkGfm -> remarkMath -> remarkBreaks -> remarkLiteralHtml
-> remarkRehype -> rehypeKatex -> rehypeHighlight -> rehypeStringify

* fix: address review feedback from allozaur

* chore: update webui build output
2025-10-13 10:55:32 +02:00
Sam/Samuel 3f750f8d76 metal: add support for opt_step_sgd (#16539)
* metal: add support for opt_step_sgd

* add newline to pass EditorConfig check
2025-10-13 11:25:02 +03:00
28 changed files with 612 additions and 355 deletions
+6 -8
View File
@@ -146,9 +146,7 @@ void ggml_cann_op_unary_gated(
unary_op(ctx, acl_src0, acl_dst);
GGML_CANN_CALL_ACLNN_OP(ctx, InplaceMul, acl_dst, acl_src1);
ggml_cann_release_resources(ctx, acl_src0, acl_dst);
if(src1)
ggml_cann_release_resources(ctx, acl_src1);
ggml_cann_release_resources(ctx, acl_src0, acl_src1, acl_dst);
}
/**
@@ -1851,7 +1849,7 @@ void ggml_cann_get_rows(ggml_backend_cann_context& ctx, ggml_tensor* dst) {
dst->data, dst->ne, dst->nb,
src1, dst->type);
ggml_cann_release_resources(ctx, dequant_tensor);
ggml_cann_release_resources(ctx, acl_weight_tensor, acl_scale_tensor, dequant_tensor);
break;
}
default:
@@ -3290,8 +3288,8 @@ void ggml_cann_flash_attn_ext(ggml_backend_cann_context& ctx, ggml_tensor* dst){
aclTensor* acl_q_tensor = acl_src0_f16_tensor;
aclTensor* acl_k_tensors[] = {acl_src1_f16_tensor};
aclTensor* acl_v_tensors[] = {acl_src2_f16_tensor};
auto acl_k_tensor_list = aclCreateTensorList(acl_k_tensors, kvTensorNum);
auto acl_v_tensor_list = aclCreateTensorList(acl_v_tensors, kvTensorNum);
aclTensorList* acl_k_tensor_list = aclCreateTensorList(acl_k_tensors, kvTensorNum);
aclTensorList* acl_v_tensor_list = aclCreateTensorList(acl_v_tensors, kvTensorNum);
int64_t numHeads = src0->ne[2]; // N
int64_t numKeyValueHeads = src1->ne[2];
@@ -3362,8 +3360,8 @@ void ggml_cann_flash_attn_ext(ggml_backend_cann_context& ctx, ggml_tensor* dst){
}
ggml_cann_release_resources(ctx, acl_src0_f16_tensor,
acl_src1_f16_tensor,
acl_src2_f16_tensor,
acl_k_tensor_list,
acl_v_tensor_list,
fa_dst_tensor,
acl_dst_tensor,
bcast_pse_tensor);
+1 -1
View File
@@ -68,7 +68,7 @@ struct ggml_compute_params {
#endif // __VXE2__
#endif // __s390x__ && __VEC__
#if defined(__ARM_FEATURE_SVE)
#if defined(__ARM_FEATURE_SVE) && defined(__linux__)
#include <sys/prctl.h>
#endif
+6 -1
View File
@@ -689,8 +689,13 @@ bool ggml_is_numa(void) {
#endif
static void ggml_init_arm_arch_features(void) {
#if defined(__linux__) && defined(__aarch64__) && defined(__ARM_FEATURE_SVE)
#if defined(__aarch64__) && defined(__ARM_FEATURE_SVE)
#if defined(__linux__)
ggml_arm_arch_features.sve_cnt = PR_SVE_VL_LEN_MASK & prctl(PR_SVE_GET_VL);
#else
// TODO: add support of SVE for non-linux systems
#error "TODO: SVE is not supported on this platform. To use SVE, sve_cnt needs to be initialized here."
#endif
#endif
}
-7
View File
@@ -944,13 +944,6 @@ struct ggml_cuda_graph {
bool disable_due_to_failed_graph_capture = false;
int number_consecutive_updates = 0;
std::vector<ggml_graph_node_properties> ggml_graph_properties;
bool use_cpy_indirection = false;
std::vector<char *> cpy_dest_ptrs;
char ** dest_ptrs_d;
int dest_ptrs_size = 0;
// Index to allow each cpy kernel to be aware of it's position within the graph
// relative to other cpy nodes.
int graph_cpynode_index = -1;
#endif
};
+55 -163
View File
@@ -8,18 +8,16 @@
typedef void (*cpy_kernel_t)(const char * cx, char * cdst);
template <cpy_kernel_t cpy_1>
static __global__ void cpy_flt(const char * cx, char * cdst_direct, const int ne,
static __global__ void cpy_flt(const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11,
const int nb12, const int nb13, char ** cdst_indirect, int graph_cpynode_index) {
const int nb12, const int nb13) {
const int64_t i = blockDim.x*blockIdx.x + threadIdx.x;
if (i >= ne) {
return;
}
char * cdst = (cdst_indirect != nullptr) ? cdst_indirect[graph_cpynode_index]: cdst_direct;
// determine indices i03/i13, i02/i12, i01/i11, i00/i10 as a function of index i of flattened tensor
// then combine those indices with the corresponding byte offsets to get the total offsets
const int64_t i03 = i/(ne00 * ne01 * ne02);
@@ -63,18 +61,16 @@ static __device__ void cpy_blck_q_f32(const char * cxi, char * cdsti) {
}
template <cpy_kernel_t cpy_blck, int qk>
static __global__ void cpy_f32_q(const char * cx, char * cdst_direct, const int ne,
static __global__ void cpy_f32_q(const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11,
const int nb12, const int nb13, char ** cdst_indirect, int graph_cpynode_index) {
const int nb12, const int nb13) {
const int i = (blockDim.x*blockIdx.x + threadIdx.x)*qk;
if (i >= ne) {
return;
}
char * cdst = (cdst_indirect != nullptr) ? cdst_indirect[graph_cpynode_index]: cdst_direct;
const int i03 = i/(ne00 * ne01 * ne02);
const int i02 = (i - i03*ne00*ne01*ne02 )/ (ne00*ne01);
const int i01 = (i - i03*ne00*ne01*ne02 - i02*ne01*ne00) / ne00;
@@ -91,18 +87,16 @@ static __global__ void cpy_f32_q(const char * cx, char * cdst_direct, const int
}
template <cpy_kernel_t cpy_blck, int qk>
static __global__ void cpy_q_f32(const char * cx, char * cdst_direct, const int ne,
static __global__ void cpy_q_f32(const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11,
const int nb12, const int nb13, char ** cdst_indirect, int graph_cpynode_index) {
const int nb12, const int nb13) {
const int i = (blockDim.x*blockIdx.x + threadIdx.x)*qk;
if (i >= ne) {
return;
}
char * cdst = (cdst_indirect != nullptr) ? cdst_indirect[graph_cpynode_index]: cdst_direct;
const int i03 = i/(ne00 * ne01 * ne02);
const int i02 = (i - i03*ne00*ne01*ne02 )/ (ne00*ne01);
const int i01 = (i - i03*ne00*ne01*ne02 - i02*ne01*ne00) / ne00;
@@ -118,67 +112,47 @@ static __global__ void cpy_q_f32(const char * cx, char * cdst_direct, const int
cpy_blck(cx + x_offset, cdst + dst_offset);
}
// Copy destination pointers to GPU to be available when pointer indirection is in use
void ggml_cuda_cpy_dest_ptrs_copy(ggml_cuda_graph * cuda_graph, char ** host_dest_ptrs, const int host_dest_ptrs_size, cudaStream_t stream) {
#if defined(GGML_CUDA_USE_GRAPHS) || defined(GGML_HIP_GRAPHS) || defined(GGML_MUSA_GRAPHS)
if (cuda_graph->dest_ptrs_size < host_dest_ptrs_size) { // (re-)allocate GPU memory for destination pointers
CUDA_CHECK(cudaStreamSynchronize(stream));
if (cuda_graph->dest_ptrs_d != nullptr) {
CUDA_CHECK(cudaFree(cuda_graph->dest_ptrs_d));
}
CUDA_CHECK(cudaMalloc(&cuda_graph->dest_ptrs_d, host_dest_ptrs_size*sizeof(char *)));
cuda_graph->dest_ptrs_size = host_dest_ptrs_size;
}
// copy destination pointers to GPU
CUDA_CHECK(cudaMemcpyAsync(cuda_graph->dest_ptrs_d, host_dest_ptrs, host_dest_ptrs_size*sizeof(char *), cudaMemcpyHostToDevice, stream));
cuda_graph->graph_cpynode_index = 0; // reset index
#else
GGML_UNUSED_VARS(cuda_graph, host_dest_ptrs, host_dest_ptrs_size, stream);
#endif
}
template<typename src_t, typename dst_t>
static void ggml_cpy_flt_cuda(
const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {
const int num_blocks = (ne + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE;
cpy_flt<cpy_1_flt<src_t, dst_t>><<<num_blocks, CUDA_CPY_BLOCK_SIZE, 0, stream>>>
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_f32_q8_0_cuda(
const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {
GGML_ASSERT(ne % QK8_0 == 0);
const int num_blocks = ne / QK8_0;
cpy_f32_q<cpy_blck_f32_q8_0, QK8_0><<<num_blocks, 1, 0, stream>>>
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_q8_0_f32_cuda(
const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {
const int num_blocks = ne;
cpy_q_f32<cpy_blck_q8_0_f32, QK8_0><<<num_blocks, 1, 0, stream>>>
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_f32_q4_0_cuda(
const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {
GGML_ASSERT(ne % QK4_0 == 0);
const int num_blocks = ne / QK4_0;
cpy_f32_q<cpy_blck_f32_q4_0, QK4_0><<<num_blocks, 1, 0, stream>>>
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_q4_0_f32_cuda(
@@ -187,22 +161,22 @@ static void ggml_cpy_q4_0_f32_cuda(
const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12,
const int nb10, const int nb11, const int nb12, const int nb13,
cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
cudaStream_t stream) {
const int num_blocks = ne;
cpy_q_f32<cpy_blck_q_f32<dequantize_q4_0, QK4_0>, QK4_0><<<num_blocks, 1, 0, stream>>>(
cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03,
ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_f32_q4_1_cuda(
const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {
GGML_ASSERT(ne % QK4_1 == 0);
const int num_blocks = ne / QK4_1;
cpy_f32_q<cpy_blck_f32_q4_1, QK4_1><<<num_blocks, 1, 0, stream>>>
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_q4_1_f32_cuda(
