1#include "softcap.cuh"
2
3static __global__ void softcap_f32(const float * x, float * dst, const float scale, const float softcap, const int k) {
4 const int i = blockDim.x*blockIdx.x + threadIdx.x;
5
6 if (i >= k) {
7 return;
8 }
9
10 dst[i] = tanhf(a: scale * x[i]) * softcap;
11}
12
13static void softcap_f32_cuda(const float * x, float * dst, const float scale, const float softcap, const int k, cudaStream_t stream) {
14 const int num_blocks = (k + CUDA_SOFTCAP_BLOCK_SIZE - 1) / CUDA_SOFTCAP_BLOCK_SIZE;
15 softcap_f32<<<gridDim: num_blocks, CUDA_SOFTCAP_BLOCK_SIZE, sharedMem: 0, stream>>>(x, dst, scale, softcap, k);
16}
17
18// fused GGML_OP_SCALE + GGML_UNARY_OP_TANH + GGML_OP_SCALE
19void ggml_cuda_op_softcap(ggml_backend_cuda_context & ctx, ggml_tensor * dst, ggml_tensor * src) {
20 const ggml_tensor * src0 = src->src[0];
21 const float * src0_d = (const float *)src0->data;
22 float * dst_d = (float *)dst->data;
23 cudaStream_t stream = ctx.stream();
24
25 GGML_ASSERT(src0->type == GGML_TYPE_F32);
26 GGML_ASSERT( dst->type == GGML_TYPE_F32);
27
28 float scale;
29 float softcap;
30 memcpy(dest: &scale, src: (float *) src->op_params + 0, n: sizeof(float));
31 memcpy(dest: &softcap, src: (float *) dst->op_params + 0, n: sizeof(float));
32
33 softcap_f32_cuda(src0_d, dst_d, scale, softcap, ggml_nelements(src0), stream);
34}
35