未验证 提交 65a94be1 编写于 作者: F fengjiayi 提交者: GitHub

Merge pull request #11223 from JiayiFeng/dev_reverse_op

Add reverse op
// 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.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/fluid/operators/reverse_op.h"
#include <vector>
namespace paddle {
namespace operators {
class ReverseOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null");
const auto& x_dims = ctx->GetInputDim("X");
const auto& axis = ctx->Attrs().Get<std::vector<int>>("axis");
PADDLE_ENFORCE(!axis.empty(), "'axis' can not be empty.");
for (int a : axis) {
PADDLE_ENFORCE_LT(a, x_dims.size(),
"The axis must be less than input tensor's rank.");
}
ctx->SetOutputDim("Out", x_dims);
}
};
class ReverseOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
AddInput("X", "The LoDTensor to be flipped.");
AddOutput("Out", "The LoDTensor after flipping.");
AddAttr<std::vector<int>>(
"axis", "The axises that along which order of elements is reversed.");
AddComment(R"DOC(
Reverse Operator.
Reverse the order of elements in the input LoDTensor along given axises.
Case 1:
Given
X = [[1, 2, 3, 4, 5]
[6, 7, 8, 9, 10]
[11, 12, 13, 14, 15]],
and
axis = [0],
we get:
Out = [[11, 12, 13, 14, 15]
[6, 7, 8, 9, 10]
[1, 2, 3, 4, 5]].
Case 2:
Given
X = [[[1, 2, 3, 4]
[5, 6, 7, 8]]
[[9, 10, 11, 12]
[13, 14, 15, 16]]],
and
axis = [0, 2],
we get:
Out = [[[12, 11, 10, 9]
[16, 15, 14, 13]]
[[4, 3, 2, 1]
[8, 7, 6, 5]]],
)DOC");
}
};
class ReverseGradMaker : public framework::SingleGradOpDescMaker {
public:
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
std::unique_ptr<framework::OpDesc> Apply() const override {
auto* grad_op = new framework::OpDesc();
grad_op->SetType("reverse");
grad_op->SetInput("X", OutputGrad("Out"));
grad_op->SetOutput("Out", InputGrad("X"));
grad_op->SetAttr("axis", GetAttr("axis"));
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(reverse, ops::ReverseOp, ops::ReverseOpMaker,
ops::ReverseGradMaker);
REGISTER_OPERATOR(reverse_grad, ops::ReverseOp);
REGISTER_OP_CPU_KERNEL(
reverse, ops::ReverseKernel<paddle::platform::CPUDeviceContext, int>,
ops::ReverseKernel<paddle::platform::CPUDeviceContext, uint8_t>,
ops::ReverseKernel<paddle::platform::CPUDeviceContext, int64_t>,
ops::ReverseKernel<paddle::platform::CPUDeviceContext, bool>,
ops::ReverseKernel<paddle::platform::CPUDeviceContext, float>,
ops::ReverseKernel<paddle::platform::CPUDeviceContext, double>)
// 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.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/fluid/operators/reverse_op.h"
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(
reverse, ops::ReverseKernel<paddle::platform::CUDADeviceContext, int>,
ops::ReverseKernel<paddle::platform::CUDADeviceContext, uint8_t>,
ops::ReverseKernel<paddle::platform::CUDADeviceContext, int64_t>,
ops::ReverseKernel<paddle::platform::CUDADeviceContext, bool>,
ops::ReverseKernel<paddle::platform::CUDADeviceContext, float>,
ops::ReverseKernel<paddle::platform::CUDADeviceContext, double>)
// 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.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
namespace paddle {
namespace operators {
template <typename DeviceContext, typename T, int Rank>
struct ReverseFunctor {
void operator()(const DeviceContext& context, const framework::LoDTensor& in,
framework::LoDTensor* out, const std::vector<int>& axis) {
Eigen::array<bool, Rank> reverse_axis;
for (int i = 0; i < Rank; ++i) {
reverse_axis[i] = false;
}
for (int a : axis) {
