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#include "clamp.cuh"
static __device__ __forceinline__ float op_clamp(float x, float min, float max) {
return fminf(fmaxf(x, min), max);
}
template <class T>
static __global__ void op_clamp_kernel(const T * x, T * dst, const T min, const T max, const int k) {
const int i = blockDim.x*blockIdx.x + threadIdx.x;
if (i >= k) {
return;
}
dst[i] = (T)op_clamp((float)x[i], (float)min, (float)max);
}
template <class T>
static void clamp_cuda(const T * x, T * dst, const T min, const T max, const int k, cudaStream_t stream) {
const int num_blocks = (k + CUDA_CLAMP_BLOCK_SIZE - 1) / CUDA_CLAMP_BLOCK_SIZE;
op_clamp_kernel<<<num_blocks, CUDA_CLAMP_BLOCK_SIZE, 0, stream>>>(x, dst, min, max, k);
}
void ggml_cuda_op_clamp(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
const ggml_tensor * src0 = dst->src[0];
const void * src0_d = src0->data;
void * dst_d = dst->data;
cudaStream_t stream = ctx.stream();
GGML_ASSERT(src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16);
GGML_ASSERT( dst->type == GGML_TYPE_F32 || dst->type == GGML_TYPE_F16);
GGML_ASSERT(src0->type == dst->type);
float min;
float max;
memcpy(&min, dst->op_params, sizeof(float));
memcpy(&max, (float *) dst->op_params + 1, sizeof(float));
if (src0->type == GGML_TYPE_F16) {
clamp_cuda((const half *)src0_d, (half *)dst_d, (half)min, (half)max, ggml_nelements(src0), stream);
} else {
clamp_cuda((const float *)src0_d, (float *)dst_d, (float)min, (float)max, ggml_nelements(src0), stream);
}
}
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