#include "clamp.cuh"

template <class T>
static __global__ void op_clamp(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] = x[i] < min ? min : (x[i] > max ? max : x[i]);
}

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<<<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);
    }
}