@@ -211,22 +185,22 @@ static void ggml_cpy_q4_1_f32_cuda(
const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12,
const int nb10, const int nb11, const int nb12, const int nb13,
cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
cudaStream_t stream) {
const int num_blocks = ne;
cpy_q_f32<cpy_blck_q_f32<dequantize_q4_1, QK4_1>, QK4_1><<<num_blocks, 1, 0, stream>>>(
cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03,
ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_f32_q5_0_cuda(
const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {
GGML_ASSERT(ne % QK5_0 == 0);
const int num_blocks = ne / QK5_0;
cpy_f32_q<cpy_blck_f32_q5_0, QK5_0><<<num_blocks, 1, 0, stream>>>
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_q5_0_f32_cuda(
@@ -235,22 +209,22 @@ static void ggml_cpy_q5_0_f32_cuda(
const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12,
const int nb10, const int nb11, const int nb12, const int nb13,
cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
cudaStream_t stream) {
const int num_blocks = ne;
cpy_q_f32<cpy_blck_q_f32<dequantize_q5_0, QK5_0>, QK5_0><<<num_blocks, 1, 0, stream>>>(
cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03,
ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_f32_q5_1_cuda(
const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {
GGML_ASSERT(ne % QK5_1 == 0);
const int num_blocks = ne / QK5_1;
cpy_f32_q<cpy_blck_f32_q5_1, QK5_1><<<num_blocks, 1, 0, stream>>>
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_q5_1_f32_cuda(
@@ -259,25 +233,25 @@ static void ggml_cpy_q5_1_f32_cuda(
const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12,
const int nb10, const int nb11, const int nb12, const int nb13,
cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
cudaStream_t stream) {
const int num_blocks = ne;
cpy_q_f32<cpy_blck_q_f32<dequantize_q5_1, QK5_1>, QK5_1><<<num_blocks, 1, 0, stream>>>(
cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03,
ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
static void ggml_cpy_f32_iq4_nl_cuda(
const char * cx, char * cdst, const int ne,
const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream, char ** cdst_indirect, int & graph_cpynode_index) {
const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {
GGML_ASSERT(ne % QK4_NL == 0);
const int num_blocks = ne / QK4_NL;
cpy_f32_q<cpy_blck_f32_iq4_nl, QK4_NL><<<num_blocks, 1, 0, stream>>>
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, cdst_indirect, graph_cpynode_index++);
(cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}
void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, ggml_tensor * src1, bool disable_indirection_for_this_node) {
void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, ggml_tensor * src1) {
const int64_t ne = ggml_nelements(src0);
GGML_ASSERT(ne == ggml_nelements(src1));
@@ -311,16 +285,6 @@ void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, gg
char * src0_ddc = (char *) src0->data;
char * src1_ddc = (char *) src1->data;
char ** dest_ptrs_d = nullptr;
int graph_cpynode_index = -1;
#if defined(GGML_CUDA_USE_GRAPHS) || defined(GGML_HIP_GRAPHS) || defined(GGML_MUSA_GRAPHS)
if(ctx.cuda_graph->use_cpy_indirection && !disable_indirection_for_this_node) {
dest_ptrs_d = ctx.cuda_graph->dest_ptrs_d;
graph_cpynode_index = ctx.cuda_graph->graph_cpynode_index;
}
#else
GGML_UNUSED(disable_indirection_for_this_node);
#endif
if (src0->type == src1->type && ggml_is_contiguous(src0) && ggml_is_contiguous(src1)) {
GGML_ASSERT(ggml_nbytes(src0) == ggml_nbytes(src1));
#if defined(GGML_USE_MUSA) && defined(GGML_MUSA_MUDNN_COPY)
@@ -329,134 +293,62 @@ void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, gg
} else
#endif // GGML_USE_MUSA && GGML_MUSA_MUDNN_COPY
{
if (src0->type == GGML_TYPE_F32) {
ggml_cpy_flt_cuda<float, float> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
} else {
CUDA_CHECK(cudaMemcpyAsync(src1_ddc, src0_ddc, ggml_nbytes(src0), cudaMemcpyDeviceToDevice, main_stream));
}
CUDA_CHECK(cudaMemcpyAsync(src1_ddc, src0_ddc, ggml_nbytes(src0), cudaMemcpyDeviceToDevice, main_stream));
}
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32) {
ggml_cpy_flt_cuda<float, float> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<float, float> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_BF16) {
ggml_cpy_flt_cuda<float, nv_bfloat16> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<float, nv_bfloat16> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16) {
ggml_cpy_flt_cuda<float, half> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<float, half> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q8_0) {
ggml_cpy_f32_q8_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_f32_q8_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_Q8_0 && src1->type == GGML_TYPE_F32) {
ggml_cpy_q8_0_f32_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_q8_0_f32_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_0) {
ggml_cpy_f32_q4_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_f32_q4_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_Q4_0 && src1->type == GGML_TYPE_F32) {
ggml_cpy_q4_0_f32_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02,
nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_1) {
ggml_cpy_f32_q4_1_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_f32_q4_1_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_Q4_1 && src1->type == GGML_TYPE_F32) {
ggml_cpy_q4_1_f32_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02,
nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_0) {
ggml_cpy_f32_q5_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_f32_q5_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_Q5_0 && src1->type == GGML_TYPE_F32) {
ggml_cpy_q5_0_f32_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02,
nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_IQ4_NL) {
ggml_cpy_f32_iq4_nl_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_f32_iq4_nl_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_1) {
ggml_cpy_f32_q5_1_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_f32_q5_1_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_Q5_1 && src1->type == GGML_TYPE_F32) {
ggml_cpy_q5_1_f32_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_q5_1_f32_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F16) {
ggml_cpy_flt_cuda<half, half> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<half, half> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_BF16) {
ggml_cpy_flt_cuda<half, nv_bfloat16> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<half, nv_bfloat16> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F32) {
ggml_cpy_flt_cuda<half, float> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<half, float> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_BF16) {
ggml_cpy_flt_cuda<nv_bfloat16, nv_bfloat16> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<nv_bfloat16, nv_bfloat16> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_F16) {
ggml_cpy_flt_cuda<nv_bfloat16, half> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<nv_bfloat16, half> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_F32) {
ggml_cpy_flt_cuda<nv_bfloat16, float> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<nv_bfloat16, float> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_I32) {
ggml_cpy_flt_cuda<float, int32_t> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<float, int32_t> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else if (src0->type == GGML_TYPE_I32 && src1->type == GGML_TYPE_F32) {
ggml_cpy_flt_cuda<int32_t, float> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream, dest_ptrs_d, graph_cpynode_index);
ggml_cpy_flt_cuda<int32_t, float> (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else {
GGML_ABORT("%s: unsupported type combination (%s to %s)\n", __func__,
ggml_type_name(src0->type), ggml_type_name(src1->type));
}
#if defined(GGML_CUDA_USE_GRAPHS) || defined(GGML_HIP_GRAPHS) || defined(GGML_MUSA_GRAPHS)
if(ctx.cuda_graph->use_cpy_indirection && !disable_indirection_for_this_node) {
ctx.cuda_graph->graph_cpynode_index = graph_cpynode_index;
}
#else
GGML_UNUSED(disable_indirection_for_this_node);
#endif
}
void ggml_cuda_dup(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
const ggml_tensor * src0 = dst->src[0];
bool disable_indirection = true;
ggml_cuda_cpy(ctx, src0, dst, disable_indirection);
}
void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1) {
if (src0->type == src1->type && ggml_is_contiguous(src0) && ggml_is_contiguous(src1)) {
// Prioritize CUDA graph compatibility over direct memory copy optimization.
