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cpu/gpu mean op and its unit test #3135
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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"); | ||
you may not use this file except in compliance with the License. | ||
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 | ||
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. */ | ||
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#include "paddle/operators/mean_op.h" | ||
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namespace paddle { | ||
namespace operators { | ||
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class MeanOp : public OperatorWithKernel { | ||
protected: | ||
void InferShape(const InferShapeContext &ctx) const override { | ||
PADDLE_ENFORCE(ctx.InputSize() == 1, "Input size of AddOp must be one"); | ||
PADDLE_ENFORCE(ctx.OutputSize() == 1, "Output size of AddOp must be one"); | ||
PADDLE_ENFORCE(ctx.InputVar(0) != nullptr && ctx.OutputVar(0) != nullptr, | ||
"Input/Output of MeanOp must be initialized."); | ||
ctx.Output<Tensor>(0)->Resize(framework::make_ddim({1})); | ||
} | ||
}; | ||
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class MeanOpMaker : public OpProtoAndCheckerMaker { | ||
public: | ||
MeanOpMaker(OpProto *proto, OpAttrChecker *op_checker) | ||
: OpProtoAndCheckerMaker(proto, op_checker) { | ||
AddInput("X", "The input of mean op"); | ||
AddOutput("Out", "The output of mean op"); | ||
AddComment("Mean Operator"); | ||
} | ||
}; | ||
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} // namespace operators | ||
} // namespace paddle | ||
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REGISTER_OP(mean, ops::MeanOp, ops::MeanOpMaker); | ||
REGISTER_OP_CPU_KERNEL(mean, ops::MeanKernel<ops::CPUPlace, float>); |
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#define EIGEN_USE_GPU | ||
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#include "paddle/operators/mean_op.h" | ||
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REGISTER_OP_GPU_KERNEL(mean, ops::MeanKernel<ops::GPUPlace, 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"); | ||
you may not use this file except in compliance with the License. | ||
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 | ||
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. */ | ||
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#pragma once | ||
#include "paddle/operators/type_alias.h" | ||
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namespace paddle { | ||
namespace operators { | ||
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template <typename Place, typename T> | ||
class MeanKernel : public OpKernel { | ||
public: | ||
void Compute(const ExecutionContext& context) const override { | ||
auto input = context.Input<Tensor>(0); | ||
auto output = context.Output<Tensor>(0); | ||
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output->mutable_data<T>(context.GetPlace()); | ||
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EigenScalar<T>::From(*output).device(*(context.GetEigenDevice<Place>())) = | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Tensor2Eigen still not easy to w/r. |
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EigenVector<T>::Flatten(*input).mean(); | ||
} | ||
}; | ||
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} // namespace operators | ||
} // namespace paddle |
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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"); | ||
you may not use this file except in compliance with the License. | ||
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 | ||
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. */ | ||
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#include <gtest/gtest.h> | ||
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#include <paddle/framework/op_registry.h> | ||
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USE_OP(mean); | ||
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TEST(MeanOp, GetOpProto) { | ||
auto& protos = paddle::framework::OpRegistry::protos(); | ||
auto it = protos.find("mean"); | ||
ASSERT_NE(it, protos.end()); | ||
} |
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cc_library(paddle_pybind SHARED SRCS pybind.cc DEPS pybind python | ||
add_op fc_op sgd_op cross_entropy_op recurrent_network_op) | ||
cc_library(paddle_pybind SHARED | ||
SRCS pybind.cc | ||
DEPS pybind python | ||
fc_op | ||
sgd_op | ||
add_op | ||
mean_op | ||
cross_entropy_op | ||
recurrent_network_op) |
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import unittest | ||
from op_test_util import OpTestMeta | ||
import numpy as np | ||
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class TestMeanOp(unittest.TestCase): | ||
__metaclass__ = OpTestMeta | ||
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def setUp(self): | ||
self.type = "mean" | ||
self.X = np.random.random((32, 784)).astype("float32") | ||
self.Out = np.mean(self.X) | ||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. no real test here ? check if mean_op's output equals inputs's mean There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. It looks it already did where OpTestMeta took this job. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. get it. |
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if __name__ == '__main__': | ||
unittest.main() |
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maybe we need a
axis
parameter to indicate which axis will be computed.There was a problem hiding this comment.
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I got, thanks.
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discussed with @reyoung Currently, we only need all mean operator.