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JiayiFengJiayiFeng
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Merge pull request #11223 from JiayiFeng/dev_reverse_op
Add reverse op
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‎paddle/fluid/operators/reverse_op.cc

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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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#include "paddle/fluid/operators/reverse_op.h"
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#include <vector>
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namespace paddle {
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namespace operators {
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class ReverseOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
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PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null");
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const auto& x_dims = ctx->GetInputDim("X");
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const auto& axis = ctx->Attrs().Get<std::vector<int>>("axis");
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PADDLE_ENFORCE(!axis.empty(), "'axis' can not be empty.");
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for (int a : axis) {
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PADDLE_ENFORCE_LT(a, x_dims.size(),
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"The axis must be less than input tensor's rank.");
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}
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ctx->SetOutputDim("Out", x_dims);
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}
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};
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class ReverseOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "The LoDTensor to be flipped.");
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AddOutput("Out", "The LoDTensor after flipping.");
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AddAttr<std::vector<int>>(
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"axis", "The axises that along which order of elements is reversed.");
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AddComment(R"DOC(
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Reverse Operator.
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Reverse the order of elements in the input LoDTensor along given axises.
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Case 1:
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Given
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X = [[1, 2, 3, 4, 5]
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[6, 7, 8, 9, 10]
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[11, 12, 13, 14, 15]],
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and
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axis = [0],
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we get:
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Out = [[11, 12, 13, 14, 15]
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[6, 7, 8, 9, 10]
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[1, 2, 3, 4, 5]].
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Case 2:
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Given
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X = [[[1, 2, 3, 4]
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[5, 6, 7, 8]]
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[[9, 10, 11, 12]
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[13, 14, 15, 16]]],
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and
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axis = [0, 2],
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we get:
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Out = [[[12, 11, 10, 9]
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[16, 15, 14, 13]]
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[[4, 3, 2, 1]
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[8, 7, 6, 5]]],
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)DOC");
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}
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};
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class ReverseGradMaker : public framework::SingleGradOpDescMaker {
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public:
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using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
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std::unique_ptr<framework::OpDesc> Apply() const override {
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auto* grad_op = new framework::OpDesc();
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grad_op->SetType("reverse");
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grad_op->SetInput("X", OutputGrad("Out"));
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grad_op->SetOutput("Out", InputGrad("X"));
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grad_op->SetAttr("axis", GetAttr("axis"));
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return std::unique_ptr<framework::OpDesc>(grad_op);
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OPERATOR(reverse, ops::ReverseOp, ops::ReverseOpMaker,
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ops::ReverseGradMaker);
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REGISTER_OPERATOR(reverse_grad, ops::ReverseOp);
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REGISTER_OP_CPU_KERNEL(
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reverse, ops::ReverseKernel<paddle::platform::CPUDeviceContext, int>,
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ops::ReverseKernel<paddle::platform::CPUDeviceContext, uint8_t>,
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ops::ReverseKernel<paddle::platform::CPUDeviceContext, int64_t>,
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ops::ReverseKernel<paddle::platform::CPUDeviceContext, bool>,
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ops::ReverseKernel<paddle::platform::CPUDeviceContext, float>,
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ops::ReverseKernel<paddle::platform::CPUDeviceContext, double>)

‎paddle/fluid/operators/reverse_op.cu

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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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#include "paddle/fluid/operators/reverse_op.h"
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namespace ops = paddle::operators;
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REGISTER_OP_CUDA_KERNEL(
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reverse, ops::ReverseKernel<paddle::platform::CUDADeviceContext, int>,
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ops::ReverseKernel<paddle::platform::CUDADeviceContext, uint8_t>,
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ops::ReverseKernel<paddle::platform::CUDADeviceContext, int64_t>,
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ops::ReverseKernel<paddle::platform::CUDADeviceContext, bool>,
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ops::ReverseKernel<paddle::platform::CUDADeviceContext, float>,
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ops::ReverseKernel<paddle::platform::CUDADeviceContext, double>)