reverse_axis[a] = true;
}
auto in_eigen = framework::EigenTensor<T, Rank>::From(in);
auto out_eigen = framework::EigenTensor<T, Rank>::From(*out);
auto* dev = context.eigen_device();
out_eigen.device(*dev) = in_eigen.reverse(reverse_axis);
}
};
template <typename DeviceContext, typename T>
class ReverseKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
auto* x = context.Input<framework::LoDTensor>("X");
auto* out = context.Output<framework::LoDTensor>("Out");
out->mutable_data<T>(context.GetPlace());
const auto& axis = context.Attr<std::vector<int>>("axis");
int rank = x->dims().size();
auto& dev_ctx = context.template device_context<DeviceContext>();
switch (rank) {
case 1:
ReverseFunctor<DeviceContext, T, 1> functor1;
functor1(dev_ctx, *x, out, axis);
break;
case 2:
ReverseFunctor<DeviceContext, T, 2> functor2;
functor2(dev_ctx, *x, out, axis);
break;
case 3:
ReverseFunctor<DeviceContext, T, 3> functor3;
functor3(dev_ctx, *x, out, axis);
break;
case 4:
ReverseFunctor<DeviceContext, T, 4> functor4;
functor4(dev_ctx, *x, out, axis);
break;
case 5:
ReverseFunctor<DeviceContext, T, 5> functor5;
functor5(dev_ctx, *x, out, axis);
break;
case 6:
ReverseFunctor<DeviceContext, T, 6> functor6;
functor6(dev_ctx, *x, out, axis);
break;
default:
PADDLE_THROW(
"Reserve operator doesn't supports tensors whose ranks are greater "
"than 6.");
}
}
};
} // namespace operators
} // namespace paddle
......@@ -363,6 +363,40 @@ def zeros(shape, dtype, force_cpu=False):
return fill_constant(value=0.0, **locals())
def reverse(x, axis):
"""
**reverse**
This function reverse the input 'x' along given axises.
Args:
x(Vairbale): the input to be reversed.
axis(int|tuple|list): Axis that along which order of elements
is reversed. If it is a tuple or a list, reversing
will be apply on each axis in the tuple or list.
Returns:
Variable: The reversed tensor.
Examples:
.. code-block:: python
out = fluid.layers.reverse(x=in, axis=0)
# or:
out = fluid.layers.reverse(x=in, axis=[0,1])
"""
if isinstance(axis, int):
axis = [axis]
helper = LayerHelper("reverse", **locals())
out = helper.create_tmp_variable(dtype=x.dtype)
helper.append_op(
type='reverse',
inputs={'Input': x},
outputs={'Out': [out]},
attrs={'axis': axis})
return out
def save(x, file_path, overwrite=True):
"""
Saves a variable as a file.
......
# 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.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest
import numpy as np
from op_test import OpTest
class TestReverseOp(OpTest):
def initTestCase(self):
self.x = np.random.random((3, 4)).astype('float32')
self.axis = [0]
def setUp(self):
self.initTestCase()
self.op_type = "reverse"
self.inputs = {"X": self.x}
self.attrs = {'axis': self.axis}
out = self.x
for a in self.axis:
out = np.flip(out, axis=a)
self.outputs = {'Out': out}
def test_check_output(self):
self.check_output()
def test_check_grad(self):
self.check_grad(['X'], 'Out')
class TestCase0(TestReverseOp):
def initTestCase(self):
self.x = np.random.random((3, 4)).astype('float32')
self.axis = [1]
class TestCase1(TestReverseOp):
def initTestCase(self):
self.x = np.random.random((3, 4)).astype('float32')
self.axis = [0, 1]
class TestCase2(TestReverseOp):
def initTestCase(self):
self.x = np.random.random((3, 4, 5)).astype('float32')
self.axis = [0, 2]
class TestCase3(TestReverseOp):
def initTestCase(self):
self.x = np.random.random((3, 4, 5)).astype('float32')
self.axis = [1, 2]
if __name__ == '__main__':
unittest.main()
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