提交 72fb86a2 编写于 作者: D dongzhihong

"remove type alias done."

上级 9e25988f
......@@ -13,6 +13,7 @@
limitations under the License. */
#include "paddle/framework/backward.h"
#include <list>
#include "paddle/framework/op_registry.h"
#include "paddle/operators/net_op.h"
......
......@@ -17,16 +17,21 @@
#include <gtest/gtest.h>
#include "paddle/framework/op_registry.h"
#include "paddle/operators/net_op.h"
#include "paddle/operators/type_alias.h"
namespace paddle {
namespace framework {
using OperatorBase = framework::OperatorBase;
using OpProtoAndCheckerMaker = framework::OpProtoAndCheckerMaker;
using OpProto = framework::OpProto;
using OpAttrChecker = framework::OpAttrChecker;
using Scope = framework::Scope;
using DeviceContext = platform::DeviceContext;
class EmptyOp : public OperatorBase {
public:
void InferShape(const Scope &scope) const override {}
void Run(const Scope &scope,
const platform::DeviceContext &dev_ctx) const override {}
void Run(const Scope &scope, const DeviceContext &dev_ctx) const override {}
};
class RowWiseAddOpMaker : public OpProtoAndCheckerMaker {
......@@ -71,7 +76,7 @@ class NoGradOpMaker : public OpProtoAndCheckerMaker {
}
};
class FcOp : public ops::NetOp {
class FcOp : public operators::NetOp {
public:
void Init() override {
AddOp(OpRegistry::CreateOp("mul", {Input("X"), Input("W")},
......@@ -143,6 +148,7 @@ class AddOpMaker : public OpProtoAndCheckerMaker {
} // namespace paddle
namespace f = paddle::framework;
namespace ops = paddle::operators;
using EnforceNotMet = paddle::platform::EnforceNotMet;
REGISTER_OP(rowwise_add, f::EmptyOp, f::RowWiseAddOpMaker);
REGISTER_GRADIENT_OP(rowwise_add, rowwise_add_grad, f::EmptyOp);
......
......@@ -18,11 +18,8 @@ limitations under the License. */
#include "paddle/framework/backward.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"
#include "paddle/framework/scope.h"
#include "paddle/framework/tensor_py.h"
#include "paddle/operators/net_op.h"
#include "paddle/operators/type_alias.h"
#include "paddle/platform/enforce.h"
#include "paddle/platform/place.h"
#include "pybind11/numpy.h"
......@@ -43,6 +40,9 @@ USE_OP(rowwise_add);
USE_OP_WITHOUT_KERNEL(recurrent_op);
namespace paddle {
namespace framework {
using Tensor = framework::Tensor;
template <typename ClassType>
void ExposeOperator(ClassType &m) {
m.def("infer_shape", &ClassType::type::InferShape)
......@@ -128,8 +128,8 @@ All parameter, weight, gradient are variables in Paddle.
[](Variable &self) -> Tensor * { return self.GetMutable<Tensor>(); },
py::return_value_policy::reference)
.def("get_net",
[](Variable &self) -> ops::NetOp * {
return self.GetMutable<ops::NetOp>();
[](Variable &self) -> operators::NetOp * {
return self.GetMutable<operators::NetOp>();
},
py::return_value_policy::reference);
......@@ -208,23 +208,24 @@ All parameter, weight, gradient are variables in Paddle.
ExposeOperator(operator_base);
py::class_<ops::NetOp, std::shared_ptr<ops::NetOp>> net(m, "Net");
py::class_<operators::NetOp, std::shared_ptr<operators::NetOp>> net(m, "Net");
net.def_static("create",
[]() -> std::shared_ptr<ops::NetOp> {
auto retv = std::make_shared<ops::NetOp>();
[]() -> std::shared_ptr<operators::NetOp> {
auto retv = std::make_shared<operators::NetOp>();
retv->type_ = "plain_net";
return retv;
})
.def("add_op", &ops::NetOp::AddOp)
.def(
"add_op",
[](ops::NetOp &self, const std::shared_ptr<ops::NetOp> &net) -> void {
self.AddOp(std::static_pointer_cast<OperatorBase>(net));
})
.def("complete_add_op", &ops::NetOp::CompleteAddOp)
.def("complete_add_op",
[](std::shared_ptr<ops::NetOp> &self) { self->CompleteAddOp(); });
.def("add_op", &operators::NetOp::AddOp)
.def("add_op",
[](operators::NetOp &self,
const std::shared_ptr<operators::NetOp> &net) -> void {
self.AddOp(std::static_pointer_cast<OperatorBase>(net));
})
.def("complete_add_op", &operators::NetOp::CompleteAddOp)
.def("complete_add_op", [](std::shared_ptr<operators::NetOp> &self) {
self->CompleteAddOp();
});
ExposeOperator(net);
......
......@@ -14,7 +14,8 @@ limitations under the License. */
#include <gtest/gtest.h>
#define private public
#include <paddle/framework/op_registry.h>
#include "paddle/framework/op_registry.h"
USE_OP(add_two);
// USE_OP(add_two_grad);
......
......@@ -13,8 +13,6 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/fill_zeros_like_op.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/tensor.h"
namespace paddle {
namespace operators {
......@@ -52,8 +50,8 @@ The output will have the same size with input.
} // namespace operators
} // namespace paddle
REGISTER_OP(fill_zeros_like, paddle::operators::FillZerosLikeOp,
paddle::operators::FillZerosLikeOpMaker);
namespace ops = paddle::operators;
REGISTER_OP(fill_zeros_like, ops::FillZerosLikeOp, ops::FillZerosLikeOpMaker);
REGISTER_OP_CPU_KERNEL(
fill_zeros_like,
paddle::operators::FillZerosLikeKernel<paddle::platform::CPUPlace, float>);
ops::FillZerosLikeKernel<paddle::platform::CPUPlace, float>);
......@@ -12,9 +12,9 @@
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/framework/op_registry.h"
#include "paddle/operators/fill_zeros_like_op.h"
namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(
fill_zeros_like,
paddle::operators::FillZerosLikeKernel<paddle::platform::GPUPlace, float>);
ops::FillZerosLikeKernel<paddle::platform::GPUPlace, float>);
......@@ -13,9 +13,8 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include "glog/logging.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/operator.h"
#include "paddle/framework/op_registry.h"
namespace paddle {
namespace operators {
......
......@@ -4,26 +4,25 @@
namespace paddle {
namespace operators {
using Scope = framework::Scope;
using DeviceContext = platform::DeviceContext;
static int infer_shape_cnt = 0;
static int run_cnt = 0;
class TestOp : public OperatorBase {
class TestOp : public framework::OperatorBase {
public:
void InferShape(const framework::Scope& scope) const override {
++infer_shape_cnt;
}
void Run(const framework::Scope& scope,
const paddle::platform::DeviceContext& dev_ctx) const override {
void InferShape(const Scope& scope) const override { ++infer_shape_cnt; }
void Run(const Scope& scope,
const platform::DeviceContext& dev_ctx) const override {
++run_cnt;
}
};
class EmptyOp : public OperatorBase {
class EmptyOp : public framework::OperatorBase {
public:
void InferShape(const Scope& scope) const override {}
void Run(const Scope& scope,
const platform::DeviceContext& dev_ctx) const override {}
void Run(const Scope& scope, const DeviceContext& dev_ctx) const override {}
};
template <typename T>
......@@ -69,7 +68,7 @@ TEST(OpKernel, all) {
net->Run(scope, dev_ctx);
ASSERT_EQ(2, infer_shape_cnt);
ASSERT_EQ(2, run_cnt);
ASSERT_THROW(net->AddOp(op2), paddle::platform::EnforceNotMet);
ASSERT_THROW(net->AddOp(op2), platform::EnforceNotMet);
}
TEST(NetOp, insert_op) {
......
