// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #include "lite/kernels/xpu/mul_compute.h" #include "lite/backends/xpu/xpu_header_sitter.h" #include "lite/core/op_registry.h" namespace paddle { namespace lite { namespace kernels { namespace xpu { void MulCompute::Run() { auto& param = this->Param(); auto& ctx = this->ctx_->As(); auto& origin_x = *param.x; auto& origin_y = *param.y; auto& x_dims = origin_x.dims(); auto& y_dims = origin_y.dims(); Tensor x_matrix, y_matrix; if (x_dims.size() > 2) { x_matrix = ReshapeToMatrix(origin_x, param.x_num_col_dims); } else { x_matrix = origin_x; } if (y_dims.size() > 2) { y_matrix = ReshapeToMatrix(origin_y, param.y_num_col_dims); } else { y_matrix = origin_y; } int m = x_matrix.dims()[0]; int k = x_matrix.dims()[1]; int n = y_matrix.dims()[1]; int r = xdnn::fc_int16(ctx.GetRawContext(), /* context */ false, /* TransA */ false, /* TransB */ m, n, k, 1.0f, /* alpha */ x_matrix.data(), /* A */ y_matrix.data(), /* B */ 0.0f, /* beta */ param.output->mutable_data(TARGET(kXPU)) /* C */); CHECK_EQ(r, 0); } } // namespace xpu } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL( mul, kXPU, kFloat, kNCHW, paddle::lite::kernels::xpu::MulCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindInput("Y", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))}) .Finalize();