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f3f65429c4
* scripts : update sync [no ci] * files : relocate [no ci] * ci : disable kompute build [no ci] * cmake : fixes [no ci] * server : fix mingw build ggml-ci * cmake : minor [no ci] * cmake : link math library [no ci] * cmake : build normal ggml library (not object library) [no ci] * cmake : fix kompute build ggml-ci * make,cmake : fix LLAMA_CUDA + replace GGML_CDEF_PRIVATE ggml-ci * move public backend headers to the public include directory (#8122) * move public backend headers to the public include directory * nix test * spm : fix metal header --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * scripts : fix sync paths [no ci] * scripts : sync ggml-blas.h [no ci] --------- Co-authored-by: slaren <slarengh@gmail.com>
52 lines
2.1 KiB
Plaintext
52 lines
2.1 KiB
Plaintext
#include "upscale.cuh"
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static __global__ void upscale_f32(const float * x, float * dst,
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const int nb00, const int nb01, const int nb02, const int nb03,
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const int ne10, const int ne11, const int ne12, const int ne13,
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const float sf0, const float sf1, const float sf2, const float sf3) {
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int index = threadIdx.x + blockIdx.x * blockDim.x;
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if (index >= ne10 * ne11 * ne12 * ne13) {
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return;
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}
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int i10 = index % ne10;
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int i11 = (index / ne10) % ne11;
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int i12 = (index / (ne10 * ne11)) % ne12;
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int i13 = (index / (ne10 * ne11 * ne12)) % ne13;
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int i00 = i10 / sf0;
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int i01 = i11 / sf1;
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int i02 = i12 / sf2;
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int i03 = i13 / sf3;
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dst[index] = *(float *)((char *)x + i03 * nb03 + i02 * nb02 + i01 * nb01 + i00 * nb00);
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}
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static void upscale_f32_cuda(const float * x, float * dst,
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const int nb00, const int nb01, const int nb02, const int nb03,
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const int ne10, const int ne11, const int ne12, const int ne13,
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const float sf0, const float sf1, const float sf2, const float sf3,
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cudaStream_t stream) {
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int dst_size = ne10 * ne11 * ne12 * ne13;
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int num_blocks = (dst_size + CUDA_UPSCALE_BLOCK_SIZE - 1) / CUDA_UPSCALE_BLOCK_SIZE;
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upscale_f32<<<num_blocks, CUDA_UPSCALE_BLOCK_SIZE,0,stream>>>(x, dst, nb00, nb01, nb02, nb03, ne10, ne11, ne12, ne13, sf0, sf1, sf2, sf3);
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}
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void ggml_cuda_op_upscale(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
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const ggml_tensor * src0 = dst->src[0];
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const float * src0_d = (const float *)src0->data;
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float * dst_d = (float *)dst->data;
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cudaStream_t stream = ctx.stream();
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GGML_ASSERT(src0->type == GGML_TYPE_F32);
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GGML_ASSERT( dst->type == GGML_TYPE_F32);
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const float sf0 = (float)dst->ne[0]/src0->ne[0];
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const float sf1 = (float)dst->ne[1]/src0->ne[1];
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const float sf2 = (float)dst->ne[2]/src0->ne[2];
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const float sf3 = (float)dst->ne[3]/src0->ne[3];
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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);
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}
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