From e0a2d4dfec0aa58d943f9d20efb462fb83380ce1 Mon Sep 17 00:00:00 2001 From: danleifeng <52735331+danleifeng@users.noreply.github.com> Date: Tue, 30 Jul 2019 15:29:01 +0800 Subject: [PATCH] Add elementwise_pow_op backward implementation and the unit test codes of it. (#18848) --- .../elementwise/elementwise_pow_op.cc | 39 ++++++++-- .../elementwise/elementwise_pow_op.cu | 11 ++- .../elementwise/elementwise_pow_op.h | 41 +++++++++-- .../unittests/test_elementwise_pow_op.py | 71 +++++++++++++++++-- 4 files changed, 146 insertions(+), 16 deletions(-) diff --git a/paddle/fluid/operators/elementwise/elementwise_pow_op.cc b/paddle/fluid/operators/elementwise/elementwise_pow_op.cc index 6335e67a8a..59ec9a2d4a 100644 --- a/paddle/fluid/operators/elementwise/elementwise_pow_op.cc +++ b/paddle/fluid/operators/elementwise/elementwise_pow_op.cc @@ -1,11 +1,8 @@ /* 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. @@ -13,11 +10,30 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/operators/elementwise/elementwise_pow_op.h" +#include #include #include "paddle/fluid/operators/elementwise/elementwise_op.h" namespace paddle { namespace operators { + +class ElementwisePowOpGradDescMaker : public framework::SingleGradOpDescMaker { + public: + using framework::SingleGradOpDescMaker::SingleGradOpDescMaker; + + protected: + std::unique_ptr Apply() const override { + std::unique_ptr op(new framework::OpDesc()); + op->SetType("elementwise_pow_grad"); + op->SetInput("X", Input("X")); + op->SetInput("Y", Input("Y")); + op->SetInput(framework::GradVarName("Out"), OutputGrad("Out")); + op->SetAttrMap(Attrs()); + op->SetOutput(framework::GradVarName("X"), InputGrad("X")); + op->SetOutput(framework::GradVarName("Y"), InputGrad("Y")); + return op; + } +}; class ElementwisePowOpMaker : public ElementwiseOpMaker { protected: std::string GetName() const override { return "Pow"; } @@ -27,9 +43,20 @@ class ElementwisePowOpMaker : public ElementwiseOpMaker { } // namespace paddle namespace ops = paddle::operators; -REGISTER_OP_WITHOUT_GRADIENT(elementwise_pow, ops::ElementwiseOp, - ops::ElementwisePowOpMaker); +REGISTER_OPERATOR(elementwise_pow, ops::ElementwiseOp, + ops::ElementwisePowOpMaker, ops::ElementwiseOpInferVarType, + ops::ElementwisePowOpGradDescMaker); +REGISTER_OPERATOR(elementwise_pow_grad, ops::ElementwiseOpGrad); + REGISTER_OP_CPU_KERNEL( elementwise_pow, ops::ElementwisePowKernel, - ops::ElementwisePowKernel); + ops::ElementwisePowKernel, + ops::ElementwisePowKernel, + ops::ElementwisePowKernel); +REGISTER_OP_CPU_KERNEL( + elementwise_pow_grad, + ops::ElementwisePowGradKernel, + ops::ElementwisePowGradKernel, + ops::ElementwisePowGradKernel, + ops::ElementwisePowGradKernel); diff --git a/paddle/fluid/operators/elementwise/elementwise_pow_op.cu b/paddle/fluid/operators/elementwise/elementwise_pow_op.cu index 9263dbfebf..320d1e7b38 100644 --- a/paddle/fluid/operators/elementwise/elementwise_pow_op.cu +++ b/paddle/fluid/operators/elementwise/elementwise_pow_op.cu @@ -15,4 +15,13 @@ namespace ops = paddle::operators; REGISTER_OP_CUDA_KERNEL( elementwise_pow, ops::ElementwisePowKernel, - ops::ElementwisePowKernel); + ops::ElementwisePowKernel, + ops::ElementwisePowKernel, + ops::ElementwisePowKernel); +REGISTER_OP_CUDA_KERNEL( + elementwise_pow_grad, + ops::ElementwisePowGradKernel, + ops::ElementwisePowGradKernel, + ops::ElementwisePowGradKernel, + ops::ElementwisePowGradKernel); diff --git a/paddle/fluid/operators/elementwise/elementwise_pow_op.h b/paddle/fluid/operators/elementwise/elementwise_pow_op.h index dc584b4c32..1363485ced 100644 --- a/paddle/fluid/operators/elementwise/elementwise_pow_op.h +++ b/paddle/fluid/operators/elementwise/elementwise_pow_op.h @@ -1,11 +1,8 @@ /* 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. @@ -15,6 +12,7 @@ limitations under the License. */ #pragma once #include +#include "paddle/fluid/operators/elementwise/elementwise_op.h" #include "paddle/fluid/operators/elementwise/elementwise_op_function.h" namespace paddle { @@ -29,9 +27,11 @@ template class ElementwisePowKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { - using Tensor = framework::Tensor; - + using Tensor = framework::LoDTensor; auto* x = ctx.Input("X"); + PADDLE_ENFORCE(x != nullptr, + "Cannot get input Variable X, variable name = %s", + ctx.op().Input("X")); auto* y = ctx.Input("Y"); auto* z = ctx.Output("Out"); z->mutable_data(ctx.GetPlace()); @@ -41,5 +41,36 @@ class ElementwisePowKernel : public framework::OpKernel { } }; +template +struct PowGradDX { + HOSTDEVICE T operator()(T x, T y, T out, T dout) const { + return dout * y * std::pow(x, y - 1); + } +}; + +template +struct PowGradDY { + HOSTDEVICE T operator()(T x, T y, T out, T dout) const { + return dout * std::log(x) * std::pow(x, y); + } +}; + +template +class ElementwisePowGradKernel : public ElemwiseGradKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + ElemwiseGradKernel::Compute(ctx); + using Tensor = framework::Tensor; + auto* x = ctx.Input("X"); + auto* y = ctx.Input("Y"); + auto* dout = ctx.Input(framework::GradVarName("Out")); + auto* out = dout; + auto* dx = ctx.Output(framework::GradVarName("X")); + auto* dy = ctx.Output(framework::GradVarName("Y")); + int axis = ctx.Attr("axis"); + ElemwiseGradCompute, PowGradDY>( + ctx, *x, *y, *out, *dout, axis, dx, dy, PowGradDX(), PowGradDY()); + } +}; } // namespace operators } // namespace paddle diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_pow_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_pow_op.py index 7bf642f03f..0b0c7c5ecb 100644 --- a/python/paddle/fluid/tests/unittests/test_elementwise_pow_op.py +++ b/python/paddle/fluid/tests/unittests/test_elementwise_pow_op.py @@ -22,24 +22,87 @@ class TestElementwisePowOp(OpTest): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.uniform(0.1, 1, [13, 17]).astype("float32"), - 'Y': np.random.uniform(0.1, 1, [13, 17]).astype("float32") + 'X': np.random.uniform(0.1, 1, [2, 3]).astype("float32"), + 'Y': np.random.uniform(0.1, 1, [2, 3]).astype("float32") } self.outputs = {'Out': np.power(self.inputs['X'], self.inputs['Y'])} def test_check_output(self): self.check_output() + def test_check_grad_normal(self): + self.check_grad(['X', 'Y'], 'Out') + class TestElementwisePowOp_scalar(TestElementwisePowOp): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.rand(2, 3, 4).astype('float32'), - 'Y': np.random.rand(1).astype('float32') + 'X': np.random.uniform(0.1, 1, [3, 3, 4]).astype(np.float32), + 'Y': np.random.uniform(0.1, 1, [1]).astype(np.float32) + } + self.outputs = {'Out': np.power(self.inputs['X'], self.inputs['Y'])} + + +class TestElementwisePowOp_tensor(TestElementwisePowOp): + def setUp(self): + self.op_type = "elementwise_pow" + self.inputs = { + 'X': np.random.uniform(0.1, 1, [32]).astype("float32"), + 'Y': np.random.uniform(0.1, 1, [32]).astype("float32") + } + self.outputs = {'Out': np.power(self.inputs['X'], self.inputs['Y'])} + + +class TestElementwisePowOp_broadcast_0(TestElementwisePowOp): + def setUp(self): + self.op_type = "elementwise_pow" + self.inputs = { + 'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"), + 'Y': np.random.uniform(0.1, 1, [4]).astype("float32") } self.outputs = {'Out': np.power(self.inputs['X'], self.inputs['Y'])} +class TestElementwisePowOp_broadcast_1(TestElementwisePowOp): + def setUp(self): + self.op_type = "elementwise_pow" + self.inputs = { + 'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"), + 'Y': np.random.uniform(0.1, 1, [3]).astype("float32") + } + self.attrs = {'axis': 1} + self.outputs = { + 'Out': np.power(self.inputs['X'], self.inputs['Y'].reshape(3, 1)) + } + + +class TestElementwisePowOp_broadcast_2(TestElementwisePowOp): + def setUp(self): + self.op_type = "elementwise_pow" + self.inputs = { + 'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"), + 'Y': np.random.uniform(0.1, 1, [2]).astype("float32") + } + self.attrs = {'axis': 0} + self.outputs = { + 'Out': np.power(self.inputs['X'], self.inputs['Y'].reshape(2, 1, 1)) + } + + +class TestElementwisePowOp_broadcast_3(TestElementwisePowOp): + def setUp(self): + self.op_type = "elementwise_pow" + self.inputs = { + 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float32"), + 'Y': np.random.uniform(0.1, 1, [3, 4]).astype("float32") + } + self.attrs = {'axis': 1} + self.outputs = { + 'Out': np.power(self.inputs['X'], self.inputs['Y'].reshape(1, 3, 4, + 1)) + } + + if __name__ == '__main__': unittest.main() -- GitLab