Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into reduce-elementwise-warning

paddle/framework/attribute.cc

@@ -24,6 +24,9 @@ static ProgramDesc* g_program_desc = nullptr;
 ProgramDesc& GetProgramDesc() {
   if (g_program_desc == nullptr) {
     g_program_desc = new ProgramDesc();
+    auto root_block = g_program_desc->mutable_blocks()->Add();
+    root_block->set_idx(0);
+    root_block->set_parent_idx(-1);
   }
   return *g_program_desc;
 }

paddle/operators/math/softmax.cc

@@ -18,7 +18,7 @@ namespace paddle {
 namespace operators {
 namespace math {
 
-template class SoftmaxFunctor<platform::GPUPlace, float>;
+template class SoftmaxFunctor<platform::CPUPlace, float>;
 
 }  // namespace math
 }  // namespace operators

paddle/operators/softmax_with_cross_entropy_op.cc

@@ -82,40 +82,38 @@ class SoftmaxWithCrossEntropyOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
-  void InferShape(const framework::InferShapeContext& ctx) const override {
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Logits"),
-                            "Input(Logits) should be not null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Label"),
-                            "Input(Label) should be not null.");
-
-    PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Softmax"),
-                            "Output(Softmax) should be not null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Loss"),
-                            "Output(Loss) should be not null.");
-
-    const Tensor* logits = ctx.Input<Tensor>("Logits");
-    const Tensor* labels = ctx.Input<Tensor>("Label");
+  void InferShape(framework::InferShapeContextBase* ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput("Logits"),
+                   "Input(Logits) should be not null.");
+    PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) should be not null.");
+
+    PADDLE_ENFORCE(ctx->HasOutput("Softmax"),
+                   "Output(Softmax) should be not null.");
+    PADDLE_ENFORCE(ctx->HasOutput("Loss"), "Output(Loss) should be not null.");
+
+    auto logits_dims = ctx->GetInputDim("Logits");
+    auto labels_dims = ctx->GetInputDim("Label");
     PADDLE_ENFORCE_EQ(
-        logits->dims().size(), 2UL,
+        logits_dims.size(), 2UL,
         "The input of softmax_with_cross_entropy should be a 2-D tensor.");
-    PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("Label")->dims().size(), 2UL,
+    PADDLE_ENFORCE_EQ(labels_dims.size(), 2UL,
                       "The labels should be a 2-D tensor.");
 
-    if (ctx.Attr<bool>("softLabel")) {
-      PADDLE_ENFORCE_EQ(logits->dims()[1], labels->dims()[1],
+    if (ctx->Attrs().Get<bool>("softLabel")) {
+      PADDLE_ENFORCE_EQ(logits_dims[1], labels_dims[1],
                         "If Attr(softLabel) == true, the 2nd dimension of "
                         "Input(X) and Input(Label) should be equal.");
     } else {
-      PADDLE_ENFORCE_EQ(labels->dims()[1], 1UL,
+      PADDLE_ENFORCE_EQ(labels_dims[1], 1UL,
                         "If Attr(softLabel) == false, the 2nd dimension of "
                         "Input(Label) should be 1.");
     }
 
-    ctx.Output<framework::Tensor>("Softmax")->Resize(logits->dims());
-    ctx.Output<framework::Tensor>("Loss")->Resize({logits->dims()[0], 1});
+    ctx->SetOutputDim("Softmax", logits_dims);
+    ctx->SetOutputDim("Loss", {logits_dims[0], 1});
 
-    ctx.ShareLoD("Logits", /*->*/ "Softmax");
-    ctx.ShareLoD("Logits", /*->*/ "Loss");
+    ctx->ShareLoD("Logits", /*->*/ "Softmax");
+    ctx->ShareLoD("Logits", /*->*/ "Loss");
   }
 };
 
@@ -124,33 +122,32 @@ class SoftmaxWithCrossEntropyOpGrad : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
-  void InferShape(const framework::InferShapeContext& ctx) const override {
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Loss")),
-                            "Input(Loss@Grad) should not be null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Softmax"),
-                            "Input(Softmax) should be not null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Label"),
-                            "Input(Label) should be not null.");
-    PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar(framework::GradVarName("Logits")),
-                            "Output(Logits@Grad) should be not null.");
-
-    const Tensor* softmax = ctx.Input<Tensor>("Softmax");
-    const Tensor* labels = ctx.Input<Tensor>("Label");
-    PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("Label")->dims().size(), 2UL,
+  void InferShape(framework::InferShapeContextBase* ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Loss")),
+                   "Input(Loss@Grad) should not be null.");
+    PADDLE_ENFORCE(ctx->HasInput("Softmax"),
+                   "Input(Softmax) should be not null.");
+    PADDLE_ENFORCE(ctx->HasInput("Label"), "Input(Label) should be not null.");
+    PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("Logits")),
+                   "Output(Logits@Grad) should be not null.");
+
+    auto softmax_dims = ctx->GetInputDim("Softmax");
+    auto labels_dims = ctx->GetInputDim("Label");
+    PADDLE_ENFORCE_EQ(labels_dims.size(), 2UL,
                       "The labels should be a 2-D tensor.");
 
