Merge branch 'develop' into refine_relu_test

cmake/external/mkldnn.cmake

@@ -56,6 +56,8 @@ ExternalProject_Add(
     GIT_TAG             "v0.14"
     PREFIX              ${MKLDNN_SOURCES_DIR}
     UPDATE_COMMAND      ""
+    # Patch MKLDNN to compile with gcc 4.8, the related issue is in intel/mkl-dnn#237.
+    PATCH_COMMAND       ${CMAKE_COMMAND} -E copy_if_different ${CMAKE_CURRENT_SOURCE_DIR}/patches/mkldnn.hpp ${MKLDNN_SOURCES_DIR}/src/extern_mkldnn/include/mkldnn.hpp
     CMAKE_ARGS          -DCMAKE_INSTALL_PREFIX=${MKLDNN_INSTALL_DIR}
     CMAKE_ARGS          -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE} 
     CMAKE_ARGS          -DMKLROOT=${MKLML_ROOT}

paddle/fluid/inference/analysis/CMakeLists.txt

-cc_library(dot SRCS dot.cc)
+cc_library(analysis SRCS dot.cc node.cc node.h)
+cc_test(test_node SRCS node_tester.cc DEPS analysis)

paddle/fluid/inference/analysis/device.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. */
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+enum class Device { CPU, GPU };
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle

paddle/fluid/inference/analysis/dot_tester.cc

+//   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.
+
+#include "paddle/fluid/inference/analysis/dot.h"
+
+#include <gtest/gtest.h>
+#include <memory>
+#include "paddle/fluid/inference/analysis/data_flow_graph.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+class DotTester : public ::testing::Test {
+ protected:
+  void SetUp() override {
+    std::vector<Dot::Attr> attrs({{"title", "hello"}});
+    dot.reset(new Dot(attrs));
+    dot->AddNode("a", {Dot::Attr{"shape", "box"}, Dot::Attr("color", "blue")});
+    dot->AddNode("b", {});
+    dot->AddNode("c", {});
+    dot->AddEdge("a", "b", {});
+    dot->AddEdge("b", "c", {});
+    dot->AddEdge("a", "c", {});
+  }
+
+  std::unique_ptr<Dot> dot;
+};
+
+TEST_F(DotTester, Build) {
+  auto codes = dot->Build();
+  // Output the DOT language code, the generated codes are too long to compare
+  // the string.
+  //
+  // The output is
+  //
+  // digraph G {
+  //   title="hello"
+  //   node_1
+  //   node_2
+  //   node_0[label="a" shape="box" color="blue"]
+  //   node_0->node_1
+  //   node_1->node_2
+  //   node_0->node_2
+  // } // end G
+  LOG(INFO) << '\n' << codes;
+}
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle

paddle/fluid/inference/analysis/helper.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 <string>
+#include <unordered_map>
+#include <vector>
+
+#include "paddle/fluid/platform/enforce.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+template <typename IteratorT>
+class iterator_range {
+  IteratorT begin_, end_;
+
+ public:
+  template <typename Container>
+  explicit iterator_range(Container &&c) : begin_(c.begin()), end_(c.end()) {}
+
+  iterator_range(const IteratorT &begin, const IteratorT &end)
+      : begin_(begin), end_(end) {}
+
+  const IteratorT &begin() const { return begin_; }
+  const IteratorT &end() const { return end_; }
+};
+
+/*
+ * An registry helper class, with its records keeps the order they registers.
+ */
+template <typename T>
+class OrderedRegistry {
+ public:
+  T *Register(const std::string &name, T *x) {
+    PADDLE_ENFORCE(!dic_.count(name));
+    dic_[name] = data_.size();
+    data_.emplace_back(std::unique_ptr<T>(x));
+    return data_.back().get();
+  }
+
+  T *Lookup(const std::string &name) {
+    auto it = dic_.find(name);
+    if (it == dic_.end()) return nullptr;
+    return data_[it->second].get();
+  }
+
+ protected:
+  std::unordered_map<std::string, int> dic_;
+  std::vector<std::unique_ptr<T>> data_;
+};
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle
+
+#define PADDLE_DISALLOW_COPY_AND_ASSIGN(type__) \
+                                                \
+  type__(const type__ &) = delete;              \
+                                                \
+  void operator=(const type__ &) = delete;

