mirror of
https://github.com/ggerganov/llama.cpp.git
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35 lines
1.1 KiB
Plaintext
35 lines
1.1 KiB
Plaintext
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#include "clamp.cuh"
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static __global__ void clamp_f32(const float * x, float * dst, const float min, const float max, const int k) {
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const int i = blockDim.x*blockIdx.x + threadIdx.x;
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if (i >= k) {
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return;
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}
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dst[i] = x[i] < min ? min : (x[i] > max ? max : x[i]);
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}
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static void clamp_f32_cuda(const float * x, float * dst, const float min, const float max, const int k, cudaStream_t stream) {
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const int num_blocks = (k + CUDA_CLAMP_BLOCK_SIZE - 1) / CUDA_CLAMP_BLOCK_SIZE;
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clamp_f32<<<num_blocks, CUDA_CLAMP_BLOCK_SIZE, 0, stream>>>(x, dst, min, max, k);
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}
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void ggml_cuda_op_clamp(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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float min;
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float max;
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memcpy(&min, dst->op_params, sizeof(float));
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memcpy(&max, (float *) dst->op_params + 1, sizeof(float));
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clamp_f32_cuda(src0_d, dst_d, min, max, ggml_nelements(src0), stream);
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}
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