提交 809793c9 编写于 作者: Y Yu Yang 提交者: GitHub

Merge pull request #3173 from reyoung/feature/move_pybind_to_framework_dir

Move pybind.cc/tensor_bind.h to paddle::framework
......@@ -15,7 +15,6 @@ if(Boost_FOUND)
add_subdirectory(platform)
add_subdirectory(framework)
add_subdirectory(operators)
add_subdirectory(pybind)
endif()
if(WITH_C_API)
......
......@@ -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)
......@@ -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
......@@ -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;
......
......@@ -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
......
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