1#include "clamp.cuh"
2
3static __device__ __forceinline__ float op_clamp(float x, float min, float max) {
4 return fminf(a: fmaxf(a: x, b: min), b: max);
5}
6
7template <class T>
8static __global__ void op_clamp_kernel(const T * x, T * dst, const T min, const T max, const int k) {
9 const int i = blockDim.x*blockIdx.x + threadIdx.x;
10
11 if (i >= k) {
12 return;
13 }
14
15 dst[i] = (T)op_clamp(x: (float)x[i], min: (float)min, max: (float)max);
16}
17
18template <class T>
19static void clamp_cuda(const T * x, T * dst, const T min, const T max, const int k, cudaStream_t stream) {
20 const int num_blocks = (k + CUDA_CLAMP_BLOCK_SIZE - 1) / CUDA_CLAMP_BLOCK_SIZE;
21 op_clamp_kernel<<<gridDim: num_blocks, CUDA_CLAMP_BLOCK_SIZE, sharedMem: 0, stream>>>(x, dst, min, max, k);
22}
23
24
25void ggml_cuda_op_clamp(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
26 const ggml_tensor * src0 = dst->src[0];
27 const void * src0_d = src0->data;
28 void * dst_d = dst->data;
29 cudaStream_t stream = ctx.stream();
30
31 GGML_ASSERT(src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16);
32 GGML_ASSERT( dst->type == GGML_TYPE_F32 || dst->type == GGML_TYPE_F16);
33 GGML_ASSERT(src0->type == dst->type);
34
35 float min;
36 float max;
37 memcpy(&min, dst->op_params, sizeof(float));
38 memcpy(dest: &max, src: (float *) dst->op_params + 1, n: sizeof(float));
39
40 if (src0->type == GGML_TYPE_F16) {
41 clamp_cuda((const half *)src0_d, (half *)dst_d, (half)min, (half)max, ggml_nelements(src0), stream);
42 } else {
43 clamp_cuda((const float *)src0_d, (float *)dst_d, (float)min, (float)max, ggml_nelements(src0), stream);
44 }
45}
46