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Dev ivalue for cpp api #6890
Dev ivalue for cpp api #6890
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Original file line number | Diff line number | Diff line change |
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/* | ||
Copyright 2020 The OneFlow Authors. All rights reserved. | ||
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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 | ||
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http://www.apache.org/licenses/LICENSE-2.0 | ||
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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 "oneflow/api/cpp/framework/ivalue.h" | ||
#include <glog/logging.h> | ||
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namespace oneflow_api { | ||
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namespace of = oneflow; | ||
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std::ostream& operator<<(std::ostream& os, const IValue::Tag& tag) { | ||
os << static_cast<int>(tag); | ||
return os; | ||
} | ||
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bool IValue::IsNone() { return tag_ == Tag::kNone; } | ||
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bool IValue::IsInt() { return tag_ == Tag::kInt; } | ||
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bool IValue::IsDouble() { return tag_ == Tag::kDouble; } | ||
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bool IValue::IsBool() { return tag_ == Tag::kBool; } | ||
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bool IValue::IsTensor() { return tag_ == Tag::kTensor; } | ||
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bool IValue::IsTensorVector() { return tag_ == Tag::kTensorVector; } | ||
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const int64_t IValue::ToInt() const { | ||
CHECK_EQ(tag_, Tag::kInt) << "Current value is not an int."; | ||
return payload_.i.v_int; | ||
} | ||
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const double IValue::ToDouble() const { | ||
CHECK_EQ(tag_, Tag::kDouble) << "Current value is not a double."; | ||
return payload_.i.v_double; | ||
} | ||
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const bool IValue::ToBool() const { | ||
CHECK_EQ(tag_, Tag::kBool) << "Current value is not a bool."; | ||
return payload_.i.v_bool; | ||
} | ||
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const Tensor& IValue::ToTensor() const { | ||
CHECK_EQ(tag_, Tag::kTensor) << "Current value is not a tensor."; | ||
return payload_.v_tensor; | ||
} | ||
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const std::vector<Tensor>& IValue::ToTensorVector() const { | ||
CHECK_EQ(tag_, Tag::kTensorVector) << "Current value is not a vector of tensor."; | ||
return payload_.v_tensor_vector; | ||
} | ||
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} // namespace oneflow_api |
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/* | ||
Copyright 2020 The OneFlow Authors. All rights reserved. | ||
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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 | ||
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http://www.apache.org/licenses/LICENSE-2.0 | ||
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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. | ||
*/ | ||
#ifndef ONEFLOW_API_CPP_FRAMEWORK_IVALUE_H_ | ||
#define ONEFLOW_API_CPP_FRAMEWORK_IVALUE_H_ | ||
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#include <cstdint> | ||
#include <memory> | ||
#include <vector> | ||
#include "tensor.h" | ||
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namespace oneflow_api { | ||
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class IValue { | ||
public: | ||
IValue() : tag_(IValue::Tag::kNone) {} | ||
explicit IValue(int value) : tag_(IValue::Tag::kInt) { payload_.i.v_int = value; } | ||
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explicit IValue(int64_t value) : tag_(IValue::Tag::kInt) { payload_.i.v_int = value; } | ||
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explicit IValue(double value) : tag_(IValue::Tag::kDouble) { payload_.i.v_double = value; } | ||
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explicit IValue(bool value) : tag_(IValue::Tag::kBool) { payload_.i.v_bool = value; } | ||
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IValue(const Tensor& value) : tag_(IValue::Tag::kTensor) { // NOLINT | ||
new (&payload_.v_tensor) Tensor(value); | ||
} | ||
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IValue(Tensor&& value) : tag_(IValue::Tag::kTensor) { // NOLINT | ||
new (&payload_.v_tensor) Tensor(std::move(value)); | ||
} | ||
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IValue(const std::vector<Tensor>& value) : tag_(IValue::Tag::kTensorVector) { // NOLINT | ||
new (&payload_.v_tensor_vector) std::vector<Tensor>(value); | ||
} | ||
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IValue(std::vector<Tensor>&& value) : tag_(IValue::Tag::kTensorVector) { // NOLINT | ||
new (&payload_.v_tensor_vector) std::vector<Tensor>(std::move(value)); | ||
} | ||
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IValue(const IValue& value) : tag_(value.tag_) { | ||
if (IsTensor()) { | ||
new (&payload_.v_tensor) Tensor(value.payload_.v_tensor); | ||
} else if (IsTensorVector()) { | ||
new (&payload_.v_tensor_vector) std::vector<Tensor>(value.payload_.v_tensor_vector); | ||
} else { | ||
payload_.i = value.payload_.i; | ||
} | ||
} | ||
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IValue(IValue&& value) noexcept : tag_(value.tag_) { MoveFrom(std::move(value)); } | ||
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IValue& operator=(const IValue& value) { | ||
if (&value == this) { return *this; } | ||
this->tag_ = value.tag_; | ||
*this = IValue(value); | ||
return *this; | ||
} | ||
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IValue& operator=(IValue&& value) noexcept { | ||
if (&value == this) { return *this; } | ||
Destory(); | ||
this->tag_ = value.tag_; | ||
MoveFrom(std::move(value)); | ||
return *this; | ||
} | ||
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~IValue() { Destory(); } | ||
