Enable momentum operator for a ngraph engine (#15673)
* Enable momentum operator for a ngraph engine test=develop * Update tests test=develop * Unnecessary line of the code as intended was removed test=developrevert-15774-anakin_subgraph_engine
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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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#pragma once
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#include <string>
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#include <vector>
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#include "ngraph/ngraph.hpp"
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#include "paddle/fluid/platform/ngraph_helper.h"
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namespace paddle {
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namespace operators {
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namespace ngraphs {
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void BuildMomentumNode(
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const std::shared_ptr<paddle::framework::OperatorBase>& op,
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std::shared_ptr<
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std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
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ngb_node_map) {
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auto op_attrs = paddle::framework::AttrReader(op->Attrs());
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auto param = paddle::platform::GetInputNode(op, "Param", ngb_node_map);
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auto grad = paddle::platform::GetInputNode(op, "Grad", ngb_node_map);
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auto velocity = paddle::platform::GetInputNode(op, "Velocity", ngb_node_map);
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auto learning_rate =
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paddle::platform::GetInputNode(op, "LearningRate", ngb_node_map);
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auto mu = op_attrs.Get<float>("mu");
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bool use_nesterov = op_attrs.Get<bool>("use_nesterov");
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auto param_shape = param->get_shape();
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auto velocity_shape = velocity->get_shape();
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auto grad_shape = grad->get_shape();
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auto lr_shape = learning_rate->get_shape();
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auto shape_velocity = ngraph::Shape{velocity_shape};
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auto mu_create =
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ngraph::op::Constant::create(ngraph::element::f32, shape_velocity, {mu});
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auto vel_mul = std::make_shared<ngraph::op::Multiply>(velocity, mu_create);
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auto vel_out = std::make_shared<ngraph::op::Add>(vel_mul, grad);
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ngraph::NodeVector result;
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if (use_nesterov) {
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auto mul_res = std::make_shared<ngraph::op::Multiply>(vel_out, mu_create);
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auto add_res = std::make_shared<ngraph::op::Add>(grad, mul_res);
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auto add_2d = paddle::platform::FlattenTo2d(add_res->get_shape(), 0);
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auto vel_reshape = paddle::platform::NgReshaper(vel_out, add_2d);
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auto lr_bcast = std::make_shared<ngraph::op::Broadcast>(
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learning_rate, vel_reshape->get_shape(),
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ngraph::AxisSet{vel_reshape->get_shape().size() - 1});
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auto lr_1d = paddle::platform::FlattenTo1d(lr_bcast->get_shape(), 0);
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auto lr_reshape = std::make_shared<ngraph::op::Reshape>(
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lr_bcast, ngraph::AxisVector{0, 1}, lr_1d);
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lr_reshape = std::make_shared<ngraph::op::Reshape>(
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lr_reshape, ngraph::AxisVector{0}, param->get_shape());
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auto mul_res1 = std::make_shared<ngraph::op::Multiply>(add_res, lr_reshape);
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auto res = std::make_shared<ngraph::op::Subtract>(param, mul_res1);
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paddle::platform::SetOutputNode(op, "ParamOut", res, ngb_node_map);
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} else {
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auto vel_2d = paddle::platform::FlattenTo2d(vel_out->get_shape(), 0);
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auto vel_reshape = paddle::platform::NgReshaper(vel_out, vel_2d);
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auto lr_bcast = std::make_shared<ngraph::op::Broadcast>(
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learning_rate, vel_reshape->get_shape(),
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ngraph::AxisSet{vel_reshape->get_shape().size() - 1});
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auto lr_1d = paddle::platform::FlattenTo1d(lr_bcast->get_shape(), 0);
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auto lr_reshape = std::make_shared<ngraph::op::Reshape>(
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lr_bcast, ngraph::AxisVector{0, 1}, lr_1d);
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lr_reshape = std::make_shared<ngraph::op::Reshape>(
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lr_reshape, ngraph::AxisVector{0}, param->get_shape());
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auto mul_result =
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std::make_shared<ngraph::op::Multiply>(lr_reshape, vel_out);
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auto res = std::make_shared<ngraph::op::Subtract>(param, mul_result);
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paddle::platform::SetOutputNode(op, "ParamOut", res, ngb_node_map);
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}
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paddle::platform::SetOutputNode(op, "VelocityOut", vel_out, ngb_node_map);
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}
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} // namespace ngraphs
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} // namespace operators
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} // namespace paddle
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# Copyright (c) 2019 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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from __future__ import print_function
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import unittest
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from paddle.fluid.tests.unittests.test_momentum_op import TestMomentumOp1, TestMomentumOp2, TestLarsMomentumOp, TestSparseMomentumOp, TestSparseMomentumOp2
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if __name__ == '__main__':
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unittest.main()
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