// Using copy kernels here maintains graph indirection support, preventing performance regression from disabled CUDA graphs.
if (src0->type == GGML_TYPE_F32) {
return (void*) cpy_flt<cpy_1_flt<float, float>>;
} else {
return nullptr;
}
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32) {
return (void*) cpy_flt<cpy_1_flt<float, float>>;
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_BF16) {
return (void*) cpy_flt<cpy_1_flt<float, nv_bfloat16>>;
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16) {
return (void*) cpy_flt<cpy_1_flt<float, half>>;
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q8_0) {
return (void*) cpy_f32_q<cpy_blck_f32_q8_0, QK8_0>;
} else if (src0->type == GGML_TYPE_Q8_0 && src1->type == GGML_TYPE_F32) {
return (void*) cpy_q_f32<cpy_blck_q8_0_f32, QK8_0>;
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_0) {
return (void*) cpy_f32_q<cpy_blck_f32_q4_0, QK4_0>;
} else if (src0->type == GGML_TYPE_Q4_0 && src1->type == GGML_TYPE_F32) {
return (void*) cpy_q_f32<cpy_blck_q_f32<dequantize_q4_0, QK4_0>, QK4_0>;
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_1) {
return (void*) cpy_f32_q<cpy_blck_f32_q4_1, QK4_1>;
} else if (src0->type == GGML_TYPE_Q4_1 && src1->type == GGML_TYPE_F32) {
return (void*) cpy_q_f32<cpy_blck_q_f32<dequantize_q4_1, QK4_1>, QK4_1>;
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_0) {
return (void*) cpy_f32_q<cpy_blck_f32_q5_0, QK5_0>;
} else if (src0->type == GGML_TYPE_Q5_0 && src1->type == GGML_TYPE_F32) {
return (void*) cpy_q_f32<cpy_blck_q_f32<dequantize_q5_0, QK5_0>, QK5_0>;
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_IQ4_NL) {
return (void*) cpy_f32_q<cpy_blck_f32_iq4_nl, QK4_NL>;
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_1) {
return (void*) cpy_f32_q<cpy_blck_f32_q5_1, QK5_1>;
} else if (src0->type == GGML_TYPE_Q5_1 && src1->type == GGML_TYPE_F32) {
return (void*) cpy_q_f32<cpy_blck_q_f32<dequantize_q5_1, QK5_1>, QK5_1>;
} else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F16) {
return (void*) cpy_flt<cpy_1_flt<half, half>>;
} else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_BF16) {
return (void*) cpy_flt<cpy_1_flt<half, nv_bfloat16>>;
} else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F32) {
return (void*) cpy_flt<cpy_1_flt<half, float>>;
} else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_F16) {
return (void*) cpy_flt<cpy_1_flt<nv_bfloat16, half>>;
} else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_BF16) {
return (void*) cpy_flt<cpy_1_flt<nv_bfloat16, nv_bfloat16>>;
} else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_F32) {
return (void*) cpy_flt<cpy_1_flt<nv_bfloat16, float>>;
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_I32) {
return (void*) cpy_flt<cpy_1_flt<float, int32_t>>;
} else if (src0->type == GGML_TYPE_I32 && src1->type == GGML_TYPE_F32) {
return (void*) cpy_flt<cpy_1_flt<int32_t, float>>;
} else {
GGML_ABORT("%s: unsupported type combination (%s to %s)\n", __func__,
ggml_type_name(src0->type), ggml_type_name(src1->type));
}
ggml_cuda_cpy(ctx, src0, dst);
}
+1 -5
View File
@@ -2,10 +2,6 @@
#define CUDA_CPY_BLOCK_SIZE 64
void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, ggml_tensor * src1, bool disable_indirection = false);
void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, ggml_tensor * src1);
void ggml_cuda_dup(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1);
void ggml_cuda_cpy_dest_ptrs_copy(ggml_cuda_graph * cuda_graph, char ** host_dest_ptrs, const int host_dest_ptrs_size, cudaStream_t stream);
+17 -27
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@@ -540,10 +540,12 @@ static __device__ __forceinline__ void flash_attn_tile_iter(
KQ_acc[(i_KQ_0/(np*warp_size))*cpw + jc0] = logit_softcap * tanhf(KQ_acc[(i_KQ_0/(np*warp_size))*cpw + jc0]);
}
KQ_acc[(i_KQ_0/(np*warp_size))*cpw + jc0] += (ncols2 > 1 || mask) && (!oob_check || i_KQ < k_VKQ_sup) ?
slope*__half2float(mask[j*stride_mask + k_VKQ_0 + i_KQ]) : 0.0f;
if (!oob_check || i_KQ < k_VKQ_sup) {
KQ_acc[(i_KQ_0/(np*warp_size))*cpw + jc0] += (ncols2 > 1 || mask) ?
slope*__half2float(mask[j*stride_mask + k_VKQ_0 + i_KQ]) : 0.0f;
KQ_max_new[jc0] = fmaxf(KQ_max_new[jc0], KQ_acc[(i_KQ_0/(np*warp_size))*cpw + jc0]);
KQ_max_new[jc0] = fmaxf(KQ_max_new[jc0], KQ_acc[(i_KQ_0/(np*warp_size))*cpw + jc0]);
}
}
KQ_max_new[jc0] = warp_reduce_max<warp_size>(KQ_max_new[jc0]);
@@ -581,10 +583,9 @@ static __device__ __forceinline__ void flash_attn_tile_iter(
float KQ_sum_add = 0.0f;
#pragma unroll
for (int i0 = 0; i0 < nbatch_fa; i0 += np*warp_size) {
const float val = expf(KQ_acc[(i0/(np*warp_size))*cpw + jc] - KQ_max[jc]);
if (!oob_check || i0 + (threadIdx.y % np)*warp_size + threadIdx.x < k_VKQ_sup) {
KQ_sum_add += val;
}
const float val = !oob_check || i0 + (threadIdx.y % np)*warp_size + threadIdx.x < k_VKQ_sup ?
