m53297601
/
Paddle
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Adding L1 norm op for L1 regularization (#5058)

Browse Source 
* Adding L1 norm op for L1 regularization

* Addressing code review feedback

* Address code review feedback

* Change variable names to match google style guide
fix-typo
Abhinav Arora 8 years ago committed by GitHub
parent 9596731348
commit 94fb7ba4fa
4 changed files with 188 additions and 0 deletions
Show Stats Download Patch File Download Diff File

75
paddle/operators/l1_norm_op.cc
Unescape View File

@ -0,0 +1,75 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#include "paddle/operators/l1_norm_op.h"
namespace paddle {
namespace operators {
using framework::Tensor;
class L1NormOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should be not null.");
PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should be not null.");
ctx->SetOutputDim("Out", {1});
}
};
class L1NormGradOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should be not null.");
PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
"Input(Out@GRAD) should be not null.");
PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("X")),
"Output(X@GRAD) should be not null.");
ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X"));
}
};
class L1NormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
L1NormOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("X", "(Tensor) The input of l1_norm op.");
AddOutput("Out", "(Scalar) The output of l1_norm op.");
AddComment(R"DOC(
L1 Norm Operator.
Computes the L1 norm of a tensor.
Out = sum (abs(X))
)DOC");
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OP(l1_norm, ops::L1NormOp, ops::L1NormOpMaker, l1_norm_grad,
ops::L1NormGradOp);
REGISTER_OP_CPU_KERNEL(l1_norm,
ops::L1NormKernel<paddle::platform::CPUPlace, float>);
REGISTER_OP_CPU_KERNEL(
l1_norm_grad, ops::L1NormGradKernel<paddle::platform::CPUPlace, float>);

22
paddle/operators/l1_norm_op.cu
Unescape View File

@ -0,0 +1,22 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#define EIGEN_USE_GPU
#include "paddle/operators/l1_norm_op.h"
namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(l1_norm,
ops::L1NormKernel<paddle::platform::GPUPlace, float>);
REGISTER_OP_GPU_KERNEL(
l1_norm_grad, ops::L1NormGradKernel<paddle::platform::GPUPlace, float>);

63
paddle/operators/l1_norm_op.h
Unescape View File

@ -0,0 +1,63 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/framework/eigen.h"
#include "paddle/framework/op_registry.h"
namespace paddle {
namespace operators {
// Out = sum(abs(X))
template <typename Place, typename T>
class L1NormKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &context) const override {
const framework::Tensor *X = context.Input<framework::Tensor>("X");
framework::Tensor *Out = context.Output<framework::Tensor>("Out");
Out->mutable_data<T>(context.GetPlace());
auto x = framework::EigenVector<T>::Flatten(*X);
auto out = framework::EigenVector<T>::Flatten(*Out);
auto place = context.GetEigenDevice<Place>();
out.device(place) = x.abs().sum();
}
};
// dX = dout * sign(X)
template <typename Place, typename T>
class L1NormGradKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &context) const override {
const framework::Tensor *x = context.Input<framework::Tensor>("X");
const framework::Tensor *d_out =
context.Input<framework::Tensor>(framework::GradVarName("Out"));
PADDLE_ENFORCE(d_out->numel() == 1, "L1 Norm Gradient should be scalar");
framework::Tensor *dx =
context.Output<framework::Tensor>(framework::GradVarName("X"));
dx->mutable_data<T>(context.GetPlace());
auto x_eigen = framework::EigenVector<T>::Flatten(*x);
auto d_out_eigen = framework::EigenVector<T>::Flatten(*d_out);
auto dx_eigen = framework::EigenVector<T>::Flatten(*dx);
auto place = context.GetEigenDevice<Place>();
Eigen::DSizes<int, 1> x_dsize(x->numel());
dx_eigen.device(place) = d_out_eigen.broadcast(x_dsize) * x_eigen.sign();
}
};
} // namespace operators
} // namespace paddle

28
python/paddle/v2/framework/tests/test_l1_norm_op.py
Unescape View File

@ -0,0 +1,28 @@
import numpy as np
import unittest
from op_test import OpTest
class TestL1NormOp(OpTest):
"""Test l1_norm
"""
def setUp(self):
self.op_type = "l1_norm"
self.max_relative_error = 0.005
X = np.random.uniform(-1, 1, (13, 19)).astype("float32")
X[np.abs(X) < self.max_relative_error] = 0.1
self.inputs = {'X': X}
self.outputs = {'Out': np.sum(np.abs(X))}
def test_check_output(self):
self.check_output()
def test_check_grad(self):
self.check_grad(
['X'], 'Out', max_relative_error=self.max_relative_error)
if __name__ == "__main__":
unittest.main()
Write Preview
Loading…
Cancel
Save