-    if (ctx.Attr<bool>("softLabel")) {
-      PADDLE_ENFORCE_EQ(softmax->dims()[1], labels->dims()[1],
+    if (ctx->Attrs().Get<bool>("softLabel")) {
+      PADDLE_ENFORCE_EQ(softmax_dims[1], labels_dims[1],
                         "When Attr(softLabel) == true, the 2nd dimension of "
                         "Input(X) and Input(Label) should be equal.");
     } else {
-      PADDLE_ENFORCE_EQ(labels->dims()[1], 1UL,
+      PADDLE_ENFORCE_EQ(labels_dims[1], 1UL,
                         "When Attr(softLabel) == false, the 2nd dimension of "
                         "Input(Label) should be 1.");
     }
 
-    ctx.Output<framework::LoDTensor>(framework::GradVarName("Logits"))
-        ->Resize(ctx.Input<Tensor>("Softmax")->dims());
+    ctx->SetOutputDim(framework::GradVarName("Logits"),
+                      ctx->GetInputDim("Softmax"));
   }
 };
 

paddle/pybind/CMakeLists.txt

 if(WITH_PYTHON)
   cc_library(paddle_pybind SHARED
-    SRCS pybind.cc
+    SRCS pybind.cc protobuf.cc
     DEPS pybind python backward
     ${GLOB_OP_LIB})
 endif(WITH_PYTHON)

