提交 2de263a5 编写于 作者: B baojun 提交者: tensor-tang

Add softmax_with_cross_entropy_op to ngraph engine (#16304)

* Add softmax_with_cross_entropy_op test=develop

* simplify implementation test=develop
上级 a3b8028d
......@@ -325,7 +325,8 @@ void NgraphEngine::BuildNgIO(const std::vector<framework::OpDesc*>& ops_desc,
const bool is_output = outputs.find(var_name) != outputs.end();
if (!is_output &&
std::find(var_in_.begin(), var_in_.end(), var_name) ==
var_in_.end()) {
var_in_.end() &&
scope_.FindVar(var_name)) {
// fill var_in here to keep lhs and rhs order
this->var_in_.emplace_back(var_name);
}
......
......@@ -27,13 +27,9 @@ namespace paddle {
namespace operators {
namespace ngraphs {
void BuildCrossEntropyNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto x = paddle::platform::GetInputNode(op, "X", ngb_node_map);
auto label = paddle::platform::GetInputNode(op, "Label", ngb_node_map);
std::shared_ptr<ngraph::Node> GetCrossEntropy(
std::shared_ptr<ngraph::Node> x, std::shared_ptr<ngraph::Node> label,
const bool is_soft_label, int ignore_index) {
auto label_shape = label->get_shape();
auto x_shape = x->get_shape();
auto label_rank = label_shape.size();
......@@ -46,18 +42,16 @@ void BuildCrossEntropyNode(
label_2d = paddle::platform::NgReshaper(label, label_2d_shape);
}
if (x_rank > 2) {
x_2d_shape = paddle::platform::FlattenTo2d(x_shape, x_rank - 1);
x_2d = paddle::platform::NgReshaper(x, x_2d_shape);
x_2d_shape = platform::FlattenTo2d(x_shape, x_rank - 1);
x_2d = platform::NgReshaper(x, x_2d_shape);
}
auto batch_size = x_2d_shape.at(0);
auto op_attrs = paddle::framework::AttrReader(op->Attrs());
const bool is_soft_label = op_attrs.Get<bool>("soft_label");
std::shared_ptr<ngraph::Node> node_1_hot = label_2d;
if (!is_soft_label) {
auto label_1d = paddle::platform::NgReshaper(
label_2d, ngraph::Shape{label_2d_shape.at(0)});
auto label_1d =
platform::NgReshaper(label_2d, ngraph::Shape{label_2d_shape.at(0)});
node_1_hot = std::make_shared<ngraph::op::OneHot>(label_1d, x_2d_shape, 1);
}
if (x->get_element_type() != node_1_hot->get_element_type()) {
......@@ -76,11 +70,9 @@ void BuildCrossEntropyNode(
auto node_sum =
std::make_shared<ngraph::op::Sum>(node_mul, ngraph::AxisSet{1});
auto node_neg = std::make_shared<ngraph::op::Negative>(node_sum);
auto xe =
paddle::platform::NgReshaper(node_neg, ngraph::Shape{batch_size, 1});
auto xe = platform::NgReshaper(node_neg, ngraph::Shape{batch_size, 1});
if (!is_soft_label) {
auto ignore_index = op_attrs.Get<int>("ignore_index");
auto ignore_node = ngraph::op::Constant::create(
label->get_element_type(), label_2d_shape, {ignore_index});
auto not_equal_node =
......@@ -89,21 +81,13 @@ void BuildCrossEntropyNode(
xe->get_element_type());
xe = xe * mask;
}
paddle::platform::SetOutputNode(op, "Y", xe, ngb_node_map);
return xe;
}
void BuildCrossEntropyGradNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto op_attrs = paddle::framework::AttrReader(op->Attrs());
const bool is_soft_label = op_attrs.Get<bool>("soft_label");
auto x = paddle::platform::GetInputNode(op, "X", ngb_node_map);
auto label = paddle::platform::GetInputNode(op, "Label", ngb_node_map);
auto dy = paddle::platform::GetInputNode(op, "Y@GRAD", ngb_node_map);
std::shared_ptr<ngraph::Node> GetCrossEntropyGrad(
std::shared_ptr<ngraph::Node> x, std::shared_ptr<ngraph::Node> label,
std::shared_ptr<ngraph::Node> dy, const bool is_soft_label,
int ignore_index) {
auto x_shape = x->get_shape();
auto rank = x_shape.size();
......@@ -111,9 +95,8 @@ void BuildCrossEntropyGradNode(
if (!is_soft_label) {
auto label_shape = label->get_shape();
label_shape.pop_back();
label = paddle::platform::NgReshaper(label, label_shape);
label = platform::NgReshaper(label, label_shape);