expf(KQ_acc[(i0/(np*warp_size))*cpw + jc] - KQ_max[jc]) : 0.0f;
KQ_sum_add += val;
tmp[i0/(np*warp_size)][jc1] = val;
}
KQ_sum[jc] = KQ_sum[jc]*KQ_max_scale + KQ_sum_add;
@@ -975,26 +976,6 @@ static __global__ void flash_attn_tile(
}
}
if (gridDim.y == 1) {
#pragma unroll
for (int jc0 = 0; jc0 < cpw; ++jc0) {
#ifdef FAST_FP16_AVAILABLE
const half2 KQ_sum_jc_inv = make_half2(1.0f/KQ_sum[jc0], 1.0f/KQ_sum[jc0]);
#pragma unroll
for (int i = 0; i < (DVp/2)/warp_size; ++i) {
VKQ[jc0*((DVp/2)/warp_size) + i] *= KQ_sum_jc_inv;
}
#else
const float KQ_sum_jc_inv = 1.0f/KQ_sum[jc0];
#pragma unroll
for (int i = 0; i < (DVp/2)/warp_size; ++i) {
VKQ[jc0*((DVp/2)/warp_size) + i].x *= KQ_sum_jc_inv;
VKQ[jc0*((DVp/2)/warp_size) + i].y *= KQ_sum_jc_inv;
}
#endif // FAST_FP16_AVAILABLE
}
}
// Write back results:
#pragma unroll
for (int jc0 = 0; jc0 < cpw; ++jc0) {
@@ -1007,6 +988,8 @@ static __global__ void flash_attn_tile(
return;
}
const float scale = gridDim.y == 1 ? 1.0f/KQ_sum[jc0] : 1.0f;
const int j_dst_unrolled = ((sequence*ne01 + col_Q_0 + j)*ne02 + head0 + c)*gridDim.y + blockIdx.y;
#ifdef FAST_FP16_AVAILABLE
@@ -1017,6 +1000,8 @@ static __global__ void flash_attn_tile(
#pragma unroll
for (int i1 = 0; i1 < cpy_ne_D; ++i1) {
tmp[i1] = __half22float2(VKQ[jc0*((DVp/2)/warp_size) + i0/warp_size + i1]);
tmp[i1].x *= scale;
tmp[i1].y *= scale;
}
if (i0 + warp_size*cpy_ne_D <= DV/2 || i0 + threadIdx.x*cpy_ne_D < DV/2) {
ggml_cuda_memcpy_1<sizeof(tmp)>(&dst[j_dst_unrolled*DV + 2*i0 + threadIdx.x*(2*cpy_ne_D)], tmp);
@@ -1027,6 +1012,11 @@ static __global__ void flash_attn_tile(
#pragma unroll
for (int i0 = 0; i0 < DVp; i0 += warp_size*cpy_ne_D) {
if (i0 + warp_size*cpy_ne_D <= DV || i0 + threadIdx.x*cpy_ne_D < DV) {
#pragma unroll
for (int i1 = 0; i1 < cpy_ne_D/2; ++i1) {
VKQ[jc0*((DVp/2)/warp_size) + i0/(2*warp_size) + i1].x *= scale;
VKQ[jc0*((DVp/2)/warp_size) + i0/(2*warp_size) + i1].y *= scale;
}
ggml_cuda_memcpy_1<cpy_ne_D*4>(
&dst[j_dst_unrolled*DV + i0 + threadIdx.x*cpy_ne_D],
&VKQ[jc0*((DVp/2)/warp_size) + i0/(2*warp_size)]);
+2 -31
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@@ -2633,11 +2633,10 @@ static void ggml_backend_cuda_synchronize(ggml_backend_t backend) {
}
#ifdef USE_CUDA_GRAPH
static bool check_node_graph_compatibility_and_refresh_copy_ops(ggml_backend_cuda_context * cuda_ctx, ggml_cgraph * cgraph,
static bool check_node_graph_compatibility(ggml_cgraph * cgraph,
bool use_cuda_graph) {
// Loop over nodes in GGML graph to obtain info needed for CUDA graph
cuda_ctx->cuda_graph->cpy_dest_ptrs.clear();
const std::string gemma3n_per_layer_proj_src0_name = "inp_per_layer_selected";
const std::string gemma3n_per_layer_proj_src1_name = "per_layer_proj";
@@ -2688,33 +2687,11 @@ static bool check_node_graph_compatibility_and_refresh_copy_ops(ggml_backend_cud
#endif
}
if (node->op == GGML_OP_CPY) {
// Store the pointers which are updated for each token, such that these can be sent
// to the device and accessed using indirection from CUDA graph
cuda_ctx->cuda_graph->cpy_dest_ptrs.push_back((char *) node->src[1]->data);
// store a pointer to each copy op CUDA kernel to identify it later
void * ptr = ggml_cuda_cpy_fn(node->src[0], node->src[1]);
if (!ptr) {
use_cuda_graph = false;
#ifndef NDEBUG
GGML_LOG_DEBUG("%s: disabling CUDA graphs due to unsupported copy op\n", __func__);
#endif
}
}
if (!use_cuda_graph) {
break;
}
}
if (use_cuda_graph) {
cuda_ctx->cuda_graph->use_cpy_indirection = true;
// copy pointers to GPU so they can be accessed via indirection within CUDA graph
ggml_cuda_cpy_dest_ptrs_copy(cuda_ctx->cuda_graph.get(), cuda_ctx->cuda_graph->cpy_dest_ptrs.data(), cuda_ctx->cuda_graph->cpy_dest_ptrs.size(), cuda_ctx->stream());
}
return use_cuda_graph;
}
@@ -2733,7 +2710,6 @@ static void set_ggml_graph_node_properties(ggml_tensor * node, ggml_graph_node_p
static bool ggml_graph_node_has_matching_properties(ggml_tensor * node, ggml_graph_node_properties * graph_node_properties) {
if (node->data != graph_node_properties->node_address &&
node->op != GGML_OP_CPY &&
node->op != GGML_OP_VIEW) {
return false;
}
@@ -2754,7 +2730,6 @@ static bool ggml_graph_node_has_matching_properties(ggml_tensor * node, ggml_gra
for (int i = 0; i < GGML_MAX_SRC; i++) {
if (node->src[i] &&
node->src[i]->data != graph_node_properties->src_address[i] &&
node->op != GGML_OP_CPY &&
node->op != GGML_OP_VIEW
) {
return false;
@@ -3120,7 +3095,7 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend,
if (use_cuda_graph) {
cuda_graph_update_required = is_cuda_graph_update_required(cuda_ctx, cgraph);
use_cuda_graph = check_node_graph_compatibility_and_refresh_copy_ops(cuda_ctx, cgraph, use_cuda_graph);
use_cuda_graph = check_node_graph_compatibility(cgraph, use_cuda_graph);
// Disable CUDA graphs (from the next token) if the use-case is demanding too many consecutive graph updates.
if (use_cuda_graph && cuda_graph_update_required) {
@@ -3147,10 +3122,6 @@ static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend,
CUDA_CHECK(cudaStreamBeginCapture(cuda_ctx->stream(), cudaStreamCaptureModeRelaxed));
}
if (!use_cuda_graph) {
cuda_ctx->cuda_graph->use_cpy_indirection = false;
}
#else
bool use_cuda_graph = false;
bool cuda_graph_update_required = false;
+19
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@@ -1519,3 +1519,22 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_adamw(ggml_metal_
return res;
}
ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_sgd(ggml_metal_library_t lib, const ggml_tensor * op) {
assert(op->op == GGML_OP_OPT_STEP_SGD);
char base[256];
char name[256];
snprintf(base, 256, "kernel_opt_step_sgd_%s", ggml_type_name(op->src[0]->type));
snprintf(name, 256, "%s", base);
ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name);
if (res) {
return res;
}
res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr);
return res;
}
+1
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@@ -136,6 +136,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_pad_reflect_1d (ggml_me
ggml_metal_pipeline_t ggml_metal_library_get_pipeline_arange (ggml_metal_library_t lib, const struct ggml_tensor * op);
ggml_metal_pipeline_t ggml_metal_library_get_pipeline_timestep_embedding(ggml_metal_library_t lib, const struct ggml_tensor * op);
ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_adamw (ggml_metal_library_t lib, const struct ggml_tensor * op);
ggml_metal_pipeline_t ggml_metal_library_get_pipeline_opt_step_sgd (ggml_metal_library_t lib, const struct ggml_tensor * op);
ggml_metal_pipeline_t ggml_metal_library_get_pipeline_flash_attn_ext_pad(
ggml_metal_library_t lib,
+3 -1
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@@ -693,7 +693,8 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te
return true;
case GGML_OP_FLASH_ATTN_EXT:
// for new head sizes, add checks here
if (op->src[0]->ne[0] != 40 &&
if (op->src[0]->ne[0] != 32 &&
op->src[0]->ne[0] != 40 &&
op->src[0]->ne[0] != 64 &&
op->src[0]->ne[0] != 80 &&
op->src[0]->ne[0] != 96 &&
@@ -800,6 +801,7 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te
};
}
case GGML_OP_OPT_STEP_ADAMW:
case GGML_OP_OPT_STEP_SGD:
return has_simdgroup_reduction;
default:
return false;
+4
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@@ -781,4 +781,8 @@ typedef struct {
int64_t np;
} ggml_metal_kargs_opt_step_adamw;
typedef struct {
int64_t np;
} ggml_metal_kargs_opt_step_sgd;
#endif // GGML_METAL_IMPL
+38
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@@ -418,6 +418,10 @@ static int ggml_metal_op_encode_impl(ggml_metal_op_t ctx, int idx) {
{
n_fuse = ggml_metal_op_opt_step_adamw(ctx, idx);
} break;
case GGML_OP_OPT_STEP_SGD:
{
n_fuse = ggml_metal_op_opt_step_sgd(ctx, idx);
} break;
default:
{
GGML_LOG_ERROR("%s: error: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(node->op));
@@ -3469,3 +3473,37 @@ int ggml_metal_op_opt_step_adamw(ggml_metal_op_t ctx, int idx) {
return 1;
}
int ggml_metal_op_opt_step_sgd(ggml_metal_op_t ctx, int idx) {
ggml_tensor * op = ctx->node(idx);
ggml_metal_library_t lib = ctx->lib;
ggml_metal_encoder_t enc = ctx->enc;
GGML_TENSOR_LOCALS( int32_t, ne0, op->src[0], ne);
GGML_TENSOR_LOCALS(uint64_t, nb0, op->src[0], nb);
GGML_TENSOR_LOCALS( int32_t, ne, op, ne);
GGML_TENSOR_LOCALS(uint32_t, nb, op, nb);
ggml_metal_pipeline_t pipeline = ggml_metal_library_get_pipeline_opt_step_sgd(lib, op);
const int64_t np = ggml_nelements(op->src[0]);
ggml_metal_kargs_opt_step_sgd args = {
/*.np =*/ np,
};
int ida = 0;
ggml_metal_encoder_set_pipeline(enc, pipeline);
ggml_metal_encoder_set_bytes (enc, &args, sizeof(args), ida++);
ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[0]), ida++);
ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[1]), ida++);
ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[2]), ida++);
const int nth = std::min(ggml_metal_pipeline_max_theads_per_threadgroup(pipeline), ne0);
const int64_t n = (np + nth - 1) / nth;
ggml_metal_encoder_dispatch_threadgroups(enc, n, 1, 1, nth, 1, 1);
return 1;
}
+1
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@@ -80,6 +80,7 @@ int ggml_metal_op_argmax (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_argsort (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_leaky_relu (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_opt_step_adamw (ggml_metal_op_t ctx, int idx);
int ggml_metal_op_opt_step_sgd (ggml_metal_op_t ctx, int idx);
#ifdef __cplusplus
}
+117 -49
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@@ -5213,8 +5213,30 @@ kernel void kernel_flash_attn_ext(
half, half4, simdgroup_half8x8
//float, float4, simdgroup_float8x8
#define FA_TYPES_F32 \
half, half4, simdgroup_half8x8, \
float, float4x4, simdgroup_float8x8, \
float, float4x4, simdgroup_float8x8, \
float, simdgroup_float8x8, \
float, float2, simdgroup_float8x8, \
float, float4, simdgroup_float8x8
//half, half4, simdgroup_half8x8
typedef decltype(kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 64, 64>) flash_attn_ext_t;
template [[host_name("kernel_flash_attn_ext_f32_dk32_dv32" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 32, 32>;
template [[host_name("kernel_flash_attn_ext_f32_dk40_dv40" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 40, 40>;
template [[host_name("kernel_flash_attn_ext_f32_dk64_dv64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 64, 64>;
template [[host_name("kernel_flash_attn_ext_f32_dk80_dv80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 80, 80>;
template [[host_name("kernel_flash_attn_ext_f32_dk96_dv96" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 96, 96>;
template [[host_name("kernel_flash_attn_ext_f32_dk112_dv112")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 112, 112>;
template [[host_name("kernel_flash_attn_ext_f32_dk128_dv128")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 128, 128>;
template [[host_name("kernel_flash_attn_ext_f32_dk192_dv192")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 192, 192>;
template [[host_name("kernel_flash_attn_ext_f32_dk192_dv128")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 192, 128>;
template [[host_name("kernel_flash_attn_ext_f32_dk256_dv256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 256, 256>;
template [[host_name("kernel_flash_attn_ext_f32_dk576_dv512")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_F32, float4x4, 1, dequantize_f32, float4x4, 1, dequantize_f32, 576, 512>;
