Merge pull request #3173 from reyoung/feature/move_pybind_to_framework_dir

Move pybind.cc/tensor_bind.h to paddle::framework

Author: reyoung

paddle/CMakeLists.txt

@@ -15,7 +15,6 @@ if(Boost_FOUND)
  add_subdirectory(platform)
  add_subdirectory(framework)
  add_subdirectory(operators)
- add_subdirectory(pybind)
 endif()
 
 if(WITH_C_API)

paddle/framework/CMakeLists.txt

@@ -36,3 +36,12 @@ cc_test(net_op_test SRCS net_op_test.cc DEPS net)
 
 cc_library(backward SRCS backward.cc DEPS net)
 cc_test(backward_test SRCS backward_test.cc DEPS backward)
+cc_library(paddle_pybind SHARED
+ SRCS pybind.cc
+ DEPS pybind python backward
+fc_op
+sgd_op
+add_op
+mean_op
+cross_entropy_op
+recurrent_op)

paddle/pybind/pybind.cc renamed to paddle/framework/pybind.cc

@@ -4,7 +4,7 @@ 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
+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,
@@ -21,15 +21,14 @@ limitations under the License. */
 #include "paddle/framework/op_registry.h"
 #include "paddle/framework/operator.h"
 #include "paddle/framework/scope.h"
+#include "paddle/framework/tensor_py.h"
 #include "paddle/platform/enforce.h"
 #include "paddle/platform/place.h"
-#include "paddle/pybind/tensor_bind.h"
 #include "pybind11/numpy.h"
 #include "pybind11/pybind11.h"
 #include "pybind11/stl.h"
 
 namespace py = pybind11;
-namespace pd = paddle::framework;
 
 USE_OP(add_two);
 USE_OP(onehot_cross_entropy);
@@ -41,17 +40,18 @@ USE_OP(sigmoid);
 USE_OP(softmax);
 USE_OP(rowwise_add);
 USE_OP_WITHOUT_KERNEL(recurrent_op);
-
+namespace paddle {
+namespace framework {
 template <typename ClassType>
-void ExposeOperator(ClassType& m) {
+void ExposeOperator(ClassType &m) {
  m.def("infer_shape", &ClassType::type::InferShape)
  .def("run", &ClassType::type::Run)
  .def("type",
- [](const typename ClassType::type& op) -> std::string {
+ [](const typename ClassType::type &op) -> std::string {
  return op.type_;
  })
  .def("outputs",
- [](const typename ClassType::type& op) -> std::vector<std::string> {
+ [](const typename ClassType::type &op) -> std::vector<std::string> {
  return op.outputs_;
  })
  .def("__str__", &ClassType::type::DebugString);
@@ -73,80 +73,70 @@ bool IsCompileGPU() {
 PYBIND11_PLUGIN(core) {
  py::module m("core", "C++ core of PaddlePaddle");
 
- py::class_<pd::Tensor>(m, "Tensor", py::buffer_protocol())
- .def_buffer([](pd::Tensor& self) -> py::buffer_info {
- return paddle::pybind::CastToPyBuffer(self);
- })
+ py::class_<Tensor>(m, "Tensor", py::buffer_protocol())
+ .def_buffer(
+ [](Tensor &self) -> py::buffer_info { return CastToPyBuffer(self); })
  .def("get_dims",
- [](const pd::Tensor& self) { return pd::vectorize(self.dims()); })
+ [](const Tensor &self) { return vectorize(self.dims()); })
  .def("set_dims",
- [](pd::Tensor& self, const std::vector<int>& dim) {
- self.Resize(pd::make_ddim(dim));
+ [](Tensor &self, const std::vector<int> &dim) {
+ self.Resize(make_ddim(dim));
  })
  .def("alloc_float",
- [](pd::Tensor& self, paddle::platform::GPUPlace& place) {
+ [](Tensor &self, paddle::platform::GPUPlace &place) {
  self.mutable_data<float>(place);
  })
  .def("alloc_float",
- [](pd::Tensor& self, paddle::platform::CPUPlace& place) {
+ [](Tensor &self, paddle::platform::CPUPlace &place) {
  self.mutable_data<float>(place);
  })
  .def("alloc_int",
- [](pd::Tensor& self, paddle::platform::CPUPlace& place) {
+ [](Tensor &self, paddle::platform::CPUPlace &place) {
  self.mutable_data<int>(place);
  })
  .def("alloc_int",
- [](pd::Tensor& self, paddle::platform::GPUPlace& place) {
+ [](Tensor &self, paddle::platform::GPUPlace &place) {
  self.mutable_data<int>(place);
  })
- .def("set", paddle::pybind::PyCPUTensorSetFromArray<float>)
- .def("set", paddle::pybind::PyCPUTensorSetFromArray<int>)
+ .def("set", PyCPUTensorSetFromArray<float>)
+ .def("set", PyCPUTensorSetFromArray<int>)
 #ifndef PADDLE_ONLY_CPU
- .def("set", paddle::pybind::PyCUDATensorSetFromArray<float>)
- .def("set", paddle::pybind::PyCUDATensorSetFromArray<int>)
+ .def("set", PyCUDATensorSetFromArray<float>)
+ .def("set", PyCUDATensorSetFromArray<int>)
 #endif
- .def("shape",
- [](pd::Tensor& self) { return pd::vectorize(self.dims()); });
+ .def("shape", [](Tensor &self) { return vectorize(self.dims()); });
 