auto ignore_index = op_attrs.Get<int>("ignore_index");
auto ignore_node = ngraph::op::Constant::create(
label->get_element_type(), label_shape, {ignore_index});
auto not_equal_node =
......@@ -128,7 +111,7 @@ void BuildCrossEntropyGradNode(
auto dy_shape = dy->get_shape();
dy_shape.pop_back();
auto dy_reshape = paddle::platform::NgReshaper(dy, dy_shape);
auto dy_reshape = platform::NgReshaper(dy, dy_shape);
auto dy_bcast = std::make_shared<ngraph::op::Broadcast>(
dy_reshape, x_shape, ngraph::AxisSet{rank - 1});
if (x->get_element_type() != label->get_element_type()) {
......@@ -140,7 +123,35 @@ void BuildCrossEntropyGradNode(
if (!is_soft_label) {
xe_grad = xe_grad * mask;
}
return xe_grad;
}
void BuildCrossEntropyNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto x = paddle::platform::GetInputNode(op, "X", ngb_node_map);
auto label = paddle::platform::GetInputNode(op, "Label", ngb_node_map);
auto op_attrs = paddle::framework::AttrReader(op->Attrs());
const bool is_soft_label = op_attrs.Get<bool>("soft_label");
int ignore_index = op_attrs.Get<int>("ignore_index");
auto xe = GetCrossEntropy(x, label, is_soft_label, ignore_index);
paddle::platform::SetOutputNode(op, "Y", xe, ngb_node_map);
}
void BuildCrossEntropyGradNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto op_attrs = paddle::framework::AttrReader(op->Attrs());
const bool is_soft_label = op_attrs.Get<bool>("soft_label");
int ignore_index = op_attrs.Get<int>("ignore_index");
auto x = paddle::platform::GetInputNode(op, "X", ngb_node_map);
auto label = paddle::platform::GetInputNode(op, "Label", ngb_node_map);
auto dy = paddle::platform::GetInputNode(op, "Y@GRAD", ngb_node_map);
auto xe_grad = GetCrossEntropyGrad(x, label, dy, is_soft_label, ignore_index);
paddle::platform::SetOutputNode(op, "X@GRAD", xe_grad, ngb_node_map);
}
} // namespace ngraphs
......
......@@ -27,12 +27,7 @@ namespace paddle {
namespace operators {
namespace ngraphs {
void BuildSoftmaxNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto x = paddle::platform::GetInputNode(op, "X", ngb_node_map);
std::shared_ptr<ngraph::Node> GetSoftmax(std::shared_ptr<ngraph::Node> x) {
auto x_shape = x->get_shape();
int rank = x_shape.size();
auto x_2d_shape = paddle::platform::FlattenTo2d(x_shape, rank - 1);
......@@ -47,16 +42,11 @@ void BuildSoftmaxNode(
-64., x_shifted);
auto softmax =
std::make_shared<ngraph::op::Softmax>(x_clipped, ngraph::AxisSet{1});
paddle::platform::SetOutputNode(op, "Out", softmax, ngb_node_map);
return softmax;
}
void BuildSoftmaxGradNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto out = paddle::platform::GetInputNode(op, "Out", ngb_node_map);
auto dout = paddle::platform::GetInputNode(op, "Out@GRAD", ngb_node_map);
std::shared_ptr<ngraph::Node> GetSoftmaxGrad(
std::shared_ptr<ngraph::Node> out, std::shared_ptr<ngraph::Node> dout) {
auto out_shape = out->get_shape();
int rank = out_shape.size();
auto out_2d_shape = paddle::platform::FlattenTo2d(out_shape, rank - 1);
......@@ -70,6 +60,27 @@ void BuildSoftmaxGradNode(
auto node_bcast = std::make_shared<ngraph::op::Broadcast>(
node_sum, out_2d_shape, ngraph::AxisSet{1});
auto dx = (dout - node_bcast) * out;
return dx;
}
void BuildSoftmaxNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto x = paddle::platform::GetInputNode(op, "X", ngb_node_map);
auto softmax = GetSoftmax(x);
paddle::platform::SetOutputNode(op, "Out", softmax, ngb_node_map);
}
void BuildSoftmaxGradNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto out = paddle::platform::GetInputNode(op, "Out", ngb_node_map);
auto dout = paddle::platform::GetInputNode(op, "Out@GRAD", ngb_node_map);
auto dx = GetSoftmaxGrad(out, dout);
paddle::platform::SetOutputNode(op, "X@GRAD", dx, ngb_node_map);
}
} // namespace ngraphs
......
