#include "out-prod.cuh" #include void ggml_cuda_out_prod(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { const ggml_tensor * src0 = dst->src[0]; const ggml_tensor * src1 = dst->src[1]; GGML_TENSOR_BINARY_OP_LOCALS GGML_ASSERT(src0->type == GGML_TYPE_F32); GGML_ASSERT(src1->type == GGML_TYPE_F32); GGML_ASSERT(dst->type == GGML_TYPE_F32); GGML_ASSERT(ggml_is_contiguous(src0)); GGML_ASSERT(ggml_is_contiguous(dst)); GGML_ASSERT(ne01 == ne11); GGML_ASSERT(ne0 == ne00); GGML_ASSERT(ne1 == ne10); GGML_ASSERT(ne2 == src0->ne[2]); GGML_ASSERT(ne2 == src1->ne[2]); GGML_ASSERT(ne3 == src0->ne[3]); GGML_ASSERT(ne3 == src1->ne[3]); const float * src0_d = (const float *) src0->data; const float * src1_d = (const float *) src1->data; float * dst_d = (float *) dst->data; cudaStream_t stream = ctx.stream(); cublasHandle_t handle = ctx.cublas_handle(); const float alpha = 1.0f; const float beta = 0.0f; GGML_ASSERT(ne2 == 1); GGML_ASSERT(ne3 == 1); CUBLAS_CHECK(cublasSetStream(handle, stream)); const bool src1_T = ggml_is_transposed(src1); const cublasOperation_t src1_cublas_op = src1_T ? CUBLAS_OP_N : CUBLAS_OP_T; const int64_t ldb = (src1_T ? nb10 : nb11) / sizeof(float); GGML_ASSERT( (src1_T ? nb11 : nb10) == sizeof(float)); CUBLAS_CHECK( cublasSgemm(handle, CUBLAS_OP_N, src1_cublas_op, ne0, ne1, ne01, &alpha, src0_d, ne00, src1_d, ldb, &beta, dst_d, ne0)); }