// Copyright (c) 2020 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. #pragma once #include #include "paddle/fluid/framework/op_registry.h" namespace paddle { namespace operators { using Tensor = framework::Tensor; using LoDTensor = framework::LoDTensor; using DDim = framework::DDim; template class MaskedSelectKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto input = context.Input("X"); auto mask = context.Input("Mask"); auto out = context.Output("Y"); auto* mask_data = mask->data(); auto input_data = input->data(); auto mask_size = mask->numel(); auto input_dim = input->dims(); auto mask_dim = mask->dims(); PADDLE_ENFORCE_EQ( input_dim, mask_dim, platform::errors::InvalidArgument( "The dim size of input and mask in OP(masked_selected) " "must be equal, but got input dim:(%ld), mask dim: " "(%ld). Please check input " "value.", input_dim, mask_dim)); int out_size = 0; for (int i = 0; i < mask_size; i++) { if (mask_data[i]) out_size++; } framework::DDim out_dim{out_size}; out->Resize(out_dim); auto out_data = out->mutable_data(context.GetPlace()); int index = 0; for (int i = 0; i < mask_size; i++) { if (mask_data[i]) { out_data[index] = input_data[i]; index++; } } } }; template class MaskedSelectGradKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto out = context.Output(framework::GradVarName("X")); auto mask = context.Input("Mask"); auto input = context.Input(framework::GradVarName("Y")); auto* mask_data = mask->data(); auto* input_data = input->data(); auto* out_data = out->mutable_data(context.GetPlace()); int mask_size = mask->numel(); int index = 0; for (int i = 0; i < mask_size; i++) { if (mask_data[i]) { out_data[i] = input_data[index]; index++; } else { out_data[i] = 0; } } } }; } // namespace operators } // namespace paddle