/*Copyright (c) 2019 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 <memory>
#include <string>
#include <unordered_map>
#include <vector>
#include "ngraph/ngraph.hpp"
#include "paddle/fluid/operators/ngraph/ops/cross_entropy_op.h"
#include "paddle/fluid/operators/ngraph/ops/softmax_op.h"
#include "paddle/fluid/platform/ngraph_helper.h"
namespace paddle {
namespace operators {
namespace ngraphs {
void BuildSoftmaxWithCrossEntropyNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto logits = paddle::platform::GetInputNode(op, "Logits", ngb_node_map);
auto label = paddle::platform::GetInputNode(op, "Label", ngb_node_map);
auto softmax = paddle::operators::ngraphs::GetSoftmax(logits);
auto op_attrs = framework::AttrReader(op->Attrs());
const bool is_soft_label = op_attrs.Get<bool>("soft_label");
int ignore_index = op_attrs.Get<int>("ignore_index");
auto xe = paddle::operators::ngraphs::GetCrossEntropy(
softmax, label, is_soft_label, ignore_index);
paddle::platform::SetOutputNode(op, "Softmax", softmax, ngb_node_map);
paddle::platform::SetOutputNode(op, "Loss", xe, ngb_node_map);
}
void BuildSoftmaxWithCrossEntropyGradNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto op_attrs = framework::AttrReader(op->Attrs());
const bool is_soft_label = op_attrs.Get<bool>("soft_label");
auto label = paddle::platform::GetInputNode(op, "Label", ngb_node_map);
auto softmax = paddle::platform::GetInputNode(op, "Softmax", ngb_node_map);
auto loss_grad =
paddle::platform::GetInputNode(op, "Loss@GRAD", ngb_node_map);
auto softmax_shape = softmax->get_shape();
auto rank = softmax_shape.size();
if (!is_soft_label) {
auto label_shape = label->get_shape();
label_shape.pop_back();
label = platform::NgReshaper(label, label_shape);
label =
std::make_shared<ngraph::op::OneHot>(label, softmax_shape, rank - 1);
}
auto loss_grad_shape = loss_grad->get_shape();
loss_grad_shape.pop_back();
auto loss_grad_reshape = platform::NgReshaper(loss_grad, loss_grad_shape);
auto loss_grad_bcast = std::make_shared<ngraph::op::Broadcast>(
loss_grad_reshape, softmax_shape, ngraph::AxisSet{rank - 1});
if (softmax->get_element_type() != label->get_element_type()) {
label = std::make_shared<ngraph::op::Convert>(label,
softmax->get_element_type());
}
auto logits_grad = loss_grad_bcast * (softmax - label);
paddle::platform::SetOutputNode(op, "Logits@GRAD", logits_grad, ngb_node_map);
}
} // namespace ngraphs
} // namespace operators
} // namespace paddle
REGISTER_NG_OP(softmax_with_cross_entropy, BuildSoftmaxWithCrossEntropyNode);
REGISTER_NG_OP(softmax_with_cross_entropy_grad,
BuildSoftmaxWithCrossEntropyGradNode);
# Copyright (c) 2019 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_softmax_with_cross_entropy_op import TestSoftmaxWithCrossEntropyOp, TestSoftmaxWithCrossEntropyOp2, TestSoftmaxWithCrossEntropyOp3
if __name__ == "__main__":
unittest.main()
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