1#include "arange.cuh"
2
3static __global__ void arange_f32(float * dst, const int ne0, const float start, const float step) {
4 // blockIDx.x: idx of ne0 / BLOCK_SIZE
5 int nidx = threadIdx.x + blockIdx.x * blockDim.x;
6 if (nidx >= ne0) {
7 return;
8 }
9 dst[nidx] = start + step * nidx;
10}
11
12static void arange_f32_cuda(float * dst, const int ne0, const float start, const float step, cudaStream_t stream) {
13 int num_blocks = (ne0 + CUDA_ARANGE_BLOCK_SIZE - 1) / CUDA_ARANGE_BLOCK_SIZE;
14 arange_f32<<<gridDim: num_blocks, CUDA_ARANGE_BLOCK_SIZE, sharedMem: 0, stream>>>(dst, ne0, start, step);
15}
16
17void ggml_cuda_op_arange(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
18 float * dst_d = (float *)dst->data;
19 cudaStream_t stream = ctx.stream();
20
21 GGML_ASSERT(dst->type == GGML_TYPE_F32);
22
23 float start;
24 float stop;
25 float step;
26 memcpy(dest: &start, src: (float *)dst->op_params + 0, n: sizeof(float));
27 memcpy(dest: &stop, src: (float *)dst->op_params + 1, n: sizeof(float));
28 memcpy(dest: &step, src: (float *)dst->op_params + 2, n: sizeof(float));
29
30 int64_t steps = (int64_t)ceil(x: (stop - start) / step);
31 GGML_ASSERT(ggml_nelements(dst) == steps);
32
33 arange_f32_cuda(dst_d, dst->ne[0], start, step, stream);
34}
35