template [[host_name("kernel_flash_attn_ext_f16_dk32_dv32" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 32, 32>;
template [[host_name("kernel_flash_attn_ext_f16_dk40_dv40" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 40, 40>;
template [[host_name("kernel_flash_attn_ext_f16_dk64_dv64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 64, 64>;
template [[host_name("kernel_flash_attn_ext_f16_dk80_dv80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 80, 80>;
@@ -5227,6 +5249,7 @@ template [[host_name("kernel_flash_attn_ext_f16_dk256_dv256")]] kernel flash_at
template [[host_name("kernel_flash_attn_ext_f16_dk576_dv512")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 576, 512>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_flash_attn_ext_bf16_dk32_dv32" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_BF, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 32, 32>;
template [[host_name("kernel_flash_attn_ext_bf16_dk40_dv40" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_BF, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 40, 40>;
template [[host_name("kernel_flash_attn_ext_bf16_dk64_dv64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_BF, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 64, 64>;
template [[host_name("kernel_flash_attn_ext_bf16_dk80_dv80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_BF, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 80, 80>;
@@ -5239,6 +5262,7 @@ template [[host_name("kernel_flash_attn_ext_bf16_dk256_dv256")]] kernel flash_at
template [[host_name("kernel_flash_attn_ext_bf16_dk576_dv512")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES_BF, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 576, 512>;
#endif
template [[host_name("kernel_flash_attn_ext_q4_0_dk32_dv32" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 32, 32>;
template [[host_name("kernel_flash_attn_ext_q4_0_dk40_dv40" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 40, 40>;
template [[host_name("kernel_flash_attn_ext_q4_0_dk64_dv64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 64, 64>;
template [[host_name("kernel_flash_attn_ext_q4_0_dk80_dv80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 80, 80>;
@@ -5250,6 +5274,7 @@ template [[host_name("kernel_flash_attn_ext_q4_0_dk192_dv128")]] kernel flash_at
template [[host_name("kernel_flash_attn_ext_q4_0_dk256_dv256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 256, 256>;
template [[host_name("kernel_flash_attn_ext_q4_0_dk576_dv512")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 576, 512>;
template [[host_name("kernel_flash_attn_ext_q4_1_dk32_dv32" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 32, 32>;
template [[host_name("kernel_flash_attn_ext_q4_1_dk40_dv40" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 40, 40>;
template [[host_name("kernel_flash_attn_ext_q4_1_dk64_dv64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 64, 64>;
template [[host_name("kernel_flash_attn_ext_q4_1_dk80_dv80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 80, 80>;
@@ -5261,6 +5286,7 @@ template [[host_name("kernel_flash_attn_ext_q4_1_dk192_dv128")]] kernel flash_at
template [[host_name("kernel_flash_attn_ext_q4_1_dk256_dv256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 256, 256>;
template [[host_name("kernel_flash_attn_ext_q4_1_dk576_dv512")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 576, 512>;
template [[host_name("kernel_flash_attn_ext_q5_0_dk32_dv32" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 32, 32>;
template [[host_name("kernel_flash_attn_ext_q5_0_dk40_dv40" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 40, 40>;
template [[host_name("kernel_flash_attn_ext_q5_0_dk64_dv64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 64, 64>;
template [[host_name("kernel_flash_attn_ext_q5_0_dk80_dv80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 80, 80>;
@@ -5272,6 +5298,7 @@ template [[host_name("kernel_flash_attn_ext_q5_0_dk192_dv128")]] kernel flash_at
template [[host_name("kernel_flash_attn_ext_q5_0_dk256_dv256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 256, 256>;
template [[host_name("kernel_flash_attn_ext_q5_0_dk576_dv512")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 576, 512>;
template [[host_name("kernel_flash_attn_ext_q5_1_dk32_dv32" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 32, 32>;
template [[host_name("kernel_flash_attn_ext_q5_1_dk40_dv40" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 40, 40>;
template [[host_name("kernel_flash_attn_ext_q5_1_dk64_dv64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 64, 64>;
template [[host_name("kernel_flash_attn_ext_q5_1_dk80_dv80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 80, 80>;
@@ -5283,6 +5310,7 @@ template [[host_name("kernel_flash_attn_ext_q5_1_dk192_dv128")]] kernel flash_at
template [[host_name("kernel_flash_attn_ext_q5_1_dk256_dv256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 256, 256>;
template [[host_name("kernel_flash_attn_ext_q5_1_dk576_dv512")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 576, 512>;
template [[host_name("kernel_flash_attn_ext_q8_0_dk32_dv32" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 32, 32>;
template [[host_name("kernel_flash_attn_ext_q8_0_dk40_dv40" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 40, 40>;
template [[host_name("kernel_flash_attn_ext_q8_0_dk64_dv64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 64, 64>;
template [[host_name("kernel_flash_attn_ext_q8_0_dk80_dv80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 80, 80>;
@@ -5818,77 +5846,103 @@ kernel void kernel_flash_attn_ext_vec(
float, float4, \
float4
#define FA_TYPES_F32 \
half4, \
float4, \
float4, \
float, \
float, float4, \
float4
typedef decltype(kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 128, 128, 4>) flash_attn_ext_vec_t;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f32_dk32_dv32")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES_F32, float4, 1, dequantize_f32_t4, float4, 1, dequantize_f32_t4, 32, 32, 4>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk32_dv32")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 32, 32, 4>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk32_dv32")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 32, 32, 4>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk32_dv32")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 32, 32, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk32_dv32")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 32, 32, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk32_dv32")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 32, 32, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk32_dv32")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 32, 32, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk32_dv32")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 32, 32, 4>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_f32_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES_F32, float4, 1, dequantize_f32_t4, float4, 1, dequantize_f32_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 64, 64, 2>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 64, 64, 2>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk64_dv64")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 64, 64, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_f32_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES_F32, float4, 1, dequantize_f32_t4, float4, 1, dequantize_f32_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 96, 96, 4>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 96, 96, 4>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk96_dv96")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 96, 96, 4>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f32_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES_F32, float4, 1, dequantize_f32_t4, float4, 1, dequantize_f32_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 128, 128, 1>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 128, 128, 1>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk128_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 128, 128, 1>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f32_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES_F32, float4, 1, dequantize_f32_t4, float4, 1, dequantize_f32_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 192, 192, 2>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 192, 192, 2>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk192_dv192")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 192, 192, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_f32_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES_F32, float4, 1, dequantize_f32_t4, float4, 1, dequantize_f32_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 192, 128, 2>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 192, 128, 2>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk192_dv128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 192, 128, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f32_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES_F32, float4, 1, dequantize_f32_t4, float4, 1, dequantize_f32_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 256, 256, 1>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 256, 256, 1>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk256_dv256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 256, 256, 1>;
template [[host_name("kernel_flash_attn_ext_vec_f32_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES_F32, float4, 1, dequantize_f32_t4, float4, 1, dequantize_f32_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_f16_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4, 1, dequantize_f16_t4, half4, 1, dequantize_f16_t4, 576, 512, 2>;
#if defined(GGML_METAL_HAS_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4, 1, dequantize_bf16_t4, bfloat4, 1, dequantize_bf16_t4, 576, 512, 2>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 8, dequantize_q4_0_t4, block_q4_0, 8, dequantize_q4_0_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 8, dequantize_q4_1_t4, block_q4_1, 8, dequantize_q4_1_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 8, dequantize_q5_0_t4, block_q5_0, 8, dequantize_q5_0_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 8, dequantize_q5_1_t4, block_q5_1, 8, dequantize_q5_1_t4, 576, 512, 2>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_dk576_dv512")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 8, dequantize_q8_0_t4, block_q8_0, 8, dequantize_q8_0_t4, 576, 512, 2>;
#undef FA_TYPES
@@ -8806,3 +8860,17 @@ kernel void kernel_opt_step_adamw_f32(
x[gid] = x[gid] * (1.0f - alpha * wd) - alpha * mh / vh;
}
kernel void kernel_opt_step_sgd_f32(
constant ggml_metal_kargs_opt_step_sgd & args,
device float * x,
device const float * g,
device const float * pars,
uint gid[[thread_position_in_grid]]) {
if (gid >= args.np) {
return;
}
x[gid] = x[gid] * (1.0f - pars[0] * pars[1]) - pars[0] * g[gid];
}
+5
View File
@@ -2348,8 +2348,13 @@ static ggml_backend_opencl_context * ggml_cl2_init(ggml_backend_dev_t dev) {
svm_caps & CL_DEVICE_SVM_ATOMICS ? "true" : "false");
if (opencl_c_version.major >= 3) {
// Assume it is not available for 3.0, since it is optional in 3.0.
