CS348Project/llama.cpp
5
0
Fork 0
mirror of https://github.com/ggml-org/llama.cpp.git synced 2025-11-17 11:37:10 +00:00
Code Issues Packages Projects Releases Wiki Activity

ggml: add ops for WAN video model (cuda && cpu) (#15669)

Browse Source 
* add conv3d support

* add ggml_pad_ext for cpu & cuda backend

* cuda/cpu: add im2col_3d support

* cuda: make im2col a little faster

* fix cuda pad/scale/im2col3d

* make im2col_3d faster

* gguf: support loading tensors which n_dims > GGML_MAX_DIMS

* fix cuda get_rows

* avoid ggml_conv_3d conflict

* correct GGML_OP_COUNT assertion

* avoid build failure

* avoid build failure on MacOS

* cuda: remove unnecessary MIN define

* fix cpu im2col_3d

* adjust the code style

* cuda: use simpler loop in get_rows

* add test_im2col_3d to test-backend-ops

* test-backend-ops.cpp: remove trailing whitespace

* cpu: im2col_3d support non continuous src

Co-authored-by: Jeff Bolz <jbolz@nvidia.com>

* fix test_im2col_3d

* remove unused variables

* cuda: get_rows: dfloat2 -> float2

* add test_pad_ext to test-backend-ops.cpp

* add gguf_init_from_file_ext impl

* Revert "gguf: support loading tensors which n_dims > GGML_MAX_DIMS"

This reverts commit d8377a0a37.

* Revert "add gguf_init_from_file_ext impl"

This reverts commit d9f1d13208.

* update ggml_backend_vk_device_supports_op

* fix ggml_backend_vk_device_supports_op

* update other backend supports op for ggml_pad_ext

* metal/opencl/sycl/vulkan: fix GGML_OP_PAD check in supports_op

---------

Co-authored-by: Jeff Bolz <jbolz@nvidia.com>
This commit is contained in:
leejet
2025-09-04 16:38:49 +08:00
committed by GitHub
parent 5421f63ab0
commit 0a1b3982cd
17 changed files with 759 additions and 90 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
ggml/src/ggml-cuda/scale.cu
View File

@@ -1,18 +1,19 @@
#include "scale.cuh"
static __global__ void scale_f32(const float * x, float * dst, const float scale, const float bias, const int k) {
const int i = blockDim.x*blockIdx.x + threadIdx.x;
#define MAX_GRIDDIM_X 0x7FFFFFFF
if (i >= k) {
return;
static __global__ void scale_f32(const float * x, float * dst, const float scale, const float bias, const int64_t nelements) {
int64_t tid = (int64_t)blockIdx.x * (int64_t)blockDim.x + (int64_t)threadIdx.x;
int64_t stride = (int64_t)blockDim.x * (int64_t)gridDim.x;
for (int64_t i = tid; i < nelements; i += stride) {
dst[i] = scale * x[i] + bias;
}
dst[i] = scale * x[i] + bias;
}
static void scale_f32_cuda(const float * x, float * dst, const float scale, const float bias, const int k, cudaStream_t stream) {
const int num_blocks = (k + CUDA_SCALE_BLOCK_SIZE - 1) / CUDA_SCALE_BLOCK_SIZE;
scale_f32<<<num_blocks, CUDA_SCALE_BLOCK_SIZE, 0, stream>>>(x, dst, scale, bias, k);
static void scale_f32_cuda(const float * x, float * dst, const float scale, const float bias, const int64_t nelements, cudaStream_t stream) {
const int64_t num_blocks = (nelements + CUDA_SCALE_BLOCK_SIZE - 1) / CUDA_SCALE_BLOCK_SIZE;
scale_f32<<<MIN(MAX_GRIDDIM_X, num_blocks), CUDA_SCALE_BLOCK_SIZE, 0, stream>>>(x, dst, scale, bias, nelements);
}
void ggml_cuda_op_scale(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {