Enable assign operator for a ngraph, test=develop

paddle/fluid/operators/ngraph/ops/assign_op.h

@@ -0,0 +1,43 @@
+/*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 <functional>
+#include <memory>
+#include <string>
+#include <unordered_map>
+
+#include "ngraph/ngraph.hpp"
+#include "paddle/fluid/operators/ngraph/ops/op_bridge.h"
+#include "paddle/fluid/platform/ngraph_helper.h"
+
+namespace paddle {
+namespace operators {
+namespace ngraphs {
+
+static void BuildAssignNode(
+    const std::shared_ptr<framework::OperatorBase>& op,
+    std::shared_ptr<
+        std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
+        ngb_node_map) {
+  auto input = platform::GetInputNode(op, "X", ngb_node_map);
+  auto out = input;
+  paddle::platform::SetOutputNode(op, "Out", out, ngb_node_map);
+}
+}  // namespace ngraphs
+}  // namespace operators
+}  // namespace paddle
+
+REGISTER_NG_OP(assign, BuildAssignNode);

paddle/fluid/operators/ngraph/ops/cross_entropy_op.h

@@ -26,59 +26,82 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 namespace ngraphs {
+std::shared_ptr<ngraph::Node> remove_trailing_one(
+    const std::shared_ptr<ngraph::Node>& input) {
+  auto shape = input->get_shape();
+  if (shape.back() == 1) {
+    shape.pop_back();
+    return platform::NgReshaper(input, shape);
+  } else {
+    return input;
+  }
+}
 
-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();
-  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);
+std::shared_ptr<ngraph::Node> flatten_node(
+    const std::shared_ptr<ngraph::Node>& input) {
+  auto shape = input->get_shape();
+  auto rank = shape.size();
+  auto output = input;
+  if (rank > 2) {
+    auto shape_2d = paddle::platform::FlattenTo2d(shape, rank - 1);
+    output = paddle::platform::NgReshaper(input, shape_2d);
   }
-  if (x_rank > 2) {
-    x_2d_shape = platform::FlattenTo2d(x_shape, x_rank - 1);
-    x_2d = platform::NgReshaper(x, x_2d_shape);
+  return output;
+}
+
+std::shared_ptr<ngraph::Node> convert_to_node_type(
+    const std::shared_ptr<ngraph::Node>& input,
+    const std::shared_ptr<ngraph::Node>& ref) {
+  auto output = input;
+  if (input->get_element_type() != ref->get_element_type()) {
+    output =
+        std::make_shared<ngraph::op::Convert>(input, ref->get_element_type());
   }
+  return output;
+}
 
-  auto batch_size = x_2d_shape.at(0);
+std::shared_ptr<ngraph::Node> create_xe(
+    const std::shared_ptr<ngraph::Node>& one_hot,
+    const std::shared_ptr<ngraph::Node>& x) {
+  auto node_log = std::make_shared<ngraph::op::Log>(x);
 
-  std::shared_ptr<ngraph::Node> node_1_hot = label_2d;
+  auto node_mul = one_hot * node_log;
+  auto node_sum = std::make_shared<ngraph::op::Sum>(
+      node_mul, ngraph::AxisSet{x->get_shape().size() - 1});
+
+  auto shape = x->get_shape();
+  shape.back() = 1;
+  return platform::NgReshaper(-node_sum, shape);
+}
+std::shared_ptr<ngraph::Node> create_mask(
+    const std::shared_ptr<ngraph::Node>& label, int ignore_index) {
+  auto ignore_node = paddle::platform::CreateConstant(
+      label->get_element_type(), label->get_shape(), {ignore_index});
+  auto not_equal_node =
+      std::make_shared<ngraph::op::NotEqual>(label, ignore_node);
+  return not_equal_node;
+}
+
+std::shared_ptr<ngraph::Node> create_one_hot(
+    const std::shared_ptr<ngraph::Node>& label,
+    const std::shared_ptr<ngraph::Node>& x) {
+  auto label_shape = label->get_shape();
+  return std::make_shared<ngraph::op::OneHot>(
+      remove_trailing_one(label), x->get_shape(), x->get_shape().size() - 1);
+}
+
+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) {
+  std::shared_ptr<ngraph::Node> node_1_hot = label;
   if (!is_soft_label) {
-    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()) {
-    node_1_hot = std::make_shared<ngraph::op::Convert>(node_1_hot,
-                                                       x->get_element_type());
+    node_1_hot = create_one_hot(label, x);
   }
+  node_1_hot = convert_to_node_type(node_1_hot, x);
 
-  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 = platform::NgReshaper(node_neg, ngraph::Shape{batch_size, 1});
-
+  auto xe = create_xe(node_1_hot, x);
   if (!is_soft_label) {
-    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());
+    auto mask = convert_to_node_type(create_mask(label, ignore_index), xe);
     xe = xe * mask;
   }
   return xe;
@@ -93,30 +116,17 @@ std::shared_ptr<ngraph::Node> GetCrossEntropyGrad(
 
   std::shared_ptr<ngraph::Node> mask;
   if (!is_soft_label) {
-    auto label_shape = label->get_shape();
-    label_shape.pop_back();
-    label = platform::NgReshaper(label, label_shape);
-
-    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);
+    mask = convert_to_node_type(create_mask(label, ignore_index), x);
+    mask = std::make_shared<ngraph::op::Broadcast>(
+        remove_trailing_one(mask), x_shape, ngraph::AxisSet{rank - 1});
+    label = create_one_hot(label, x);
   }
 
-  auto dy_shape = dy->get_shape();
-  dy_shape.pop_back();
-  auto dy_reshape = platform::NgReshaper(dy, dy_shape);
+  auto dy_reshape = remove_trailing_one(dy);
   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());
-  }
+
+  label = convert_to_node_type(label, x);
 
   auto xe_grad = -label * dy_bcast / x;
 
@@ -154,9 +164,80 @@ void BuildCrossEntropyGradNode(
   auto xe_grad = GetCrossEntropyGrad(x, label, dy, is_soft_label, ignore_index);
   paddle::platform::SetOutputNode(op, "X@GRAD", xe_grad, ngb_node_map);
 }
+
+void BuildCrossEntropy2Node(
+    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());
+  int ignore_index = op_attrs.Get<int>("ignore_index");
+
+  auto rank = x->get_shape().size();
+
+  auto one_hot = convert_to_node_type(create_one_hot(label, x), x);
+  auto xe = create_xe(one_hot, x);
+  auto mask = convert_to_node_type(create_mask(label, ignore_index), xe);
+
+  xe = xe * mask;
+
+  std::shared_ptr<ngraph::Node> node_sum =
+      std::make_shared<ngraph::op::Sum>(one_hot * x, ngraph::AxisSet{rank - 1});
+  node_sum = paddle::platform::NgReshaper(node_sum, mask->get_shape());
+  auto matchx = mask * node_sum;
+
+  paddle::platform::SetOutputNode(op, "MatchX", matchx, ngb_node_map);
+  platform::SetOutputNode(op, "XShape", x, ngb_node_map);
+  paddle::platform::SetOutputNode(op, "Y", xe, ngb_node_map);
+}
+
+void BuildCrossEntropyGrad2Node(
+    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());
+  int ignore_index = op_attrs.Get<int>("ignore_index");
+  auto matchx = paddle::platform::GetInputNode(op, "MatchX", ngb_node_map);
+  auto label = paddle::platform::GetInputNode(op, "Label", ngb_node_map);
+  auto x = paddle::platform::GetInputNode(op, "XShape", ngb_node_map);
+  auto dy = paddle::platform::GetInputNode(op, framework::GradVarName("Y"),
+                                           ngb_node_map);
+
+  matchx = remove_trailing_one(matchx);
+  label = remove_trailing_one(label);
+  x = remove_trailing_one(x);
+  dy = remove_trailing_one(dy);
+
+  auto x_shape = x->get_shape();
+  auto rank = x_shape.size();
+
+  auto one_hot = convert_to_node_type(create_one_hot(label, x), x);
+  auto mask = convert_to_node_type(create_mask(label, ignore_index), x);
+
+  auto zero = paddle::platform::CreateConstant(matchx->get_element_type(),
+                                               matchx->get_shape(), {0});
+  auto one = paddle::platform::CreateConstant(matchx->get_element_type(),
+                                              matchx->get_shape(), {1});
+  auto is_zero = std::make_shared<ngraph::op::Equal>(matchx, zero);
+  matchx = std::make_shared<ngraph::op::Select>(is_zero, one, matchx);
+
+  auto dy_bcast = std::make_shared<ngraph::op::Broadcast>(
+      mask * dy, x_shape, ngraph::AxisSet{rank - 1});
+  auto matchx_bcast = std::make_shared<ngraph::op::Broadcast>(
+      matchx, x_shape, ngraph::AxisSet{rank - 1});
+
+  auto xe_grad = -dy_bcast * one_hot / matchx_bcast;
+  paddle::platform::SetOutputNode(op, framework::GradVarName("X"), xe_grad,
+                                  ngb_node_map);
+}
 }  // namespace ngraphs
 }  // namespace operators
 }  // namespace paddle
 