// If compiling against 3.0, then we can query.
backend_ctx->non_uniform_workgroups = false;
#if CL_TARGET_OPENCL_VERSION >= 300
CL_CHECK(clGetDeviceInfo(device, CL_DEVICE_NON_UNIFORM_WORK_GROUP_SUPPORT, sizeof(cl_bool),
&backend_ctx->non_uniform_workgroups, 0));
#endif
} else {
GGML_ASSERT(opencl_c_version.major == 2);
// Non-uniform workgroup sizes is mandatory feature in v2.x.
+74 -43
View File
@@ -261,12 +261,17 @@ void llm_graph_input_cross_embd::set_input(const llama_ubatch * ubatch) {
}
}
static void print_mask(float * data, int64_t n_tokens, int64_t n_kv, int64_t n_swa, llama_swa_type swa_type) {
static void print_mask(const float * data, int64_t n_tokens, int64_t n_kv, int64_t n_swa, llama_swa_type swa_type) {
LLAMA_LOG_DEBUG("%s: === Attention mask ===\n", __func__);
const char * swa_type_str = (swa_type == LLAMA_SWA_TYPE_NONE) ? "LLAMA_SWA_TYPE_NONE" :
(swa_type == LLAMA_SWA_TYPE_STANDARD) ? "LLAMA_SWA_TYPE_STANDARD" :
(swa_type == LLAMA_SWA_TYPE_CHUNKED) ? "LLAMA_SWA_TYPE_CHUNKED" :
(swa_type == LLAMA_SWA_TYPE_SYMMETRIC) ? "LLAMA_SWA_TYPE_SYMMETRIC" : "unknown";
const char * swa_type_str = "unknown";
switch (swa_type) {
case LLAMA_SWA_TYPE_NONE: swa_type_str = "LLAMA_SWA_TYPE_NONE"; break;
case LLAMA_SWA_TYPE_STANDARD: swa_type_str = "LLAMA_SWA_TYPE_STANDARD"; break;
case LLAMA_SWA_TYPE_CHUNKED: swa_type_str = "LLAMA_SWA_TYPE_CHUNKED"; break;
case LLAMA_SWA_TYPE_SYMMETRIC: swa_type_str = "LLAMA_SWA_TYPE_SYMMETRIC"; break;
};
LLAMA_LOG_DEBUG("%s: n_swa : %d, n_kv: %d, swq_type: %s\n", __func__, (int)n_swa, (int)n_kv, swa_type_str);
LLAMA_LOG_DEBUG("%s: '0' = can attend, '∞' = masked\n", __func__);
LLAMA_LOG_DEBUG("%s: Rows = query tokens, Columns = key/value tokens\n\n", __func__);
@@ -295,50 +300,67 @@ void llm_graph_input_attn_no_cache::set_input(const llama_ubatch * ubatch) {
const int64_t n_kv = ubatch->n_tokens;
const int64_t n_tokens = ubatch->n_tokens;
GGML_ASSERT(kq_mask);
GGML_ASSERT(ggml_backend_buffer_is_host(kq_mask->buffer));
const auto fill_mask = [&](float * data, int n_swa, llama_swa_type swa_type) {
for (int h = 0; h < 1; ++h) {
for (int i1 = 0; i1 < n_tokens; ++i1) {
const llama_seq_id s1 = ubatch->seq_id[i1][0];
const llama_pos p1 = ubatch->pos[i1];
float * data = (float *) kq_mask->data;
const uint64_t idst = h*(n_kv*n_tokens) + i1*n_kv;
// [TAG_NO_CACHE_ISWA]
GGML_ASSERT(hparams.swa_type == LLAMA_SWA_TYPE_NONE && "TODO: implement");
for (int h = 0; h < 1; ++h) {
for (int i1 = 0; i1 < n_tokens; ++i1) {
const llama_seq_id s1 = ubatch->seq_id[i1][0];
for (int i0 = 0; i0 < n_tokens; ++i0) {
float f = -INFINITY;
for (int s = 0; s < ubatch->n_seq_id[i0]; ++s) {
for (int i0 = 0; i0 < n_tokens; ++i0) {
const llama_seq_id s0 = ubatch->seq_id[i0][0];
const llama_pos p0 = ubatch->pos[i0];
// mask different sequences
if (s0 != s1) {
continue; // skip different sequences
continue;
}
if (cparams.causal_attn && ubatch->pos[i0] > ubatch->pos[i1]) {
continue; // skip future tokens for causal attention
// mask future tokens
if (cparams.causal_attn && p0 > p1) {
continue;
}
// TODO: this does not take into account that some layers are SWA and others are note (i.e. iSWA) [TAG_NO_CACHE_ISWA]
//if (hparams.is_masked_swa(ubatch->pos[i0], ubatch->pos[i1])) {
// continue; // skip masked tokens for SWA
//}
// TODO: reimplement this like in llama_kv_cache_unified
if (hparams.use_alibi) {
f = -std::abs(ubatch->pos[i0] - ubatch->pos[i1]);
} else {
f = 0.0f;
// apply SWA if any
if (llama_hparams::is_masked_swa(n_swa, swa_type, p0, p1)) {
continue;
}
data[idst + i0] = hparams.use_alibi ? -std::abs(p0 - p1) : 0.0f;
}
data[h*(n_kv*n_tokens) + i1*n_kv + i0] = f;
}
}
};
{
GGML_ASSERT(self_kq_mask);
GGML_ASSERT(ggml_backend_buffer_is_host(self_kq_mask->buffer));
float * data = (float *) self_kq_mask->data;
std::fill(data, data + ggml_nelements(self_kq_mask), -INFINITY);
fill_mask(data, 0, LLAMA_SWA_TYPE_NONE);
if (debug) {
print_mask(data, n_tokens, n_kv, 0, LLAMA_SWA_TYPE_NONE);
}
}
if (debug) {
print_mask(data, n_tokens, n_kv, hparams.n_swa, hparams.swa_type);
if (hparams.swa_type != LLAMA_SWA_TYPE_NONE) {
GGML_ASSERT(self_kq_mask_swa);
GGML_ASSERT(ggml_backend_buffer_is_host(self_kq_mask_swa->buffer));
float * data = (float *) self_kq_mask_swa->data;
std::fill(data, data + ggml_nelements(self_kq_mask_swa), -INFINITY);
fill_mask(data, hparams.n_swa, hparams.swa_type);
if (debug) {
print_mask(data, n_tokens, n_kv, hparams.n_swa, hparams.swa_type);
}
}
}
@@ -1299,12 +1321,9 @@ ggml_tensor * llm_graph_context::build_attn_mha(
k = ggml_permute(ctx0, k, 0, 2, 1, 3);
v = ggml_permute(ctx0, v, 0, 2, 1, 3);
const auto n_kv = k->ne[1];
ggml_tensor * cur;
// TODO: replace hardcoded padding with ggml-provided padding
if (cparams.flash_attn && (n_kv % 256 == 0) && kq_b == nullptr) {
if (cparams.flash_attn && kq_b == nullptr) {
GGML_ASSERT(kq_b == nullptr && "Flash attention does not support KQ bias yet");
if (v_trans) {
@@ -1419,10 +1438,20 @@ llm_graph_input_attn_no_cache * llm_graph_context::build_attn_inp_no_cache() con
