Merge pull request #3634 from reyoung/feature/minus_op
Feature/minus oprevert-3824-remove_grad_op_type
commit
11f4283f09
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/* Copyright (c) 2016 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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#include "paddle/operators/minus_op.h"
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#include "paddle/operators/net_op.h"
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namespace paddle {
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namespace operators {
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class MinusOp : public framework::OperatorWithKernel {
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public:
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MinusOp(const std::string &type, const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: OperatorWithKernel(type, inputs, outputs, attrs) {}
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protected:
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void InferShape(const framework::InferShapeContext &ctx) const override {
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auto *left_tensor = ctx.Input<framework::Tensor>("X");
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auto *right_tensor = ctx.Input<framework::Tensor>("Y");
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PADDLE_ENFORCE_EQ(
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framework::product(left_tensor->dims()),
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framework::product(right_tensor->dims()),
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"Minus operator must take two tensor with same num of elements");
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ctx.Output<framework::Tensor>("Out")->Resize(left_tensor->dims());
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}
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};
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class MinusOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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MinusOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "The left tensor of minus operator.").NotInGradient();
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AddInput("Y", "The right tensor of minus operator.").NotInGradient();
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AddOutput("Out", "The output tensor of minus operator.").NotInGradient();
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AddComment(R"DOC(Minus Operator
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Equation: Out = X - Y
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)DOC");
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}
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};
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template <typename AttrType>
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class MinusGradOp : public NetOp {
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public:
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MinusGradOp(const std::string &type, const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: NetOp(type, inputs, outputs, attrs) {
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auto out_grad = Input(framework::GradVarName("Out"));
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auto x_grad = Output(framework::GradVarName("X"));
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auto y_grad = Output(framework::GradVarName("Y"));
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// x_grad = out_grad
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AppendOp(framework::OpRegistry::CreateOp("identity", {{"X", {out_grad}}},
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{{"Out", {x_grad}}}, {}));
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framework::AttributeMap scale_attr;
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scale_attr["scale"] = static_cast<AttrType>(-1);
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AppendOp(framework::OpRegistry::CreateOp("scale", {{"X", {out_grad}}},
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{{"Out", {y_grad}}}, scale_attr));
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CompleteAddOp(false);
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}
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};
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} // namespace operators
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} // namespace paddle
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USE_OP(scale);
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USE_OP_ITSELF(identity);
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namespace ops = paddle::operators;
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REGISTER_OP(minus, ops::MinusOp, ops::MinusOpMaker, minus_grad,
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ops::MinusGradOp<float>);
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REGISTER_OP_CPU_KERNEL(minus,
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ops::MinusKernel<paddle::platform::CPUPlace, float>);
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/* Copyright (c) 2016 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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#include "paddle/operators/minus_op.h"
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REGISTER_OP_GPU_KERNEL(
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minus, paddle::operators::MinusKernel<paddle::platform::GPUPlace, float>);
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@ -0,0 +1,39 @@
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/* Copyright (c) 2016 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/eigen.h"
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#include "paddle/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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template <typename Place, typename T>
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class MinusKernel : public framework::OpKernel {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* left_tensor = context.Input<framework::Tensor>("X");
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auto* right_tensor = context.Input<framework::Tensor>("Y");
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auto* out_tensor = context.Output<framework::Tensor>("Out");
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out_tensor->mutable_data<T>(context.GetPlace());
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auto& dev = context.GetEigenDevice<Place>();
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framework::EigenVector<T>::Flatten(*out_tensor).device(dev) =
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framework::EigenVector<T>::Flatten(*left_tensor) -
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framework::EigenVector<T>::Flatten(*right_tensor);
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}
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};
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} // namespace operators
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} // namespace paddle
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import unittest
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import numpy as np
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from gradient_checker import GradientChecker, create_op
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from op_test_util import OpTestMeta
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class MinusOpTest(unittest.TestCase):
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__metaclass__ = OpTestMeta
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def setUp(self):
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self.type = "minus"
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self.inputs = {
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'X': np.random.random((32, 84)).astype("float32"),
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'Y': np.random.random((32, 84)).astype("float32")
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}
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self.outputs = {'Out': (self.inputs['X'] - self.inputs['Y'])}
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class MinusGradTest(GradientChecker):
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def test_left(self):
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op = create_op("minus")
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inputs = {
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"X": np.random.random((10, 10)).astype("float32"),
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"Y": np.random.random((10, 10)).astype("float32")
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}
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self.check_grad(op, inputs, ["X", 'Y'], "Out")
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if __name__ == '__main__':
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unittest.main()
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