paddle/pybind/protobuf.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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/pybind/protobuf.h"
+#include <deque>
+#include <iostream>
+#include "paddle/framework/attribute.h"
+
+// Cast boost::variant for PyBind.
+// Copy from
+// https://github.com/pybind/pybind11/issues/576#issuecomment-269563199
+namespace pybind11 {
+namespace detail {
+
+// Can be replaced by a generic lambda in C++14
+struct variant_caster_visitor : public boost::static_visitor<handle> {
+  return_value_policy policy;
+  handle parent;
+
+  variant_caster_visitor(return_value_policy policy, handle parent)
+      : policy(policy), parent(parent) {}
+
+  template <class T>
+  handle operator()(T const &src) const {
+    return make_caster<T>::cast(src, policy, parent);
+  }
+};
+
+template <class Variant>
+struct variant_caster;
+
+template <template <class...> class V, class... Ts>
+struct variant_caster<V<Ts...>> {
+  using Type = V<Ts...>;
+
+  template <typename T>
+  typename std::enable_if<
+      !std::is_same<T, boost::detail::variant::void_>::value,
+      bool>::type
+  try_load(handle src, bool convert) {
+    auto caster = make_caster<T>();
+    if (!load_success_ && caster.load(src, convert)) {
+      load_success_ = true;
+      value = cast_op<T>(caster);
+      return true;
+    }
+    return false;
+  }
+
+  template <typename T>
+  typename std::enable_if<std::is_same<T, boost::detail::variant::void_>::value,
+                          bool>::type
+  try_load(handle src, bool convert) {
+    return false;
+  }
+
+  bool load(handle src, bool convert) {
+    auto unused = {false, try_load<Ts>(src, convert)...};
+    (void)(unused);
+    return load_success_;
+  }
+
+  static handle cast(Type const &src,
+                     return_value_policy policy,
+                     handle parent) {
+    variant_caster_visitor visitor(policy, parent);
+    return boost::apply_visitor(visitor, src);
+  }
+
+  PYBIND11_TYPE_CASTER(Type, _("Variant"));
+  bool load_success_{false};
+};
+
+// Add specialization for concrete variant type
+template <class... Args>
+struct type_caster<boost::variant<Args...>>
+    : variant_caster<boost::variant<Args...>> {};
+
+}  // namespace detail
+}  // namespace pybind11
+
+namespace paddle {
+namespace pybind {
+
+using namespace paddle::framework;  // NOLINT
+
+// convert between std::vector and protobuf repeated.
+template <typename T>
+inline std::vector<T> RepeatedToVector(
+    const google::protobuf::RepeatedField<T> &repeated_field) {
+  std::vector<T> ret;
+  ret.reserve(repeated_field.size());
+  std::copy(
+      repeated_field.begin(), repeated_field.end(), std::back_inserter(ret));
+  return ret;
+}
+
+template <typename T, typename RepeatedField>
+inline void VectorToRepeated(const std::vector<T> &vec,
+                             RepeatedField *repeated_field) {
+  repeated_field->Reserve(vec.size());
+  for (const auto &elem : vec) {
+    *repeated_field->Add() = elem;
+  }
+}
+
+// Specialize vector<bool>.
+template <typename RepeatedField>
+inline void VectorToRepeated(const std::vector<bool> &vec,
+                             RepeatedField *repeated_field) {
+  repeated_field->Reserve(vec.size());
+  for (auto elem : vec) {
+    *repeated_field->Add() = elem;
+  }
+}
+
+class ProgramDescBind;
+class OpDescBind;
+class BlockDescBind;
+class VarDescBind;
+
+// Each Protobuf Message, we provide a XXXBind class. In that class, we optimize
+// read/write speed. Only when we want the protobuf message, the local changes
+// will be synchronized (by `Sync` method).
+class VarDescBind {
+public:
+  explicit VarDescBind(const std::string &name) { desc_.set_name(name); }
+
+  VarDesc *Proto() { return &desc_; }
+
+  py::bytes Name() const { return desc_.name(); }
+
+  void SetShape(const std::vector<int64_t> &dims) {
+    VectorToRepeated(dims, desc_.mutable_lod_tensor()->mutable_dims());
+  }
+
+  void SetDataType(framework::DataType data_type) {
+    desc_.mutable_lod_tensor()->set_data_type(data_type);
+  }
+
+  std::vector<int64_t> Shape() const {
+    return RepeatedToVector(desc_.lod_tensor().dims());
+  }
+
+  framework::DataType DataType() const {
+    return desc_.lod_tensor().data_type();
+  }
+
+private:
+  VarDesc desc_;
+};
+
+class OpDescBind {
+public:
+  OpDesc *Proto() {
+    Sync();
+    return &op_desc_;
+  }
+