auto inp = std::make_unique<llm_graph_input_attn_no_cache>(hparams, cparams);
// note: there is no KV cache, so the number of KV values is equal to the number of tokens in the batch
inp->kq_mask = ggml_new_tensor_4d(ctx0, GGML_TYPE_F32, n_tokens, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD), 1, 1);
ggml_set_input(inp->kq_mask);
inp->self_kq_mask = ggml_new_tensor_4d(ctx0, GGML_TYPE_F32, n_tokens, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD), 1, 1);
ggml_set_input(inp->self_kq_mask);
inp->kq_mask_cnv = cparams.flash_attn ? ggml_cast(ctx0, inp->kq_mask, GGML_TYPE_F16) : inp->kq_mask;
inp->self_kq_mask_cnv = cparams.flash_attn ? ggml_cast(ctx0, inp->self_kq_mask, GGML_TYPE_F16) : inp->self_kq_mask;
if (hparams.swa_type != LLAMA_SWA_TYPE_NONE) {
inp->self_kq_mask_swa = ggml_new_tensor_4d(ctx0, GGML_TYPE_F32, n_tokens, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD), 1, 1);
ggml_set_input(inp->self_kq_mask_swa);
inp->self_kq_mask_swa_cnv = cparams.flash_attn ? ggml_cast(ctx0, inp->self_kq_mask_swa, GGML_TYPE_F16) : inp->self_kq_mask_swa;
} else {
inp->self_kq_mask_swa = nullptr;
inp->self_kq_mask_swa_cnv = nullptr;
}
return (llm_graph_input_attn_no_cache *) res->add_input(std::move(inp));
}
@@ -1447,7 +1476,9 @@ ggml_tensor * llm_graph_context::build_attn(
ggml_build_forward_expand(gf, k_cur);
ggml_build_forward_expand(gf, v_cur);
const auto & kq_mask = inp->get_kq_mask();
const bool is_swa = hparams.is_swa(il);
const auto & kq_mask = is_swa ? inp->get_kq_mask_swa() : inp->get_kq_mask();
// [TAG_NO_CACHE_PAD]
// TODO: if ubatch.equal_seqs() == true, we can split the three tensors below into ubatch.n_seqs_unq streams
+7 -3
View File
@@ -257,10 +257,14 @@ public:
void set_input(const llama_ubatch * ubatch) override;
ggml_tensor * get_kq_mask() const { return kq_mask_cnv; }
ggml_tensor * get_kq_mask() const { return self_kq_mask_cnv; }
ggml_tensor * get_kq_mask_swa() const { return self_kq_mask_swa_cnv; }
ggml_tensor * kq_mask = nullptr; // F32 [n_tokens, n_batch, 1, 1]
ggml_tensor * kq_mask_cnv = nullptr; // [n_tokens, n_batch, 1, 1]
// n_tokens == n_batch
ggml_tensor * self_kq_mask = nullptr; // F32 [n_tokens, n_batch/n_stream, 1, n_stream]
ggml_tensor * self_kq_mask_cnv = nullptr; // [n_tokens, n_batch/n_stream, 1, n_stream]
ggml_tensor * self_kq_mask_swa = nullptr; // F32 [n_tokens, n_batch/n_stream, 1, n_stream]
ggml_tensor * self_kq_mask_swa_cnv = nullptr; // [n_tokens, n_batch/n_stream, 1, n_stream]
const llama_hparams hparams;
const llama_cparams cparams;
+5 -6
View File
@@ -11358,8 +11358,8 @@ struct llm_build_gemma3n_iswa : public llm_graph_context {
}
};
struct llm_build_gemma_embedding_iswa : public llm_graph_context {
llm_build_gemma_embedding_iswa(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {
struct llm_build_gemma_embedding : public llm_graph_context {
llm_build_gemma_embedding(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {
const int64_t n_embd_head = hparams.n_embd_head_k;
ggml_tensor * cur;
@@ -11376,8 +11376,7 @@ struct llm_build_gemma_embedding_iswa : public llm_graph_context {
// inp_pos - contains the positions
ggml_tensor * inp_pos = build_inp_pos();
// TODO: support cacheless iSWA embeddings [TAG_NO_CACHE_ISWA]
auto * inp_attn = build_attn_inp_kv_iswa();
auto * inp_attn = build_attn_inp_no_cache();
ggml_tensor * inp_out_ids = build_inp_out_ids();
@@ -19378,7 +19377,7 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
case LLM_ARCH_NOMIC_BERT_MOE:
case LLM_ARCH_NEO_BERT:
case LLM_ARCH_WAVTOKENIZER_DEC:
//case LLM_ARCH_GEMMA_EMBEDDING: // TODO: disabled until the cacheless SWA logic is fixed [TAG_NO_CACHE_ISWA]
case LLM_ARCH_GEMMA_EMBEDDING:
case LLM_ARCH_DREAM:
case LLM_ARCH_LLADA:
case LLM_ARCH_LLADA_MOE:
@@ -19671,7 +19670,7 @@ ggml_cgraph * llama_model::build_graph(const llm_graph_params & params) const {
} break;
case LLM_ARCH_GEMMA_EMBEDDING:
{
llm = std::make_unique<llm_build_gemma_embedding_iswa>(*this, params);
llm = std::make_unique<llm_build_gemma_embedding>(*this, params);
} break;
case LLM_ARCH_STARCODER2:
{
+1
View File
@@ -312,6 +312,7 @@ struct llama_model * llama_model_load_from_splits(
LLAMA_LOG_ERROR("%s: list of splits is empty\n", __func__);
return nullptr;
}
splits.reserve(n_paths);
for (size_t i = 0; i < n_paths; ++i) {
splits.push_back(paths[i]);
}
+1 -1
View File
@@ -6779,7 +6779,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
for (int nb : { 1, 3, 32, 35, }) {
for (ggml_prec prec : {GGML_PREC_F32, GGML_PREC_DEFAULT}) {
if (hsk != 128 && prec == GGML_PREC_DEFAULT) continue;
for (ggml_type type_KV : {GGML_TYPE_F16, GGML_TYPE_BF16, GGML_TYPE_Q8_0, GGML_TYPE_Q4_0}) {
for (ggml_type type_KV : {GGML_TYPE_F32, GGML_TYPE_F16, GGML_TYPE_BF16, GGML_TYPE_Q8_0, GGML_TYPE_Q4_0}) {
test_cases.emplace_back(new test_flash_attn_ext(
hsk, hsv, nh, {nr2, nr3}, kv, nb, mask, sinks, max_bias, logit_softcap, prec, type_KV));
// run fewer test cases permuted
Binary file not shown.