- py::class_<pd::Variable>(m, "Variable", R"DOC(Variable Class.
+ py::class_<Variable>(m, "Variable", R"DOC(Variable Class.
 
 All parameter, weight, gradient are variables in Paddle.
 )DOC")
- .def("is_int", [](const pd::Variable& var) { return var.IsType<int>(); })
+ .def("is_int", [](const Variable &var) { return var.IsType<int>(); })
  .def("set_int",
- [](pd::Variable& var, int val) -> void {
- *var.GetMutable<int>() = val;
- })
- .def("get_int",
- [](const pd::Variable& var) -> int { return var.Get<int>(); })
+ [](Variable &var, int val) -> void { *var.GetMutable<int>() = val; })
+ .def("get_int", [](const Variable &var) -> int { return var.Get<int>(); })
  .def("get_tensor",
- [](pd::Variable& self) -> pd::Tensor* {
- return self.GetMutable<pd::Tensor>();
- },
+ [](Variable &self) -> Tensor * { return self.GetMutable<Tensor>(); },
  py::return_value_policy::reference)
  .def("get_net",
- [](pd::Variable& self) -> pd::NetOp* {
- return self.GetMutable<pd::NetOp>();
- },
+ [](Variable &self) -> NetOp * { return self.GetMutable<NetOp>(); },
  py::return_value_policy::reference);
 
- py::class_<pd::Scope>(m, "Scope", "")
+ py::class_<Scope>(m, "Scope", "")
  .def("new_var",
- [](pd::Scope& self, const std::string& name) -> pd::Variable* {
+ [](Scope &self, const std::string &name) -> Variable * {
  return self.NewVar(name);
  },
  py::return_value_policy::reference)
- .def("find_var", &pd::Scope::FindVar, py::return_value_policy::reference)
+ .def("find_var", &Scope::FindVar, py::return_value_policy::reference)
  .def(py::init<>())
- .def("new_scope",
- [](pd::Scope& self) -> pd::Scope* { return &self.NewScope(); },
+ .def("new_scope", [](Scope &self) -> Scope * { return &self.NewScope(); },
  py::return_value_policy::reference)
- .def("drop_kids", &pd::Scope::DropKids);
+ .def("drop_kids", &Scope::DropKids);
 
  //! @note: Be careful! PyBind will return std::string as an unicode, not
  //! Python str. If you want a str object, you should cast them in Python.
  m.def("get_all_op_protos", []() -> std::vector<py::bytes> {
- auto& protos = pd::OpRegistry::protos();
+ auto &protos = OpRegistry::protos();
  std::vector<py::bytes> ret_values;
  for (auto it = protos.begin(); it != protos.end(); ++it) {
  PADDLE_ENFORCE(it->second.IsInitialized(),
@@ -161,8 +151,8 @@ All parameter, weight, gradient are variables in Paddle.
  m.def_submodule(
  "var_names",
  "The module will return special predefined variable name in Paddle")
- .def("empty", pd::OperatorBase::EMPTY_VAR_NAME)
- .def("temp", pd::OperatorBase::TMP_VAR_NAME);
+ .def("empty", OperatorBase::EMPTY_VAR_NAME)
+ .def("temp", OperatorBase::TMP_VAR_NAME);
  // clang-format off
  py::class_<paddle::platform::DeviceContext>(m, "DeviceContext")
  .def_static("create",
@@ -185,43 +175,43 @@ All parameter, weight, gradient are variables in Paddle.
 
  py::class_<paddle::platform::CPUPlace>(m, "CPUPlace").def(py::init<>());
 