+  std::string Type() const { return op_desc_.type(); }
+
+  void SetType(const std::string &type) { op_desc_.set_type(type); }
+
+  const std::vector<std::string> &Input(const std::string &name) const {
+    auto it = inputs_.find(name);
+    PADDLE_ENFORCE(
+        it != inputs_.end(), "Input %s cannot be found in Op %s", name, Type());
+    return it->second;
+  }
+
+  std::vector<std::string> InputNames() const {
+    std::vector<std::string> retv;
+    retv.reserve(this->inputs_.size());
+    for (auto &ipt : this->inputs_) {
+      retv.push_back(ipt.first);
+    }
+    return retv;
+  }
+
+  void SetInput(const std::string &param_name,
+                const std::vector<std::string> &args) {
+    need_update_ = true;
+    inputs_[param_name] = args;
+  }
+
+  const std::vector<std::string> &Output(const std::string &name) const {
+    auto it = outputs_.find(name);
+    PADDLE_ENFORCE(it != outputs_.end(),
+                   "Output %s cannot be found in Op %s",
+                   name,
+                   Type());
+    return it->second;
+  }
+
+  std::vector<std::string> OutputNames() const {
+    std::vector<std::string> retv;
+    retv.reserve(this->outputs_.size());
+    for (auto &ipt : this->outputs_) {
+      retv.push_back(ipt.first);
+    }
+    return retv;
+  }
+
+  void SetOutput(const std::string &param_name,
+                 const std::vector<std::string> &args) {
+    need_update_ = true;
+    this->outputs_[param_name] = args;
+  }
+
+  std::string DebugString() { return this->Proto()->DebugString(); }
+
+  bool HasAttr(const std::string &name) const {
+    return attrs_.find(name) != attrs_.end();
+  }
+
+  framework::AttrType GetAttrType(const std::string &name) const {
+    auto it = attrs_.find(name);
+    PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
+    return static_cast<framework::AttrType>(it->second.which() - 1);
+  }
+
+  std::vector<std::string> AttrNames() const {
+    std::vector<std::string> retv;
+    retv.reserve(attrs_.size());
+    for (auto &attr : attrs_) {
+      retv.push_back(attr.first);
+    }
+    return retv;
+  }
+
+  void SetAttr(const std::string &name, const Attribute &v) {
+    this->attrs_[name] = v;
+    need_update_ = true;
+  }
+
+  void SetBlockAttr(const std::string &name, BlockDescBind &block);
+
+  Attribute GetAttr(const std::string &name) const {
+    auto it = attrs_.find(name);
+    PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
+    return it->second;
+  }
+
+  int GetBlockAttr(const std::string &name) const {
+    auto it = attrs_.find(name);
+    PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
+    return boost::get<BlockDesc *>(it->second)->idx();
+  }
+
+private:
+  struct SetAttrDescVisitor : public boost::static_visitor<void> {
+    explicit SetAttrDescVisitor(OpDesc::Attr *attr) : attr_(attr) {}
+    mutable OpDesc::Attr *attr_;
+    void operator()(int v) const { attr_->set_i(v); }
+    void operator()(float v) const { attr_->set_f(v); }
+    void operator()(const std::string &v) const { attr_->set_s(v); }
+    void operator()(bool b) const { attr_->set_b(b); }
+
+    void operator()(const std::vector<int> &v) const {
+      VectorToRepeated(v, attr_->mutable_ints());
+    }
+    void operator()(const std::vector<float> &v) const {
+      VectorToRepeated(v, attr_->mutable_floats());
+    }
+    void operator()(const std::vector<std::string> &v) const {
+      VectorToRepeated(v, attr_->mutable_strings());
+    }
+    void operator()(const std::vector<bool> &v) const {
+      VectorToRepeated(v, attr_->mutable_bools());
+    }
+    void operator()(BlockDesc *desc) const {
+      attr_->set_block_idx(desc->idx());
+    }
+    void operator()(boost::blank) const { PADDLE_THROW("Unexpected branch"); }
+  };
+
+  void Sync() {
+    if (need_update_) {
+      this->op_desc_.mutable_inputs()->Clear();
+      for (auto &ipt : inputs_) {
+        auto *input = op_desc_.add_inputs();
+        input->set_parameter(ipt.first);
+        VectorToRepeated(ipt.second, input->mutable_arguments());
+      }
+
+      this->op_desc_.mutable_outputs()->Clear();
+      for (auto &opt : outputs_) {
+        auto *output = op_desc_.add_outputs();
+        output->set_parameter(opt.first);
+        VectorToRepeated(opt.second, output->mutable_arguments());
+      }
+
+      this->op_desc_.mutable_attrs()->Clear();
+      for (auto &attr : attrs_) {
+        auto *attr_desc = op_desc_.add_attrs();