paddle/fluid/inference/analysis/node.cc

+/* 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. */
+
+#include "paddle/fluid/inference/analysis/node.h"
+#include "glog/logging.h"
+#include "paddle/fluid/platform/enforce.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+std::vector<Dot::Attr> Value::dot_attrs() const {
+  return std::vector<Dot::Attr>({Dot::Attr("style", "filled,rounded"),
+                                 Dot::Attr("shape", "box"),
+                                 Dot::Attr("fillcolor", "red")});
+}
+
+std::vector<Dot::Attr> Function::dot_attrs() const {
+  return std::vector<Dot::Attr>({Dot::Attr("style", "filled,rounded"),
+                                 Dot::Attr("shape", "diamond"),
+                                 Dot::Attr("fillcolor", "yellow")});
+}
+
+Node *NodeMap::Create(Node::Type type) {
+  switch (type) {
+    case Node::Type::kFunction:
+      nodes_.emplace_back(new Function);
+      break;
+    case Node::Type::kValue:
+      nodes_.emplace_back(new Value);
+      break;
+    default:
+      PADDLE_THROW("Not supported node type.");
+  }
+  nodes_.back()->id_ = size() - 1;
+  return nodes_.back().get();
+}
+
+Node *NodeMap::GetMutable(size_t id) {
+  PADDLE_ENFORCE_GT(size(), id);
+  return nodes_[id].get();
+}
+
+const Node &NodeMap::Get(size_t id) const {
+  PADDLE_ENFORCE_GT(size(), id);
+  return *nodes_[id].get();
+}
+
+void NodeMap::Delete(size_t id) {
+  PADDLE_ENFORCE_LT(id, size());
+  nodes_[id]->SetDeleted();
+}
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle

paddle/fluid/inference/analysis/node.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. */
+
+/*
+ * This file defines the Node class and its subclasses. A Node is the basis
+ * analysis element in a computation graph.
+ * There are basically two kinds of nodes, the function node and value node.
+ */
+#pragma once
+
+#include <memory>
+#include <string>
+#include <unordered_map>
+#include <vector>
+
+#include "paddle/fluid/inference/analysis/device.h"
+#include "paddle/fluid/inference/analysis/dot.h"
+#include "paddle/fluid/inference/analysis/helper.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+class NodeMap;
+
+/*
+ * Node Representation.
+ *
+ * This is a very important class for analysis. It is the base class of all
+ * nodes computed by a program that may be used as operands to other nodes.
+ * Node is the super class of other important classes such as Function and
+ * Value, some nodes can have a name.
+ */
+class Node {
+ public:
+  // Node type. NOTE the new node types should add here.
+  enum class Type { kNone = -1, kFunction, kValue, kFunctionBlock };
+
+  Node() = default;
+
+  struct Attr;
+
+  // Cast to a subclass type, Function for example.
+  template <typename Subclass>
+  Subclass &As() {
+    return *dynamic_cast<Subclass *>(this);
+  }
+
+  // Formatted representation of this Node.
+  virtual std::string repr() const {
+    return name() + "(" + std::to_string(id()) + ")";
+  }
+
+  // DOT node representation. One Node type can customize its own node
+  // representation.
+  virtual std::vector<Dot::Attr> dot_attrs() const {
+    return std::vector<Dot::Attr>({Dot::Attr("style", "filled")});
+  }
+
+  // Get an additional attribute and convert it to T data type. NOTE this will
+  // silently create a new attribute if not exists.
+  Attr &attr(const std::string &name) { return attrs_[name]; }
+
+  int id() const { return id_; }
+
+  bool deleted() const { return deleted_; }
+  void SetDeleted() { deleted_ = true; }
+
+  void SetName(const std::string &name) { name_ = name; }
+  const std::string &name() const { return name_; }
+
+  void SetType(Type type) { type_ = type; }
+  Type type() const { return type_; }
+
+  void *extra_info() const { return extra_info_; }
+  void SetExtraInfo(void *extra_info) { extra_info_ = extra_info; }
+
+  // Input links.
+  std::vector<Node *> inlinks;
+  // Output links.
+  std::vector<Node *> outlinks;
+
+  // A helper class to maintain the status from Pass.
+  // TODO(superjomn) add a checker here to ensure the T is primary.
+  struct Attr {
+    // NOTE T should be a primary type or a struct combined by several primary
+    // types.
+    // NOTE the STL containers should not use here.
+    // Some usages
+    // Attr attr;
+    // T data;
+    // attr.data.assign((char*)data, sizeof(data));
+
+    bool &Bool() { return As<bool>(); }
+    float &Float() { return As<float>(); }
+    int32_t &Int32() { return As<int32_t>(); }
+    int64_t &Int64() { return As<int64_t>(); }
+
+   private:
+    template <typename T>
+    T &As() {
+      // init storage in the first usage.
+      if (data_.empty()) {
+        VLOG(4) << "resize data to " << sizeof(T);
+        type_hash_ = typeid(T).hash_code();
+        data_.resize(sizeof(T));
+      }
+      PADDLE_ENFORCE(type_hash_ == typeid(T).hash_code(), "type not matched");
+      PADDLE_ENFORCE_EQ(data_.size(), sizeof(T), "Node attr type recast error");
+      return *reinterpret_cast<T *>(&data_[0]);
+    }
+
+   private:
+    std::string data_;
+    size_t type_hash_{std::numeric_limits<size_t>::max()};
+  };
+
+  virtual ~Node() {}
+
+  friend class NodeMap;
+
+  PADDLE_DISALLOW_COPY_AND_ASSIGN(Node);
+
+ protected:
+  // The id number not the name is a node's unique identifier in the computation
+  // graph.
+  int id_{-1};
+  std::string name_;
+  Type type_{Type::kNone};
+  // Mark this node is deleted by some pass.
+  bool deleted_{false};
+
+  void *extra_info_;
+
+  mutable std::unordered_map<std::string, Attr> attrs_;
+};
+
+class Function;
+/*
+ * Value represents a value node, it has some attributes including dims, data
+ * type and so on.
+ */
+class Value : public Node {
+ public:
+  enum class DataType { kInt32, kInt64, kFloat32, kFloat64 };
+  using Dims = std::vector<int>;
+
+  void SetDataType(DataType data_type) { data_type_ = data_type; }
+  DataType data_type() const { return data_type_; }
+
+  void SetDims(const Dims &dims) { dims_ = dims; }
+  const Dims &dims() const { return dims_; }
+
+  Device device() const { return device_; }
+  void SetDevice(Device device) { device_ = device; }
+
+  std::vector<Dot::Attr> dot_attrs() const override;
+
+  PADDLE_DISALLOW_COPY_AND_ASSIGN(Value);
+
+ protected:
+  Value() { SetType(Node::Type::kValue); }
+  friend class NodeMap;
+
+ private:
+  DataType data_type_;
+  Dims dims_;
+  Device device_;
+};
+
+/*
+ * Function represents any kind of executable concepts that takes several Values
+ * as input, and outputs several Values.
+ */
+class Function : public Node {
+ public:
+  std::vector<Dot::Attr> dot_attrs() const override;
+
+  // Get the operator's type from Desc.
+  const std::string &func_type() const { return func_type_; }
+  // Set the operator's type.
+  void SetFuncType(const std::string &func_type) { func_type_ = func_type; }
+
+  PADDLE_DISALLOW_COPY_AND_ASSIGN(Function);
+
+ protected:
+  std::string func_type_;
+  Function() { SetType(Node::Type::kFunction); }
+  friend class NodeMap;
+};
+
+/*
+ * FunctionBlock is a Node that contains a sub-graph multiple Node.
+ */
+struct FunctionBlock : public Node {
+  std::string repr() const override { return "block-" + std::to_string(id()); }
+  std::vector<Node *> subgraph;
+};
+
+class NodeMap {
+ public:
+  // Create a new node with type.
+  Node *Create(Node::Type type);
+
+  // Get a node by its id.
+  Node *GetMutable(size_t id);
+
+  const Node &Get(size_t id) const;
+
+  void Delete(size_t id);
+
+  const std::vector<std::unique_ptr<Node>> &nodes() { return nodes_; }
+
+  size_t size() const { return nodes_.size(); }
+
+ private:
+  std::vector<std::unique_ptr<Node>> nodes_;
+  std::unordered_map<std::string, Node *> map_;
+};
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle

paddle/fluid/inference/analysis/node_tester.cc

+/* 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. */
+
+#include "paddle/fluid/inference/analysis/node.h"
+
+#include <gtest/gtest.h>
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+TEST(Node, Attr) {
+  // Node is an abstract class, use Value instead for they share the same Attr
+  // logic.
+  NodeMap nodes;
+  auto* node = nodes.Create(Node::Type::kValue);
+  node->attr("v0").Int32() = 2008;
+  ASSERT_EQ(node->attr("v0").Int32(), 2008);
+}
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle

python/paddle/fluid/tests/unittests/test_network_with_dtype.py

@@ -27,12 +27,15 @@ class TestNetWithDtype(unittest.TestCase):
     def set_network(self):
         self.dtype = "float64"
         self.init_dtype()
+        main = fluid.Program()
+        with fluid.program_guard(main):
             self.x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype)
             self.y = fluid.layers.data(name='y', shape=[1], dtype=self.dtype)
             y_predict = fluid.layers.fc(input=self.x, size=1, act=None)
 
             cost = fluid.layers.square_error_cost(input=y_predict, label=self.y)
             avg_cost = fluid.layers.mean(cost)
+        self.program = main
         self.fetch_list = [avg_cost]
 
         sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
@@ -45,7 +48,7 @@ class TestNetWithDtype(unittest.TestCase):
         exe = fluid.Executor(place)
         exe.run(fluid.default_startup_program())
         for data in train_reader():
-            exe.run(fluid.default_main_program(),
+            exe.run(self.program,
                     feed=feeder.feed(data),
                     fetch_list=self.fetch_list)
             # the main program is runable, the datatype is fully supported
@@ -68,7 +71,7 @@ class TestNetWithDtype(unittest.TestCase):
 
 
 # TODO(dzhwinter): make sure the fp16 is runable
-# class TestFloat16(SimpleNet):
+# class TestFloat16(TestNetWithDtype):
 #     def init_dtype(self):
 #         self.dtype = "float16"