mirror of
https://github.com/ggerganov/whisper.cpp.git
synced 2024-12-30 01:08:52 +00:00
c4de1e19df
* initial commit with CPU implementation of upscale to shape and test, cuda implementation next * experimental commit to see if dst shape is correct * test version * test * removed unnecessary params * refactor * fixed tests * ggml : metal impl + cleanup + sycl dev warnings * patched ggml_upscale cuda op to handle non-contiguous tensors, added test for non-contiguous behavior * metal : fix upsacle op to support nb00 + style --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
52 lines
2.1 KiB
Plaintext
52 lines
2.1 KiB
Plaintext
#include "upscale.cuh"
|
|
|
|
static __global__ void upscale_f32(const float * x, float * dst,
|
|
const int nb00, const int nb01, const int nb02, const int nb03,
|
|
const int ne10, const int ne11, const int ne12, const int ne13,
|
|
const float sf0, const float sf1, const float sf2, const float sf3) {
|
|
int index = threadIdx.x + blockIdx.x * blockDim.x;
|
|
if (index >= ne10 * ne11 * ne12 * ne13) {
|
|
return;
|
|
}
|
|
|
|
int i10 = index % ne10;
|
|
int i11 = (index / ne10) % ne11;
|
|
int i12 = (index / (ne10 * ne11)) % ne12;
|
|
int i13 = (index / (ne10 * ne11 * ne12)) % ne13;
|
|
|
|
int i00 = i10 / sf0;
|
|
int i01 = i11 / sf1;
|
|
int i02 = i12 / sf2;
|
|
int i03 = i13 / sf3;
|
|
|
|
dst[index] = *(float *)((char *)x + i03 * nb03 + i02 * nb02 + i01 * nb01 + i00 * nb00);
|
|
}
|
|
|
|
static void upscale_f32_cuda(const float * x, float * dst,
|
|
const int nb00, const int nb01, const int nb02, const int nb03,
|
|
const int ne10, const int ne11, const int ne12, const int ne13,
|
|
const float sf0, const float sf1, const float sf2, const float sf3,
|
|
cudaStream_t stream) {
|
|
int dst_size = ne10 * ne11 * ne12 * ne13;
|
|
int num_blocks = (dst_size + CUDA_UPSCALE_BLOCK_SIZE - 1) / CUDA_UPSCALE_BLOCK_SIZE;
|
|
|
|
upscale_f32<<<num_blocks, CUDA_UPSCALE_BLOCK_SIZE,0,stream>>>(x, dst, nb00, nb01, nb02, nb03, ne10, ne11, ne12, ne13, sf0, sf1, sf2, sf3);
|
|
}
|
|
|
|
void ggml_cuda_op_upscale(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
|
|
const ggml_tensor * src0 = dst->src[0];
|
|
const float * src0_d = (const float *)src0->data;
|
|
float * dst_d = (float *)dst->data;
|
|
cudaStream_t stream = ctx.stream();
|
|
|
|
GGML_ASSERT(src0->type == GGML_TYPE_F32);
|
|
GGML_ASSERT( dst->type == GGML_TYPE_F32);
|
|
|
|
const float sf0 = (float)dst->ne[0]/src0->ne[0];
|
|
const float sf1 = (float)dst->ne[1]/src0->ne[1];
|
|
const float sf2 = (float)dst->ne[2]/src0->ne[2];
|
|
const float sf3 = (float)dst->ne[3]/src0->ne[3];
|
|
|
|
upscale_f32_cuda(src0_d, dst_d, src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3], dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3], sf0, sf1, sf2, sf3, stream);
|
|
}
|