+        attr_desc->set_name(attr.first);
+        attr_desc->set_type(
+            static_cast<framework::AttrType>(attr.second.which() - 1));
+        boost::apply_visitor(SetAttrDescVisitor(attr_desc), attr.second);
+      }
+
+      need_update_ = false;
+    }
+  }
+
+  OpDesc op_desc_;
+  std::unordered_map<std::string, std::vector<std::string>> inputs_;
+  std::unordered_map<std::string, std::vector<std::string>> outputs_;
+  std::unordered_map<std::string, Attribute> attrs_;
+
+  // need_update_ indicate there some local changes not be synchronized. If
+  // local changes should be synchronized, need_update_ should be set to true.
+  bool need_update_{false};
+};
+
+class BlockDescBind {
+public:
+  BlockDescBind(ProgramDescBind *prog, BlockDesc *desc)
+      : prog_(prog), desc_(desc), need_update_(false) {}
+
+  BlockDescBind(const BlockDescBind &o) = delete;
+  BlockDescBind &operator=(const BlockDescBind &o) = delete;
+
+  int32_t ID() const { return desc_->idx(); }
+
+  int32_t Parent() const { return desc_->parent_idx(); }
+
+  VarDescBind *NewVar(py::bytes name_bytes) {
+    std::string name = name_bytes;
+    need_update_ = true;
+    auto it = vars_.find(name);
+    PADDLE_ENFORCE(it == vars_.end(), "Duplicated variable %s", name);
+    auto var = new VarDescBind(name);
+    vars_[name].reset(var);
+    return var;
+  }
+
+  VarDescBind *Var(py::bytes name_bytes) const {
+    std::string name = name_bytes;
+    auto it = vars_.find(name);
+    PADDLE_ENFORCE(
+        it != vars_.end(), "Can not find variable %s in current block.", name);
+    return it->second.get();
+  }
+
+  std::vector<VarDescBind *> AllVars() const {
+    std::vector<VarDescBind *> res;
+    for (const auto &p : vars_) {
+      res.push_back(p.second.get());
+    }
+    return res;
+  }
+
+  BlockDescBind *ParentBlock() const;
+
+  OpDescBind *AppendOp() {
+    need_update_ = true;
+    ops_.emplace_back(new OpDescBind());
+    return ops_.back().get();
+  }
+
+  OpDescBind *PrependOp() {
+    need_update_ = true;
+    ops_.emplace_front(new OpDescBind());
+    return ops_.front().get();
+  }
+
+  std::vector<OpDescBind *> AllOps() const {
+    std::vector<OpDescBind *> res;
+    for (const auto &op : ops_) {
+      res.push_back(op.get());
+    }
+    return res;
+  }
+
+  void Sync() {
+    if (need_update_) {
+      auto &op_field = *this->desc_->mutable_ops();
+      op_field.Clear();
+      op_field.Reserve(static_cast<int>(ops_.size()));
+      for (auto &op_desc : ops_) {
+        op_field.AddAllocated(op_desc->Proto());
+      }
+      need_update_ = false;
+    }
+  }
+
+  BlockDesc *RawPtr() { return desc_; }
+
+private:
+  ProgramDescBind *prog_;  // not_own
+  BlockDesc *desc_;        // not_own
+  bool need_update_;
+
+  std::deque<std::unique_ptr<OpDescBind>> ops_;
+  std::unordered_map<std::string, std::unique_ptr<VarDescBind>> vars_;
+};
+
+using ProgDescMap =
+    std::unordered_map<ProgramDesc *, std::unique_ptr<ProgramDescBind>>;
+static ProgDescMap *g_bind_map = nullptr;
+
+class ProgramDescBind {
+public:
+  static ProgramDescBind &Instance(ProgramDesc *prog) {
+    if (g_bind_map == nullptr) {
+      g_bind_map = new ProgDescMap();
+    }
+    auto &map = *g_bind_map;
+    auto &ptr = map[prog];
+
+    if (ptr == nullptr) {
+      ptr.reset(new ProgramDescBind(prog));
+    }
+    return *ptr;
+  }
+  ProgramDescBind(const ProgramDescBind &o) = delete;
+  ProgramDescBind &operator=(const ProgramDescBind &o) = delete;
+
+  BlockDescBind *AppendBlock(const BlockDescBind &parent) {
+    auto *b = prog_->add_blocks();
+    b->set_parent_idx(parent.ID());
+    b->set_idx(prog_->blocks_size() - 1);
+    blocks_.emplace_back(new BlockDescBind(this, b));
+    return blocks_.back().get();
+  }
+
+  BlockDescBind *Block(size_t idx) { return blocks_[idx].get(); }
+
+  std::string DebugString() { return Proto()->DebugString(); }
+
+  size_t Size() const { return blocks_.size(); }
+
+  ProgramDesc *Proto() {
+    for (auto &block : blocks_) {
+      block->Sync();
+    }
+    return prog_;
+  }
+
+private:
+  explicit ProgramDescBind(ProgramDesc *prog) : prog_(prog) {
+    for (auto &block : *prog->mutable_blocks()) {
+      blocks_.emplace_back(new BlockDescBind(this, &block));
+    }
+  }
+
+  // Not owned
+  ProgramDesc *prog_;
+
+  std::vector<std::unique_ptr<BlockDescBind>> blocks_;
+};
+