- py::class_<pd::OperatorBase, std::shared_ptr<pd::OperatorBase>> operator_base(
+ py::class_<OperatorBase, std::shared_ptr<OperatorBase>> operator_base(
  m, "Operator");
 
  operator_base.def_static("create", [](py::bytes protobin) {
- pd::OpDesc desc;
+ OpDesc desc;
  PADDLE_ENFORCE(desc.ParsePartialFromString(protobin),
  "Cannot parse user input to OpDesc");
  PADDLE_ENFORCE(desc.IsInitialized(),
  "User OpDesc is not initialized, reason %s",
  desc.InitializationErrorString());
- return pd::OpRegistry::CreateOp(desc);
+ return OpRegistry::CreateOp(desc);
  });
 
  operator_base.def("backward",
- [](const pd::OperatorBase& forwardOp,
- const std::unordered_set<std::string>& no_grad_vars) {
- return pd::Backward(forwardOp, no_grad_vars);
+ [](const OperatorBase &forwardOp,
+ const std::unordered_set<std::string> &no_grad_vars) {
+ return Backward(forwardOp, no_grad_vars);
  });
 
  ExposeOperator(operator_base);
 
- py::class_<pd::NetOp, std::shared_ptr<pd::NetOp>> net(m, "Net");
+ py::class_<NetOp, std::shared_ptr<NetOp>> net(m, "Net");
 
  net.def_static("create",
- []() -> std::shared_ptr<pd::NetOp> {
- auto retv = std::make_shared<pd::NetOp>();
+ []() -> std::shared_ptr<NetOp> {
+ auto retv = std::make_shared<NetOp>();
  retv->type_ = "plain_net";
  return retv;
  })
- .def("add_op", &pd::NetOp::AddOp)
+ .def("add_op", &NetOp::AddOp)
  .def("add_op",
- [](pd::NetOp& self, const std::shared_ptr<pd::NetOp>& net) -> void {
- self.AddOp(std::static_pointer_cast<pd::OperatorBase>(net));
+ [](NetOp &self, const std::shared_ptr<NetOp> &net) -> void {
+ self.AddOp(std::static_pointer_cast<OperatorBase>(net));
  })
- .def("complete_add_op", &pd::NetOp::CompleteAddOp)
+ .def("complete_add_op", &NetOp::CompleteAddOp)
  .def("complete_add_op",
- [](std::shared_ptr<pd::NetOp>& self) { self->CompleteAddOp(); });
+ [](std::shared_ptr<NetOp> &self) { self->CompleteAddOp(); });
  ExposeOperator(net);
 
  m.def("unique_integer", UniqueIntegerGenerator);
@@ -230,3 +220,5 @@ All parameter, weight, gradient are variables in Paddle.
 
  return m.ptr();
 }
+} // namespace framework
+} // namespace paddle

paddle/framework/tensor.h

@@ -26,19 +26,17 @@ limitations under the License. */
 #include "unsupported/Eigen/CXX11/Tensor"
 
 namespace paddle {
-namespace pybind {
-namespace details { // forward declare
-template <bool less, size_t i, typename... args>
-struct CastToPyBufferImpl;
-} // namespace details
-} // namespace pybind
 
 namespace framework {
+namespace details {
+template <bool less, size_t i, typename... args>
+struct CastToPyBufferImpl;
+}
 
 class Tensor {
  public:
  template <bool less, size_t i, typename... args>
- friend struct paddle::pybind::details::CastToPyBufferImpl;
+ friend struct details::CastToPyBufferImpl;
 
  template <typename T, size_t D, int MajorType, typename IndexType>
  friend struct EigenTensor;

paddle/pybind/tensor_bind.h renamed to paddle/framework/tensor_py.h

@@ -23,7 +23,7 @@ namespace py = pybind11;
 
 namespace paddle {
 
-namespace pybind {
+namespace framework {
 
 namespace details {
 
@@ -63,11 +63,8 @@ struct CastToPyBufferImpl<true, I, ARGS...> {
  }
  return py::buffer_info(
  dst_tensor.mutable_data<CUR_TYPE>(dst_tensor.holder_->place()),
- sizeof(CUR_TYPE),
- py::format_descriptor<CUR_TYPE>::format(),
- (size_t)framework::arity(dst_tensor.dims()),
- dims_outside,
- strides);
+ sizeof(CUR_TYPE), py::format_descriptor<CUR_TYPE>::format(),
+ (size_t)framework::arity(dst_tensor.dims()), dims_outside, strides);
  } else {
  constexpr bool less = I + 1 < std::tuple_size<std::tuple<ARGS...>>::value;
  return CastToPyBufferImpl<less, I + 1, ARGS...>()(tensor);
@@ -110,8 +107,8 @@ void PyCUDATensorSetFromArray(
 
  self.Resize(framework::make_ddim(dims));
  auto *dst = self.mutable_data<T>(place);
- paddle::platform::GpuMemcpySync(
- dst, array.data(), sizeof(T) * array.size(), cudaMemcpyHostToDevice);
+ paddle::platform::GpuMemcpySync(dst, array.data(), sizeof(T) * array.size(),
+   cudaMemcpyHostToDevice);
 }
 #endif