‎paddle/fluid/operators/reverse_op.h

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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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 <vector>
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#include "paddle/fluid/framework/eigen.h"
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T, int Rank>
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struct ReverseFunctor {
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void operator()(const DeviceContext& context, const framework::LoDTensor& in,
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framework::LoDTensor* out, const std::vector<int>& axis) {
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Eigen::array<bool, Rank> reverse_axis;
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for (int i = 0; i < Rank; ++i) {
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reverse_axis[i] = false;
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}
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for (int a : axis) {
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reverse_axis[a] = true;
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}
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auto in_eigen = framework::EigenTensor<T, Rank>::From(in);
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auto out_eigen = framework::EigenTensor<T, Rank>::From(*out);
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auto* dev = context.eigen_device();
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out_eigen.device(*dev) = in_eigen.reverse(reverse_axis);
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}
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};
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template <typename DeviceContext, typename T>
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class ReverseKernel : 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 = context.Input<framework::LoDTensor>("X");
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auto* out = context.Output<framework::LoDTensor>("Out");
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out->mutable_data<T>(context.GetPlace());
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const auto& axis = context.Attr<std::vector<int>>("axis");
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int rank = x->dims().size();
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auto& dev_ctx = context.template device_context<DeviceContext>();
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switch (rank) {
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case 1:
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ReverseFunctor<DeviceContext, T, 1> functor1;
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functor1(dev_ctx, *x, out, axis);
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break;
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case 2:
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ReverseFunctor<DeviceContext, T, 2> functor2;
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functor2(dev_ctx, *x, out, axis);
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break;
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case 3:
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ReverseFunctor<DeviceContext, T, 3> functor3;
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functor3(dev_ctx, *x, out, axis);
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break;
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case 4:
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ReverseFunctor<DeviceContext, T, 4> functor4;
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functor4(dev_ctx, *x, out, axis);
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break;
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case 5:
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ReverseFunctor<DeviceContext, T, 5> functor5;
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functor5(dev_ctx, *x, out, axis);
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break;
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case 6:
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ReverseFunctor<DeviceContext, T, 6> functor6;
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functor6(dev_ctx, *x, out, axis);
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break;
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default:
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PADDLE_THROW(
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"Reserve operator doesn't supports tensors whose ranks are greater "
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"than 6.");
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}
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}
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};
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} // namespace operators
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} // namespace paddle

‎python/paddle/fluid/layers/tensor.py

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return fill_constant(value=0.0, **locals())
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def reverse(x, axis):
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"""
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**reverse**
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This function reverse the input 'x' along given axises.
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Args:
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x(Vairbale): the input to be reversed.
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axis(int|tuple|list): Axis that along which order of elements
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is reversed. If it is a tuple or a list, reversing
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will be apply on each axis in the tuple or list.
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Returns:
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Variable: The reversed tensor.
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Examples:
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.. code-block:: python
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out = fluid.layers.reverse(x=in, axis=0)
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# or:
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out = fluid.layers.reverse(x=in, axis=[0,1])
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"""
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if isinstance(axis, int):
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axis = [axis]
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helper = LayerHelper("reverse", **locals())
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out = helper.create_tmp_variable(dtype=x.dtype)
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helper.append_op(
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type='reverse',
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inputs={'Input': x},
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outputs={'Out': [out]},
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attrs={'axis': axis})
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return out
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def save(x, file_path, overwrite=True):
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"""
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Saves a variable as a file.

‎python/paddle/fluid/tests/unittests/test_reverse_op.py

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# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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import unittest
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import numpy as np
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from op_test import OpTest
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class TestReverseOp(OpTest):
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def initTestCase(self):
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self.x = np.random.random((3, 4)).astype('float32')
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self.axis = [0]
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def setUp(self):
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self.initTestCase()
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self.op_type = "reverse"
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self.inputs = {"X": self.x}
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self.attrs = {'axis': self.axis}
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out = self.x
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for a in self.axis:
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out = np.flip(out, axis=a)
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self.outputs = {'Out': out}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(['X'], 'Out')
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class TestCase0(TestReverseOp):
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def initTestCase(self):
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self.x = np.random.random((3, 4)).astype('float32')
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self.axis = [1]
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class TestCase1(TestReverseOp):
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def initTestCase(self):
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self.x = np.random.random((3, 4)).astype('float32')
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self.axis = [0, 1]
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class TestCase2(TestReverseOp):
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def initTestCase(self):
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self.x = np.random.random((3, 4, 5)).astype('float32')
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self.axis = [0, 2]
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class TestCase3(TestReverseOp):
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def initTestCase(self):
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self.x = np.random.random((3, 4, 5)).astype('float32')
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self.axis = [1, 2]
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if __name__ == '__main__':
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unittest.main()

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