+13 -5
View File
@@ -1585,23 +1585,31 @@ struct server_prompt_cache {
}
}
// average size per token
const float size_per_token = std::max<float>(1.0f, float(size()) / (std::max<size_t>(1, n_tokens())));
// dynamically increase the token limit if it can fit in the memory limit
const size_t limit_tokens_cur = limit_size > 0 ? std::max<size_t>(limit_tokens, limit_size/size_per_token) : limit_tokens;
if (limit_tokens > 0) {
while (states.size() > 1 && n_tokens() > limit_tokens) {
while (states.size() > 1 && n_tokens() > limit_tokens_cur) {
if (states.empty()) {
break;
}
SRV_WRN(" - cache token limit reached, removing oldest entry (size = %.3f MiB)\n", states.front().size() / (1024.0 * 1024.0));
SRV_WRN(" - cache token limit (%zu, est: %zu) reached, removing oldest entry (size = %.3f MiB)\n",
limit_tokens, limit_tokens_cur, states.front().size() / (1024.0 * 1024.0));
states.pop_front();
}
}
SRV_WRN(" - cache state: %zu prompts, %.3f MiB (limits: %.3f MiB, %zu tokens)\n",
states.size(), size() / (1024.0 * 1024.0), limit_size / (1024.0 * 1024.0), limit_tokens);
SRV_WRN(" - cache state: %zu prompts, %.3f MiB (limits: %.3f MiB, %zu tokens, %zu est)\n",
states.size(), size() / (1024.0 * 1024.0), limit_size / (1024.0 * 1024.0), limit_tokens, limit_tokens_cur);
for (const auto & state : states) {
SRV_WRN(" - prompt %p: %7d tokens, checkpoints: %2zu, %9.3f MiB\n", (const void *)&state, state.n_tokens(), state.checkpoints.size(), state.size() / (1024.0 * 1024.0));
SRV_WRN(" - prompt %p: %7d tokens, checkpoints: %2zu, %9.3f MiB\n",
(const void *)&state, state.n_tokens(), state.checkpoints.size(), state.size() / (1024.0 * 1024.0));
}
}
};
+69
View File
@@ -50,6 +50,7 @@
"eslint-plugin-svelte": "^3.0.0",
"fflate": "^0.8.2",
"globals": "^16.0.0",
"mdast": "^3.0.0",
"mdsvex": "^0.12.3",
"playwright": "^1.53.0",
"prettier": "^3.4.2",
@@ -66,6 +67,7 @@
"tw-animate-css": "^1.3.5",
"typescript": "^5.0.0",
"typescript-eslint": "^8.20.0",
"unified": "^11.0.5",
"uuid": "^13.0.0",
"vite": "^7.0.4",
"vite-plugin-devtools-json": "^0.2.0",
@@ -2128,6 +2130,66 @@
"node": ">=14.0.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@emnapi/core": {
"version": "1.4.3",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"@emnapi/wasi-threads": "1.0.2",
"tslib": "^2.4.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@emnapi/runtime": {
"version": "1.4.3",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"tslib": "^2.4.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@emnapi/wasi-threads": {
"version": "1.0.2",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"tslib": "^2.4.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@napi-rs/wasm-runtime": {
"version": "0.2.11",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"@emnapi/core": "^1.4.3",
"@emnapi/runtime": "^1.4.3",
"@tybys/wasm-util": "^0.9.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@tybys/wasm-util": {
"version": "0.9.0",
"dev": true,
"inBundle": true,
"license": "MIT",
"optional": true,
"dependencies": {
"tslib": "^2.4.0"
}
},
"node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/tslib": {
"version": "2.8.0",
"dev": true,
"inBundle": true,
"license": "0BSD",
"optional": true
},
"node_modules/@tailwindcss/oxide-win32-arm64-msvc": {
"version": "4.1.11",
"resolved": "https://registry.npmjs.org/@tailwindcss/oxide-win32-arm64-msvc/-/oxide-win32-arm64-msvc-4.1.11.tgz",
@@ -4946,6 +5008,13 @@
"url": "https://github.com/sponsors/wooorm"
}
},
"node_modules/mdast": {
"version": "3.0.0",
"resolved": "https://registry.npmjs.org/mdast/-/mdast-3.0.0.tgz",
"integrity": "sha512-xySmf8g4fPKMeC07jXGz971EkLbWAJ83s4US2Tj9lEdnZ142UP5grN73H1Xd3HzrdbU5o9GYYP/y8F9ZSwLE9g==",
"dev": true,
"license": "MIT"
},
"node_modules/mdast-util-find-and-replace": {
"version": "3.0.2",
"resolved": "https://registry.npmjs.org/mdast-util-find-and-replace/-/mdast-util-find-and-replace-3.0.2.tgz",
+2
View File
@@ -52,6 +52,7 @@
"eslint-plugin-svelte": "^3.0.0",
"fflate": "^0.8.2",
"globals": "^16.0.0",
"mdast": "^3.0.0",
"mdsvex": "^0.12.3",
"playwright": "^1.53.0",
"prettier": "^3.4.2",
@@ -68,6 +69,7 @@
"tw-animate-css": "^1.3.5",
"typescript": "^5.0.0",
"typescript-eslint": "^8.20.0",
"unified": "^11.0.5",
"uuid": "^13.0.0",
"vite": "^7.0.4",
"vite-plugin-devtools-json": "^0.2.0",
@@ -14,6 +14,7 @@
import githubDarkCss from 'highlight.js/styles/github-dark.css?inline';
import githubLightCss from 'highlight.js/styles/github.css?inline';
import { mode } from 'mode-watcher';
import { remarkLiteralHtml } from '$lib/markdown/literal-html';
interface Props {
content: string;
@@ -50,36 +51,59 @@
.use(remarkGfm) // GitHub Flavored Markdown
.use(remarkMath) // Parse $inline$ and $$block$$ math
.use(remarkBreaks) // Convert line breaks to <br>
.use(remarkRehype) // Convert to rehype (HTML AST)
.use(remarkLiteralHtml) // Treat raw HTML as literal text with preserved indentation
.use(remarkRehype) // Convert Markdown AST to rehype
.use(rehypeKatex) // Render math using KaTeX
.use(rehypeHighlight) // Add syntax highlighting
.use(rehypeStringify); // Convert to HTML string
});
function enhanceLinks(html: string): string {
if (!html.includes('<a')) {
return html;
}
const tempDiv = document.createElement('div');
tempDiv.innerHTML = html;
// Make all links open in new tabs
const linkElements = tempDiv.querySelectorAll('a[href]');
let mutated = false;
for (const link of linkElements) {
const target = link.getAttribute('target');
const rel = link.getAttribute('rel');
if (target !== '_blank' || rel !== 'noopener noreferrer') {
mutated = true;
}
link.setAttribute('target', '_blank');
link.setAttribute('rel', 'noopener noreferrer');
}
return tempDiv.innerHTML;
return mutated ? tempDiv.innerHTML : html;
}
function enhanceCodeBlocks(html: string): string {
if (!html.includes('<pre')) {
return html;
}
const tempDiv = document.createElement('div');
tempDiv.innerHTML = html;
const preElements = tempDiv.querySelectorAll('pre');
let mutated = false;
for (const [index, pre] of Array.from(preElements).entries()) {
const codeElement = pre.querySelector('code');
if (!codeElement) continue;
if (!codeElement) {
continue;
}
mutated = true;
let language = 'text';
const classList = Array.from(codeElement.classList);
@@ -127,7 +151,7 @@
pre.parentNode?.replaceChild(wrapper, pre);
}
return tempDiv.innerHTML;
return mutated ? tempDiv.innerHTML : html;
}
async function processMarkdown(text: string): Promise<string> {
@@ -0,0 +1,15 @@
export const LINE_BREAK = /\r?\n/;
export const PHRASE_PARENTS = new Set([
'paragraph',
'heading',
'emphasis',
'strong',
'delete',
'link',
'linkReference',
'tableCell'
]);
export const NBSP = '\u00a0';
export const TAB_AS_SPACES = NBSP.repeat(4);
@@ -0,0 +1,121 @@
import type { Plugin } from 'unified';
import { visit } from 'unist-util-visit';
import type { Break, Content, Paragraph, PhrasingContent, Root, Text } from 'mdast';
import { LINE_BREAK, NBSP, PHRASE_PARENTS, TAB_AS_SPACES } from '$lib/constants/literal-html';
/**
* remark plugin that rewrites raw HTML nodes into plain-text equivalents.
*
* remark parses inline HTML into `html` nodes even when we do not want to render
* them. We turn each of those nodes into regular text (plus `<br>` break markers)
* so the downstream rehype pipeline escapes the characters instead of executing
* them. Leading spaces and tab characters are converted to nonbreaking spaces to
* keep indentation identical to the original author input.
*/
function preserveIndent(line: string): string {
let index = 0;
let output = '';
while (index < line.length) {
const char = line[index];
if (char === ' ') {
output += NBSP;
index += 1;
continue;
}
if (char === '\t') {
output += TAB_AS_SPACES;
index += 1;
continue;
}
break;
}
return output + line.slice(index);
}
function createLiteralChildren(value: string): PhrasingContent[] {
const lines = value.split(LINE_BREAK);
const nodes: PhrasingContent[] = [];
for (const [lineIndex, rawLine] of lines.entries()) {
if (lineIndex > 0) {
nodes.push({ type: 'break' } as Break as unknown as PhrasingContent);
}
nodes.push({
type: 'text',
value: preserveIndent(rawLine)
} as Text as unknown as PhrasingContent);
}
if (!nodes.length) {
nodes.push({ type: 'text', value: '' } as Text as unknown as PhrasingContent);
}
return nodes;
}
export const remarkLiteralHtml: Plugin<[], Root> = () => {
return (tree) => {
visit(tree, 'html', (node, index, parent) => {
if (!parent || typeof index !== 'number') {
return;
}
const replacement = createLiteralChildren(node.value);
if (!PHRASE_PARENTS.has(parent.type as string)) {
const paragraph: Paragraph = {
type: 'paragraph',
children: replacement as Paragraph['children'],
data: { literalHtml: true }
};
const siblings = parent.children as unknown as Content[];
siblings.splice(index, 1, paragraph as unknown as Content);
if (index > 0) {
const previous = siblings[index - 1] as Paragraph | undefined;
if (
previous?.type === 'paragraph' &&
(previous.data as { literalHtml?: boolean } | undefined)?.literalHtml
) {
const prevChildren = previous.children as unknown as PhrasingContent[];
if (prevChildren.length) {
const lastChild = prevChildren[prevChildren.length - 1];
if (lastChild.type !== 'break') {
prevChildren.push({
type: 'break'
} as Break as unknown as PhrasingContent);
}
}
prevChildren.push(...(paragraph.children as unknown as PhrasingContent[]));
siblings.splice(index, 1);
return index;
}
}
return index + 1;
}
(parent.children as unknown as PhrasingContent[]).splice(
index,
1,
...(replacement as unknown as PhrasingContent[])
);
return index + replacement.length;
});
};
};