// Copyright (c) 2018 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 "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/operators/math/math_function.h" namespace paddle { namespace operators { using LoDTensor = framework::LoDTensor; template class SequenceReshapeKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto* in = context.Input("X"); auto* out = context.Output("Out"); int out_width = context.Attr("new_dim"); auto in_dims = in->dims(); int64_t in_width = in_dims[1]; auto& in_lod = in->lod(); PADDLE_ENFORCE_EQ(in_lod.size(), 1UL, "Only support one level sequence now."); PADDLE_ENFORCE_EQ( (uint64_t)in_dims[0], in_lod[0].back(), "Inconsistent size between X.shape[0] and X.lod()[0].back()."); auto in_lod_l0 = in_lod[0]; int seq_num = in_lod_l0.size() - 1; if (in_width == out_width) { out->set_lod(in->lod()); } else { auto& out_lod = *out->mutable_lod(); out_lod.resize(1); out_lod[0].resize(seq_num + 1); out_lod[0][0] = 0; for (int i = 0; i < seq_num; ++i) { size_t seq_len = in_lod_l0[i + 1] - in_lod_l0[i]; size_t offset = 0; offset = (seq_len * in_width) / out_width; PADDLE_ENFORCE_EQ(offset * out_width, seq_len * in_width, "Please make sure (sequence_length * dimension) can " "be divided by new_dim with no remainder for each " "sequence. The %dth sequence is invalid.", i + 1); out_lod[0][i + 1] = out_lod[0][i] + offset; } } framework::TensorCopy(*in, context.GetPlace(), out); out->Resize({static_cast(out->lod()[0].back()), out_width}); } }; template class SequenceReshapeGradKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto* x_tensor_ptr = context.Input("X"); auto* outg_tensor_ptr = context.Input(framework::GradVarName("Out")); auto* xg_tensor_ptr = context.Output(framework::GradVarName("X")); xg_tensor_ptr->mutable_data(context.GetPlace()); framework::TensorCopy(*outg_tensor_ptr, context.GetPlace(), xg_tensor_ptr); xg_tensor_ptr->Resize(x_tensor_ptr->dims()); } }; } // namespace operators } // namespace paddle