+BlockDescBind *BlockDescBind::ParentBlock() const {
+  if (this->desc_->parent_idx() == -1) {
+    return nullptr;
+  }
+  return prog_->Block(static_cast<size_t>(this->desc_->parent_idx()));
+}
+
+void OpDescBind::SetBlockAttr(const std::string &name, BlockDescBind &block) {
+  BlockDesc *desc = block.RawPtr();
+  this->attrs_[name] = desc;
+}
+
+// Bind Methods
+void BindProgramDesc(py::module &m) {
+  py::class_<ProgramDescBind>(m, "ProgramDesc", "")
+      .def_static("instance",
+                  []() -> ProgramDescBind * {
+                    return &ProgramDescBind::Instance(&GetProgramDesc());
+                  },
+                  py::return_value_policy::reference)
+      .def_static("__create_program_desc__",
+                  []() -> ProgramDescBind * {
+                    // Only used for unit-test
+                    auto *prog_desc = new ProgramDesc;
+                    auto *block = prog_desc->mutable_blocks()->Add();
+                    block->set_idx(0);
+                    block->set_parent_idx(-1);
+                    return &ProgramDescBind::Instance(prog_desc);
+                  },
+                  py::return_value_policy::reference)
+      .def("append_block",
+           &ProgramDescBind::AppendBlock,
+           py::return_value_policy::reference)
+      .def("block", &ProgramDescBind::Block, py::return_value_policy::reference)
+      .def("__str__", &ProgramDescBind::DebugString)
+      .def("num_blocks", &ProgramDescBind::Size);
+}
+
+void BindBlockDesc(py::module &m) {
+  py::class_<BlockDescBind>(m, "BlockDesc", "")
+      .def_property_readonly("id", &BlockDescBind::ID)
+      .def_property_readonly("parent", &BlockDescBind::Parent)
+      .def("append_op",
+           &BlockDescBind::AppendOp,
+           py::return_value_policy::reference)
+      .def("prepend_op",
+           &BlockDescBind::PrependOp,
+           py::return_value_policy::reference)
+      .def(
+          "new_var", &BlockDescBind::NewVar, py::return_value_policy::reference)
+      .def("var", &BlockDescBind::Var, py::return_value_policy::reference)
+      .def("all_vars",
+           &BlockDescBind::AllVars,
+           py::return_value_policy::reference)
+      .def("all_ops",
+           &BlockDescBind::AllOps,
+           py::return_value_policy::reference);
+}
+
+void BindVarDsec(py::module &m) {
+  py::enum_<framework::DataType>(m, "DataType", "")
+      .value("BOOL", DataType::BOOL)
+      .value("INT16", DataType::INT16)
+      .value("INT32", DataType::INT32)
+      .value("INT64", DataType::INT64)
+      .value("FP16", DataType::FP16)
+      .value("FP32", DataType::FP32)
+      .value("FP64", DataType::FP64);
+
+  py::class_<VarDescBind>(m, "VarDesc", "")
+      .def("name", &VarDescBind::Name, py::return_value_policy::reference)
+      .def("set_shape", &VarDescBind::SetShape)
+      .def("set_data_type", &VarDescBind::SetDataType)
+      .def("shape", &VarDescBind::Shape, py::return_value_policy::reference)
+      .def("data_type", &VarDescBind::DataType);
+}
+
+void BindOpDesc(py::module &m) {
+  py::enum_<framework::AttrType>(m, "AttrType", "")
+      .value("INT", AttrType::INT)
+      .value("INTS", AttrType::INTS)
+      .value("FLOAT", AttrType::FLOAT)
+      .value("FLOATS", AttrType::FLOATS)
+      .value("STRING", AttrType::STRING)
+      .value("STRINGS", AttrType::STRINGS)
+      .value("BOOL", AttrType::BOOLEAN)
+      .value("BOOLS", AttrType::BOOLEANS)
+      .value("BLOCK", AttrType::BLOCK);
+
+  py::class_<OpDescBind> op_desc(m, "OpDesc", "");
+  op_desc.def("type", &OpDescBind::Type)
+      .def("set_type", &OpDescBind::SetType)
+      .def("input", &OpDescBind::Input)
+      .def("input_names", &OpDescBind::InputNames)
+      .def("set_input", &OpDescBind::SetInput)
+      .def("output", &OpDescBind::Output)
+      .def("output_names", &OpDescBind::OutputNames)
+      .def("set_output", &OpDescBind::SetOutput)
+      .def("__str__", &OpDescBind::DebugString)
+      .def("__repr__", &OpDescBind::DebugString)
+      .def("has_attr", &OpDescBind::HasAttr)
+      .def("attr_type", &OpDescBind::GetAttrType)
+      .def("attr_names", &OpDescBind::AttrNames)
+      .def("set_attr", &OpDescBind::SetAttr)
+      .def("attr", &OpDescBind::GetAttr)
+      .def("set_block_attr", &OpDescBind::SetBlockAttr)
+      .def("get_block_attr", &OpDescBind::GetBlockAttr);
+}
+
+}  // namespace pybind
+}  // namespace paddle