/* 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 <Python.h>
#include <fstream>
#include <vector>
#include "paddle/framework/net.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"
#include "paddle/framework/scope.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);
USE_OP_WITHOUT_KERNEL(fc);
USE_OP(sgd);
USE_OP(mul);
USE_OP(mean);
USE_OP(sigmoid);
USE_OP(softmax);
USE_OP(rowwise_add);
USE_OP_WITHOUT_KERNEL(recurrent_op);
template <typename ClassType>
void ExposeOperator(ClassType& m) {
m.def("infer_shape", &ClassType::type::InferShape)
.def("run", &ClassType::type::Run)
.def("outputs",
[](const typename ClassType::type& op) -> std::vector<std::string> {
return op.outputs_;
})
.def("__str__", &ClassType::type::DebugString);
}
static size_t UniqueIntegerGenerator() {
static std::atomic<size_t> generator;
return generator.fetch_add(1);
}
bool IsCompileGPU() {
#ifdef PADDLE_ONLY_CPU
return false;
#else
return true;
#endif
}
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);
})
.def("get_dims",
[](const pd::Tensor& self) { return pd::vectorize(self.dims()); })
.def("set_dims",
[](pd::Tensor& self, const std::vector<int>& dim) {
self.Resize(pd::make_ddim(dim));
})
.def("alloc_float",
[](pd::Tensor& self, paddle::platform::GPUPlace& place) {
self.mutable_data<float>(place);
})
.def("alloc_float",
[](pd::Tensor& self, paddle::platform::CPUPlace& place) {
self.mutable_data<float>(place);
})
.def("alloc_int",
[](pd::Tensor& self, paddle::platform::CPUPlace& place) {
self.mutable_data<int>(place);
})
.def("alloc_int",
[](pd::Tensor& self, paddle::platform::GPUPlace& place) {
self.mutable_data<int>(place);
})
.def("set", paddle::pybind::PyCPUTensorSetFromArray<float>)
.def("set", paddle::pybind::PyCPUTensorSetFromArray<int>)
#ifndef PADDLE_ONLY_CPU
.def("set", paddle::pybind::PyCUDATensorSetFromArray<float>)
.def("set", paddle::pybind::PyCUDATensorSetFromArray<int>)
#endif
.def("shape",
[](pd::Tensor& self) { return pd::vectorize(self.dims()); });
py::class_<pd::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("set_int",
[](pd::Variable& var, int val) -> void {
*var.GetMutable<int>() = val;
})
.def("get_int",
[](const pd::Variable& var) -> int { return var.Get<int>(); })
.def("get_tensor",
[](pd::Variable& self) -> pd::Tensor* {
return self.GetMutable<pd::Tensor>();
},
py::return_value_policy::reference)
.def("get_net",
[](pd::Variable& self) -> pd::NetOp* {
return self.GetMutable<pd::NetOp>();
},
py::return_value_policy::reference);
py::class_<pd::Scope>(m, "Scope", "")
.def("new_var",
[](pd::Scope& self, const std::string& name) -> pd::Variable* {
return self.NewVar(name);
},
py::return_value_policy::reference)
.def("find_var", &pd::Scope::FindVar, py::return_value_policy::reference)
.def(py::init<>())
.def("new_scope",
[](pd::Scope& self) -> pd::Scope* { return &self.NewScope(); },
py::return_value_policy::reference)
.def("drop_kids", &pd::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();
std::vector<py::bytes> ret_values;
for (auto it = protos.begin(); it != protos.end(); ++it) {
PADDLE_ENFORCE(it->second.IsInitialized(),
"OpProto must all be initialized");
std::string str;
PADDLE_ENFORCE(it->second.SerializeToString(&str),
"Serialize OpProto Error. This could be a bug of Paddle.");
ret_values.push_back(py::bytes(str));
}
return ret_values;
});
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);
// clang-format off
py::class_<paddle::platform::DeviceContext>(m, "DeviceContext")
.def_static("create",
[](paddle::platform::CPUPlace& place)
-> paddle::platform::DeviceContext* {
return new paddle::platform::CPUDeviceContext();
})
.def_static("create",
[](paddle::platform::GPUPlace& place)
-> paddle::platform::DeviceContext* {
#ifdef PADDLE_ONLY_CPU
PADDLE_THROW("GPUPlace is not supported in CPU device.");
#else
return new paddle::platform::CUDADeviceContext(place);
#endif
});
// clang-format on
py::class_<paddle::platform::GPUPlace>(m, "GPUPlace").def(py::init<int>());
py::class_<paddle::platform::CPUPlace>(m, "CPUPlace").def(py::init<>());
py::class_<pd::OperatorBase, std::shared_ptr<pd::OperatorBase>> operator_base(
m, "Operator");
operator_base.def_static("create", [](py::bytes protobin) {
pd::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);
});
ExposeOperator(operator_base);
py::class_<pd::NetOp, std::shared_ptr<pd::NetOp>> net(m, "Net");
net.def_static("create",
[]() -> std::shared_ptr<pd::NetOp> {
auto retv = std::make_shared<pd::NetOp>();
retv->type_ = "plain_net";
return retv;
})
.def("add_op", &pd::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));
})
.def("complete_add_op", &pd::NetOp::CompleteAddOp)
.def("complete_add_op",
[](std::shared_ptr<pd::NetOp>& self) { self->CompleteAddOp(); });
ExposeOperator(net);
m.def("unique_integer", UniqueIntegerGenerator);
m.def("is_compile_gpu", IsCompileGPU);
return m.ptr();
}
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