Refine regularization for selected_rows (#12369)
* refine regularization for selected_rows * clean lookup_table * refine rpc_server_test * temporally disable rpc_server_test * fix rpc_server_test * add unit testbugfix/anakin-compile
chengduo
7 years ago
committed by
GitHub
parent
85c4912755
commit
2409d0f710
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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 <string>
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#include <vector>
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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class ExtractRowsOpInferShape : public framework::InferShapeBase {
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public:
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void operator()(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"),
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"Input(X) of ExtractRowsOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of ExtractRowsOp should not be null.");
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PADDLE_ENFORCE_EQ(ctx->GetInputsVarType("X")[0],
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framework::proto::VarType::SELECTED_ROWS,
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"The type of input(X) must be SelectedRows.");
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auto in_dims = ctx->GetInputDim("X");
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ctx->SetOutputDim(
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"Out", framework::make_ddim(std::vector<int64_t>{in_dims[0], 1}));
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}
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};
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class ExtractRowsOp : public framework::OperatorBase {
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public:
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ExtractRowsOp(const std::string &type,
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const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: framework::OperatorBase(type, inputs, outputs, attrs) {}
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private:
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void RunImpl(const framework::Scope &scope,
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const platform::Place &place) const override {
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auto &in = scope.FindVar(Input("X"))->Get<framework::SelectedRows>();
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auto out = scope.FindVar(Output("Out"))->GetMutable<framework::LoDTensor>();
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auto in_rows = in.rows();
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auto out_dim = framework::make_ddim(
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std::vector<int64_t>{static_cast<int64_t>(in_rows.size()), 1});
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auto dst_ptr = out->mutable_data<int64_t>(out_dim, in.place());
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if (paddle::platform::is_gpu_place(in.place())) {
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#ifdef PADDLE_WITH_CUDA
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platform::DeviceContextPool &pool =
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platform::DeviceContextPool::Instance();
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auto *dev_ctx = pool.Get(in.place());
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auto src_ptr = in_rows.Data(in.place());
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auto stream =
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reinterpret_cast<const platform::CUDADeviceContext &>(*dev_ctx)
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.stream();
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memory::Copy(boost::get<platform::CUDAPlace>(out->place()), dst_ptr,
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boost::get<platform::CUDAPlace>(in.place()), src_ptr,
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in_rows.size() * sizeof(int64_t), stream);
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#else
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PADDLE_THROW("Not compiled with CUDA.");
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#endif
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} else {
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memory::Copy(platform::CPUPlace(), dst_ptr, platform::CPUPlace(),
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in_rows.data(), in_rows.size() * sizeof(int64_t));
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}
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}
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};
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class ExtractRowsOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X",
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"(SelectedRows). The input tensor of extract_rows operator,"
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" and its type is SelectedRows.");
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AddOutput("Out", "(Tensor). The the rows of input(X).");
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AddComment(R"DOC(
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ExtractRows Operator.
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The function of extract_rows_op is extracting the rows from the input(X)
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whose type is SelectedRows.
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)DOC");
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OPERATOR(extract_rows, ops::ExtractRowsOp, ops::ExtractRowsOpMaker,
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ops::ExtractRowsOpInferShape);
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@ -0,0 +1,58 @@
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# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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import unittest
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import numpy as np
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import paddle.fluid.core as core
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from paddle.fluid.op import Operator
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from op_test import OpTest
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class TestExtractRows(OpTest):
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def check_with_place(self, place):
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scope = core.Scope()
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# create and initialize Variable
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feature_len = 12
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rows = [0, 4, 4, 7]
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np_array = np.ones((len(rows), feature_len)).astype("float32")
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in_x = scope.var('X').get_selected_rows()
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in_x.set_height(len(rows))
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in_x.set_rows(rows)
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in_x_tensor = in_x.get_tensor()
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in_x_tensor.set(np_array, place)
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# create Out Variable
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out_tensor = scope.var('Out').get_tensor()
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# create and run lookup_table operator
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extract_rows_op = Operator("extract_rows", X='X', Out='Out')
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extract_rows_op.run(scope, place)
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# get result from Out
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result_array = np.array(out_tensor)
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result_array = [ele[0] for ele in result_array]
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assert result_array == rows
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def test_concat_rows(self):
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places = [core.CPUPlace()]
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if core.is_compiled_with_cuda():
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places.append(core.CUDAPlace(0))
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for place in places:
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self.check_with_place(place)
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if __name__ == '__main__':
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unittest.main()
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