paddle/pybind/protobuf.h

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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 <Python.h>
+#include <fstream>
+#include <vector>
+#include "paddle/framework/op_registry.h"
+#include "pybind11/numpy.h"
+#include "pybind11/pybind11.h"
+#include "pybind11/stl.h"
+
+namespace py = pybind11;
+
+namespace paddle {
+namespace pybind {
+
+void BindProgramDesc(py::module& m);
+void BindBlockDesc(py::module& m);
+void BindVarDsec(py::module& m);
+void BindOpDesc(py::module& m);
+}  // namespace pybind
+}  // namespace paddle

paddle/pybind/pybind.cc

@@ -12,13 +12,10 @@ 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 <Python.h>
-#include <fstream>
-#include <vector>
+#include "paddle/pybind/protobuf.h"
 
 #include "paddle/framework/backward.h"
 #include "paddle/framework/lod_tensor.h"
-#include "paddle/framework/op_registry.h"
 #include "paddle/operators/cond_op.h"
 #include "paddle/operators/net_op.h"
 #include "paddle/operators/recurrent_op.h"
@@ -27,11 +24,6 @@ limitations under the License. */
 #include "paddle/pybind/pybind.h"
 #include "paddle/pybind/tensor_py.h"
 #include "paddle/string/to_string.h"
-#include "pybind11/numpy.h"
-#include "pybind11/pybind11.h"
-#include "pybind11/stl.h"
-
-namespace py = pybind11;
 
 namespace paddle {
 namespace pybind {
@@ -320,6 +312,11 @@ All parameter, weight, gradient are variables in Paddle.
 
   m.def("is_compile_gpu", IsCompileGPU);
 
+  BindProgramDesc(m);
+  BindBlockDesc(m);
+  BindVarDsec(m);
+  BindOpDesc(m);
+
   return m.ptr();
 }
 }  // namespace pybind

python/paddle/v2/framework/tests/test_modified_huber_loss_op.py

@@ -5,22 +5,31 @@ from op_test import OpTest
 
 def modified_huber_loss_forward(val):
     if val < -1:
-        return -4 * val
+        return -4. * val
     elif val < 1:
-        return (1 - val) * (1 - val)
+        return (1. - val) * (1. - val)
     else:
-        return 0
+        return 0.
 
 
 class TestModifiedHuberLossOp(OpTest):
     def setUp(self):
         self.op_type = 'modified_huber_loss'
         samples_num = 32
-        self.inputs = {
-            'X': np.random.uniform(-1, 1., (samples_num, 1)).astype('float32'),
-            'Y': np.random.choice([0, 1], samples_num).reshape((samples_num, 1))
-        }
-        product_res = self.inputs['X'] * (2 * self.inputs['Y'] - 1)
+
+        x_np = np.random.uniform(-2., 2., (samples_num, 1)).astype('float32')
+        y_np = np.random.choice([0, 1], samples_num).reshape(
+            (samples_num, 1)).astype('float32')
+        product_res = x_np * (2. * y_np - 1.)
+        # keep away from the junction of piecewise function
+        for pos, val in np.ndenumerate(product_res):
+            while abs(val - 1.) < 0.05:
+                x_np[pos] = np.random.uniform(-2., 2.)
+                y_np[pos] = np.random.choice([0, 1])
+                product_res[pos] = x_np[pos] * (2 * y_np[pos] - 1)
+                val = product_res[pos]
+
+        self.inputs = {'X': x_np, 'Y': y_np}
         loss = np.vectorize(modified_huber_loss_forward)(product_res)
 
         self.outputs = {
@@ -32,7 +41,7 @@ class TestModifiedHuberLossOp(OpTest):
         self.check_output()
 
     def test_check_grad(self):
-        self.check_grad(['X'], 'Out', max_relative_error=0.005)
+        self.check_grad(['X'], 'Out', max_relative_error=0.01)
 
 
 if __name__ == '__main__':

