cross_entropy_op.h

/*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 <functional>
#include <string>

#include "ngraph/ngraph.hpp"
#include "paddle/fluid/platform/ngraph_helper.h"

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);
  auto label_shape = label->get_shape();
  auto x_shape = x->get_shape();
  auto label_rank = label_shape.size();
  auto x_rank = x_shape.size();
  std::shared_ptr<ngraph::Node> x_2d = x, label_2d = label;
  auto label_2d_shape = label_shape, x_2d_shape = x_shape;

  if (label_rank > 2) {
    label_2d_shape = paddle::platform::FlattenTo2d(label_shape, label_rank - 1);
    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);
  }

  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)});
    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()) {
    node_1_hot = std::make_shared<ngraph::op::Convert>(node_1_hot,
                                                       x->get_element_type());
  }

  auto node_log = std::make_shared<ngraph::op::Log>(x_2d);
  auto high_clip = ngraph::op::Constant::create(node_log->get_element_type(),
                                                node_log->get_shape(), {1e20});
  auto low_clip = ngraph::op::Constant::create(node_log->get_element_type(),
                                               node_log->get_shape(), {-1e20});
  auto node_min = std::make_shared<ngraph::op::Minimum>(node_log, high_clip);
  auto node_max = std::make_shared<ngraph::op::Maximum>(node_min, low_clip);
  auto node_mul = node_1_hot * node_log;
  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});

  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 =
        std::make_shared<ngraph::op::NotEqual>(label_2d, ignore_node);
    auto mask = std::make_shared<ngraph::op::Convert>(not_equal_node,
                                                      xe->get_element_type());
    xe = xe * mask;
  }

  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");

  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 x_shape = x->get_shape();
  auto rank = x_shape.size();

  std::shared_ptr<ngraph::Node> mask;
  if (!is_soft_label) {
    auto label_shape = label->get_shape();
    label_shape.pop_back();
    label = paddle::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 =
        std::make_shared<ngraph::op::NotEqual>(label, ignore_node);
    mask = std::make_shared<ngraph::op::Convert>(not_equal_node,
                                                 x->get_element_type());
    mask = std::make_shared<ngraph::op::Broadcast>(mask, x_shape,
                                                   ngraph::AxisSet{rank - 1});

    label = std::make_shared<ngraph::op::OneHot>(label, x_shape, rank - 1);
  }

  auto dy_shape = dy->get_shape();
  dy_shape.pop_back();
  auto dy_reshape = paddle::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()) {
    label = std::make_shared<ngraph::op::Convert>(label, x->get_element_type());
  }

  auto xe_grad = -label * dy_bcast / x;

  if (!is_soft_label) {
    xe_grad = xe_grad * mask;
  }

  paddle::platform::SetOutputNode(op, "X@GRAD", xe_grad, ngb_node_map);
}
}  // namespace ngraphs
}  // namespace operators
}  // namespace paddle