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87 lines
3.0 KiB
87 lines
3.0 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/framework/op_registry.h"
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#include "paddle/operators/math/math_function.h"
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namespace paddle {
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namespace operators {
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using LoDTensor = framework::LoDTensor;
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template <typename DeviceContext, typename T>
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class SequenceReshapeKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* in = context.Input<LoDTensor>("X");
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auto* out = context.Output<LoDTensor>("Out");
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int out_width = context.Attr<int>("new_dim");
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auto in_dims = in->dims();
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int64_t in_width = in_dims[1];
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auto& in_lod = in->lod();
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PADDLE_ENFORCE_EQ(in_lod.size(), 1UL,
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"Only support one level sequence now.");
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PADDLE_ENFORCE_EQ(
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in_dims[0], in_lod[0].back(),
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"Inconsistent size between X.shape[0] and X.lod()[0].back().");
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auto in_lod_l0 = in_lod[0];
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int seq_num = in_lod_l0.size() - 1;
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if (in_width == out_width) {
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out->set_lod(in->lod());
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} else {
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auto& out_lod = *out->mutable_lod();
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out_lod.resize(1);
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out_lod[0].resize(seq_num + 1);
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out_lod[0][0] = 0;
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for (int i = 0; i < seq_num; ++i) {
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size_t seq_len = in_lod_l0[i + 1] - in_lod_l0[i];
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size_t offset = 0;
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offset = (seq_len * in_width) / out_width;
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PADDLE_ENFORCE_EQ(offset * out_width, seq_len * in_width,
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"Please make sure (sequence_length * dimension) can "
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"be divided by new_dim with no remainder for each "
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"sequence. The %dth sequence is invalid.",
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i + 1);
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out_lod[0][i + 1] = out_lod[0][i] + offset;
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}
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}
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framework::Copy(*in, context.GetPlace(), out);
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out->Resize({static_cast<int64_t>(out->lod()[0].back()), out_width});
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}
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};
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template <typename DeviceContext, typename T>
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class SequenceReshapeGradKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* x_tensor_ptr = context.Input<LoDTensor>("X");
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auto* outg_tensor_ptr =
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context.Input<LoDTensor>(framework::GradVarName("Out"));
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auto* xg_tensor_ptr =
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context.Output<LoDTensor>(framework::GradVarName("X"));
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xg_tensor_ptr->mutable_data<T>(context.GetPlace());
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framework::Copy(*outg_tensor_ptr, context.GetPlace(), xg_tensor_ptr);
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xg_tensor_ptr->Resize(x_tensor_ptr->dims());
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}
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};
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} // namespace operators
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} // namespace paddle
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