python/paddle/v2/framework/tests/test_protobuf_descs.py

+import unittest
+import paddle.v2.framework.core as core
+
+
+class TestOpDesc(unittest.TestCase):
+    def test_op_desc(self):
+        prog = core.ProgramDesc.__create_program_desc__()
+        self.assertIsNotNone(prog)
+        block = prog.block(0)
+        self.assertIsNotNone(block)
+        op = block.append_op()
+        self.assertIsNotNone(op)
+        op.set_type("test")
+        self.assertEqual("test", op.type())
+        op.set_input("X", ["a", "b", "c"])
+        self.assertEqual(["a", "b", "c"], op.input("X"))
+        self.assertEqual(["X"], op.input_names())
+
+        op.set_output("Out", ["z"])
+        self.assertEqual(['z'], op.output("Out"))
+        self.assertEqual(["Out"], op.output_names())
+
+        op.set_attr("int_attr", 1)
+        self.assertEqual(1, op.attr("int_attr"))
+        self.assertTrue(op.has_attr("int_attr"))
+        self.assertEqual(core.AttrType.INT, op.attr_type("int_attr"))
+
+        op.set_attr("float_attr", -1.32)
+        self.assertAlmostEqual(-1.32, op.attr("float_attr"), delta=1e-4)
+        self.assertTrue(op.has_attr("float_attr"))
+
+        op.set_attr("bool_attr", False)
+        self.assertFalse(op.attr("bool_attr"))
+
+        op.set_attr("string_attr", "abc")
+        self.assertEqual("abc", op.attr("string_attr"))
+        self.assertTrue(op.has_attr("string_attr"))
+
+        op.set_attr("ints_attr", [1, 2, 3])
+        self.assertEqual([1, 2, 3], op.attr("ints_attr"))
+
+        expected = [1.2, 2.3, 3.4]
+        op.set_attr("floats_attr", expected)
+        for e, a in zip(expected, op.attr("floats_attr")):
+            self.assertAlmostEqual(e, a, delta=1e-4)
+
+        op.set_attr("strings_attr", ["a", "b", "c"])
+        self.assertEqual(["a", "b", "c"], op.attr("strings_attr"))
+
+        op.set_attr("bools_attr", [True, False, True])
+        self.assertEqual([True, False, True], op.attr("bools_attr"))
+
+        self.assertEqual(8, len(op.attr_names()))
+
+        op.set_block_attr("block_attr", prog.block(0))
+        self.assertEqual(0, op.get_block_attr("block_attr"))
+
+
+class TestProgramDesc(unittest.TestCase):
+    def test_instance(self):
+        program_desc = core.ProgramDesc.__create_program_desc__()
+        self.assertIsNotNone(program_desc)
+        del program_desc
+        program_desc = core.ProgramDesc.instance()
+        self.assertIsNotNone(program_desc)
+        self.assertIsNotNone(program_desc.block(0))
+        del program_desc
+
+    def test_append_block(self):
+        prog_desc = core.ProgramDesc.__create_program_desc__()
+        self.assertIsNotNone(prog_desc)
+        block_root = prog_desc.block(0)
+        self.assertIsNotNone(block_root)
+        self.assertEqual(block_root.id, 0)
+        block1 = prog_desc.append_block(block_root)
+        block2 = prog_desc.append_block(block1)
+        self.assertIsNotNone(block1)
+        self.assertEqual(block1.id, block2.parent)
+        self.assertEqual(block_root.id, block1.parent)
+        block3 = prog_desc.append_block(block_root)
+        self.assertEqual(block3.parent, block_root.id)
+        self.assertEqual(prog_desc.block(1).id, 1)
+        self.assertEqual(4, prog_desc.num_blocks())
+
+
+class TestVarDesc(unittest.TestCase):
+    def test_shape(self):
+        program_desc = core.ProgramDesc.__create_program_desc__()
+        block = program_desc.block(0)
+        var = block.new_var('my_var')
+        src_shape = [3, 2, 10, 8]
+        var.set_shape(src_shape)
+        res_shape = var.shape()
+        self.assertEqual(src_shape, res_shape)
+
+    def test_data_type(self):
+        program_desc = core.ProgramDesc.__create_program_desc__()
+        block = program_desc.block(0)
+        var = block.new_var('my_var')
+        var.set_data_type(core.DataType.INT32)
+        self.assertEqual(core.DataType.INT32, var.data_type())
+
+
+class TestBlockDesc(unittest.TestCase):
+    def test_add_var(self):
+        prog = core.ProgramDesc.__create_program_desc__()
+        self.assertIsNotNone(prog)
+        block = prog.block(0)
+        self.assertIsNotNone(block)
+        var1 = block.new_var("var1")
+        var2 = block.new_var("var2")
+        var3 = block.new_var("var3")
+        all_vars = block.all_vars()
+        self.assertEqual(set(all_vars), set([var1, var2, var3]))
+        var2_re = block.var("var2")
+        self.assertEqual(var2_re, var2)
+
+    def test_add_op(self):
+        prog = core.ProgramDesc.__create_program_desc__()
+        self.assertIsNotNone(prog)
+        block = prog.block(0)
+        self.assertIsNotNone(block)
+        op1 = block.append_op()
+        op2 = block.append_op()
+        op0 = block.prepend_op()
+        all_ops = block.all_ops()
+        self.assertEqual(all_ops, [op0, op1, op2])
+
+
+if __name__ == '__main__':
+    unittest.main()