Add ngraph sum, sigmoid, relu_grad and tanh_grad op (#15642)

* Added ngraph sum op test=develop

* Added sigmoid, relu_grad and tanh_grad test=develop

* remove duplicates test=develop
revert-15684-revert-15661-fix-cpu-broadcast
baojun 6 years ago committed by tensor-tang
parent 33d0cebbff
commit c47e258ea4

@ -48,8 +48,12 @@ std::map<std::string,
{"softmax", NG_OPS::BuildSoftmaxNode},
{"softmax_grad", NG_OPS::BuildSoftmaxGradNode},
{"scale", NG_OPS::BuildScaleNode},
{"sigmoid", NG_OPS::BuildUnaryNode<ngraph::op::Sigmoid>},
{"sum", NG_OPS::BuildSumNode},
{"relu", NG_OPS::BuildUnaryNode<ngraph::op::Relu>},
{"relu_grad", NG_OPS::BuildReluGradNode},
{"tanh", NG_OPS::BuildUnaryNode<ngraph::op::Tanh>},
{"tanh_grad", NG_OPS::BuildTanhGradNode},
{"top_k", NG_OPS::BuildTopKNode}};
void NgraphBridge::BuildNgNode(

@ -22,6 +22,7 @@ limitations under the License. */
#pragma once
#include "ops/accuracy_op.h"
#include "ops/activation_op.h"
#include "ops/batch_norm_op.h"
#include "ops/binary_unary_op.h"
#include "ops/conv2d_op.h"
@ -32,4 +33,5 @@ limitations under the License. */
#include "ops/pool2d_op.h"
#include "ops/scale_op.h"
#include "ops/softmax_op.h"
#include "ops/sum_op.h"
#include "ops/top_k_op.h"

@ -0,0 +1,52 @@
/*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 <string>
#include "ngraph/ngraph.hpp"
#include "paddle/fluid/platform/ngraph_helper.h"
namespace paddle {
namespace operators {
namespace ngraphs {
void BuildReluGradNode(
const std::shared_ptr<framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto out = platform::GetInputNode(op, "Out", ngb_node_map);
auto dout = platform::GetInputNode(op, "Out@GRAD", ngb_node_map);
auto relu_grad = std::make_shared<ngraph::op::ReluBackprop>(out, dout);
platform::SetOutputNode(op, "X@GRAD", relu_grad, ngb_node_map);
}
void BuildTanhGradNode(
const std::shared_ptr<framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto out = platform::GetInputNode(op, "Out", ngb_node_map);
auto dout = platform::GetInputNode(op, "Out@GRAD", ngb_node_map);
auto shape = out->get_shape();
auto node_const =
ngraph::op::Constant::create(ngraph::element::f32, shape, {1});
auto result = dout * (node_const - out * out);
platform::SetOutputNode(op, "X@GRAD", result, ngb_node_map);
}
} // namespace ngraphs
} // namespace operators
} // namespace paddle

@ -0,0 +1,55 @@
/*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 <string>
#include <vector>
#include "ngraph/ngraph.hpp"
#include "paddle/fluid/platform/ngraph_helper.h"
namespace paddle {
namespace operators {
namespace ngraphs {
void BuildSumNode(
const std::shared_ptr<framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
std::vector<std::string> op_inputs;
for (auto& var_name_item : op->Inputs()) {
for (auto& var_name : var_name_item.second) {
op_inputs.push_back(var_name);
if (ngb_node_map->find(var_name) == ngb_node_map->end()) {
PADDLE_THROW("op % input varname %s is not found in var_node_map",
op->Type(), var_name);
}
}
}
std::shared_ptr<ngraph::Node>& sum = ngb_node_map->at(op_inputs[0]);
for (size_t k = 1; k < op_inputs.size(); ++k) {
std::shared_ptr<ngraph::Node>& nodek = ngb_node_map->at(op_inputs[k]);
if (nodek->get_element_type() != sum->get_element_type()) {
nodek =
std::make_shared<ngraph::op::Convert>(nodek, sum->get_element_type());
}
sum = sum + nodek;
}
platform::SetOutputNode(op, "Out", sum, ngb_node_map);
}
} // namespace ngraphs
} // namespace operators
} // namespace paddle

@ -18,17 +18,7 @@ import unittest
import numpy as np
import paddle.fluid.core as core
from paddle.fluid.tests.unittests.op_test import OpTest
from paddle.fluid.tests.unittests.test_activation_op import TestRelu, TestTanh
class TestNGRAPHReluDim2(TestRelu):
def setUp(self):
super(TestNGRAPHReluDim2, self).setUp()
class TestNGRAPHTanhDim2(TestTanh):
def setUp(self):
super(TestNGRAPHTanhDim2, self).setUp()
from paddle.fluid.tests.unittests.test_activation_op import TestSigmoid, TestRelu, TestTanh
class TestNGRAPHReluDim4(TestRelu):

@ -0,0 +1,19 @@
# 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.
from __future__ import print_function
import unittest
from paddle.fluid.tests.unittests.test_sum_op import TestSumOp, TestSelectedRowsSumOp, TestLoDTensorAndSelectedRowsOp
if __name__ == "__main__":
unittest.main()
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