// 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 "paddle/fluid/lite/kernels/arm/mul_compute.h" #include "paddle/fluid/lite/arm/math/funcs.h" #include "paddle/fluid/lite/core/op_registry.h" #include "paddle/fluid/lite/core/type_system.h" namespace paddle { namespace lite { namespace kernels { namespace arm { void MulCompute::PrepareForRun() { // TODO(TJ): transpose x or y if necessary } void MulCompute::Run() { auto& param = Param(); const auto* x_data = param.x->data(); const auto* y_data = param.y->data(); auto* o_data = param.output->mutable_data(); int x_h = static_cast( param.x->dims().Slice(0, param.x_num_col_dims).production()); int x_w = static_cast(param.x->dims() .Slice(param.x_num_col_dims, param.x->dims().size()) .production()); int y_h = static_cast( param.y->dims().Slice(0, param.y_num_col_dims).production()); int y_w = static_cast(param.y->dims() .Slice(param.y_num_col_dims, param.y->dims().size()) .production()); CHECK_EQ(x_w, y_h) << "x_w must be equal with y_h"; if (y_w == 1 || x_h == 1) { lite::arm::math::sgemv(x_data, y_data, o_data, false, x_h, x_w, false, nullptr, false); } else { constexpr bool is_tranposed_y = false; auto& ctx = this->ctx_->template As(); lite::arm::math::sgemm_prepack(x_data, y_data, nullptr, o_data, x_h, y_w, x_w, false, false, is_tranposed_y, &ctx); } } } // namespace arm } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL(mul, kARM, kFloat, kNCHW, paddle::lite::kernels::arm::MulCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kARM))}) .BindInput("Y", {LiteType::GetTensorTy(TARGET(kARM))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kARM))}) .Finalize();