 REGISTER_NG_OP(cross_entropy, BuildCrossEntropyNode);
 REGISTER_NG_OP(cross_entropy_grad, BuildCrossEntropyGradNode);
+REGISTER_NG_OP(cross_entropy2, BuildCrossEntropy2Node);
+REGISTER_NG_OP(cross_entropy_grad2, BuildCrossEntropyGrad2Node);

paddle/fluid/platform/ngraph_helper.h

@@ -77,9 +77,7 @@ std::shared_ptr<ngraph::Node> GetNode(
         std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
         ngb_node_map) {
   auto& var_names = var_map.at(name);
-  PADDLE_ENFORCE_EQ(var_names.size(), 1,
-                    "op %s name %s expects one associated var", op->Type(),
-                    name);
+  if (var_names.size() == 0) return nullptr;
   if (ngb_node_map->find(var_names[0]) != ngb_node_map->end()) {
     return (*ngb_node_map)[var_names[0]];
   } else {
@@ -132,16 +130,6 @@ void SetOutputNode(
         ngb_node_map) {
   auto& var_names = op->Outputs().at(name);
   if (var_names.size() == 1) {
-    /*  */
-    auto dummy_out = GetOutputNode(op, name, ngb_node_map);
-    if (dummy_out && dummy_out->get_shape() != node->get_shape()) {
-      node = NgReshaper(node, dummy_out->get_shape());
-    }
-    if (dummy_out &&
-        dummy_out->get_element_type() != node->get_element_type()) {
-      node = std::make_shared<ngraph::op::Convert>(
-          node, dummy_out->get_element_type());
-    }
     (*ngb_node_map)[var_names[0]] = node;
   } else if (var_names.size() == 0) {
     (*ngb_node_map)[""] = node;
@@ -189,6 +177,22 @@ inline void TrimTrailingSingularDims(ngraph::Shape* shape) {
     }
   }
 }
+
+ngraph::element::Type GetNgType(paddle::framework::proto::VarType::Type dtype) {
+  ngraph::element::Type ng_dtype;
+  if (dtype == paddle::framework::proto::VarType::FP32) {
+    ng_dtype = ngraph::element::f32;
+  } else if (dtype == paddle::framework::proto::VarType::FP64) {
+    ng_dtype = ngraph::element::f64;
+  } else if (dtype == paddle::framework::proto::VarType::INT64) {
+    ng_dtype = ngraph::element::i64;
+  } else if (dtype == paddle::framework::proto::VarType::INT32) {
+    ng_dtype = ngraph::element::i32;
+  } else {
+    PADDLE_THROW("unsupported data type: %s", dtype);
+  }
+  return ng_dtype;
+}
 }  // namespace platform
 }  // namespace paddle
 

python/paddle/fluid/tests/unittests/ngraph/test_assign_ngraph_op.py

@@ -0,0 +1,22 @@
+#   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, sys
+sys.path.append("../")
+from test_assign_op import *
+
+if __name__ == '__main__':
+    unittest.main()