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bool IsNone(); | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. bool IsX() const,另外这种特别简单的方法可以考虑在头文件定义,便于内联优化。 There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 好的 |
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bool IsInt(); | ||
bool IsDouble(); | ||
bool IsBool(); | ||
bool IsTensor(); | ||
bool IsTensorVector(); | ||
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const int64_t ToInt() const; | ||
const double ToDouble() const; | ||
const bool ToBool() const; | ||
const Tensor& ToTensor() const; | ||
const std::vector<Tensor>& ToTensorVector() const; | ||
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private: | ||
enum class Tag { kNone = 0, kInt = 1, kDouble = 2, kBool = 3, kTensor = 4, kTensorVector = 5 }; | ||
friend std::ostream& operator<<(std::ostream&, const Tag&); | ||
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union Payload { // NOLINT | ||
union InternalPayload { | ||
InternalPayload() : v_int(0) {} | ||
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int64_t v_int; | ||
double v_double; | ||
bool v_bool; | ||
} i; | ||
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Tensor v_tensor; | ||
std::vector<Tensor> v_tensor_vector; | ||
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Payload() : i() {} | ||
~Payload() {} | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. union 在析构的时候是不会主动析构 field 的,当构造了 Tensor 或者 vector 之后它们析构函数不会被调用,这样会造成内存泄露 There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. union 中包含 non POD type 的时候处理所有权和生命周期要非常小心 There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 对 所以在IValue析构函数里面处理了union的析构 There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 哦哦,抱歉没看到。感觉构造/析构函数写在头文件好一些,方便内联优化。 There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 有道理 |
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}; | ||
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Payload payload_; | ||
Tag tag_; | ||
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inline void Destory() { | ||
if (IsTensor()) { payload_.v_tensor.~Tensor(); } | ||
if (IsTensorVector()) { payload_.v_tensor_vector.~vector(); } | ||
} | ||
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inline void MoveFrom(IValue&& value) { | ||
if (IsTensor()) { | ||
new (&payload_.v_tensor) Tensor(std::move(value.payload_.v_tensor)); | ||
} else if (IsTensorVector()) { | ||
new (&payload_.v_tensor_vector) | ||
std::vector<Tensor>(std::move(value.payload_.v_tensor_vector)); | ||
} else { | ||
payload_.i = value.payload_.i; | ||
} | ||
value.ClearToNone(); | ||
} | ||
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inline void ClearToNone() { | ||
Destory(); | ||
payload_.i.v_int = 0; | ||
tag_ = Tag::kNone; | ||
} | ||
}; | ||
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} // namespace oneflow_api | ||
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#endif // ONEFLOW_API_CPP_FRAMEWORK_IVALUE_H_ |
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@@ -14,7 +14,6 @@ See the License for the specific language governing permissions and | |
limitations under the License. | ||
*/ | ||
#include "oneflow/api/cpp/framework/tensor.h" | ||
#include <memory> | ||
#include "oneflow/api/cpp/framework/device.h" | ||
#include "oneflow/api/cpp/framework/dtype.h" | ||
#include "oneflow/api/cpp/framework/shape.h" | ||
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} | ||
Tensor::Tensor(const std::shared_ptr<oneflow::one::Tensor>& tensor) : tensor_(tensor) {} | ||
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Tensor::Tensor(const Tensor& tensor) : tensor_(tensor.tensor_) {} | ||
Tensor::Tensor(Tensor&& tensor) noexcept : tensor_(std::move(tensor.tensor_)) {} | ||
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Tensor::~Tensor() {} | ||
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Tensor& Tensor::operator=(const Tensor& tensor) { | ||
tensor_.reset(); | ||
tensor_ = tensor.tensor_; | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 感觉 operator= 之前不需要 reset,下同。reset 相当于 shared_ptr().swap(*this),operator= 相当于 shared_ptr(v).swap(*this),都会调临时对象的 dtor There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 好的 |
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return *this; | ||
} | ||
Tensor& Tensor::operator=(Tensor&& tensor) noexcept { | ||
tensor_.reset(); | ||
tensor_ = std::move(tensor.tensor_); | ||
return *this; | ||
} | ||
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const Shape Tensor::shape() const { | ||
const auto shape_ = tensor_->shape(); | ||
return Shape(std::vector<int64_t>(shape_->dim_vec().begin(), shape_->dim_vec().end())); | ||
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explicit Tensor(const Shape& shape = Shape(), const Device& device = Device("cpu"), | ||||||
const DType& dtype = DType::kFloat); | ||||||
explicit Tensor(const std::shared_ptr<oneflow::one::Tensor>& tensor); | ||||||
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Tensor(const Tensor& tensor); | ||||||
Tensor(Tensor&& tensor) noexcept; | ||||||
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~Tensor(); | ||||||
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Suggested change
然后可以删去 .cpp 内的 |
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Tensor& operator=(const Tensor& tensor); | ||||||
Tensor& operator=(Tensor&& tensor) noexcept; | ||||||
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[[nodiscard]] const Shape shape() const; | ||||||
[[nodiscard]] const Device device() const; | ||||||
[[nodiscard]] const DType dtype() const; | ||||||
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} // namespace oneflow_api | ||||||
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#endif // !ONEFLOW_API_CPP_FRAMEWORK_TENSOR_H_ | ||||||
#endif // ONEFLOW_API_CPP_FRAMEWORK_TENSOR_H_ |
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这些 explicit 是不是可以去掉,这样 Graph::Forward 的参数类型是 IValue 的话,用户仍然可以写 graph.Forward(tensor)
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那所有的构造函数都去掉explicit还是只去掉tensor和tensor_vector的?
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只去掉tensor和tensor_vector的吧
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好的