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tensor draft for review #2645

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32 changes: 32 additions & 0 deletions paddle/framework/tensor.cc
Original file line number Diff line number Diff line change
@@ -0,0 +1,32 @@
#include "paddle/framework/tensor.h"

namespace paddle {
namespace framework {

int Tensor::Rank() const { return arity(dims_); }

int Tensor::Numel() const { return product(dims_); }

void Tensor::Resize(const DDim& dims) {
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In my design, I don't see that we need Resize. Indeed, I followed @qingqing01 's suggestion and removed the ability of the constructor to set the size.

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@JiayiFeng JiayiFeng Jun 29, 2017

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Do you mean that if users want to change tensor's size, they can invoke mutable_data(DDim) directly?

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Yes.

dims_ = dims;
return;
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Why add so many return at the end of a void func()

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@JiayiFeng JiayiFeng Jun 28, 2017

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It's just my personal habit... I'm used to adding return; to mark all return points of a void function.
Of course, they can be removed, if they break common code style or might cause confusion.

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Please strictly follow a common style as we work as a team. Let's remove all unnecessary code.

}

void Tensor::Reshape(const DDim& dims) {
if (product(dims) != product(dims_)) {
// TODO: error: "Reshape() can not change tensor's numel".
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Why can not reshape change tensor's numel?

In each mini-batch training, each output of Op should be Reshape, because the shape of input tensor could be changed.

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Users can use Resize() to change tensor's numel.

}
dims_ = dims;
return;
}

const std::shared_ptr<Tensor::Placeholder>& Tensor::Holder() const {
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I think that users don't need to and shouldn't know the concept "holder", which is defined as a private type inside Tensor in my design.

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done

return holder_;
}

const DDim& Tensor::Dims() const { return dims_; }
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Put these simple functions into the header file, the compiler can do inline optimization.

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done


const paddle::platform::Place& Tensor::Place() const { return place_; }

} // namespace framework
} // namespace paddle
138 changes: 138 additions & 0 deletions paddle/framework/tensor.h
Original file line number Diff line number Diff line change
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#pragma once

#include <memory>
#include <type_traits>
#include <typeinfo>
#include "paddle/framework/ddim.h"
#include "paddle/platform/assert.h"
#include "paddle/platform/place.h"

namespace paddle {
namespace framework {

class Tensor {
using paddle::platform::Place;
using paddle::platform::get_place;

public:
explicit Tensor(DDim dims) : dims_(dims), place_(get_place()) {}
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Please be aware that I followed @qingqing01 's suggestion 3 days ago #2611 (review) and removed Tensor::Tensor, Tensor::place_, Tensor::dims_ in my PR #2611 so to make a concise and consistent syntax.

explicit Tensor(DDim dims, Place place) : dims_(dims), place_(place) {}

Tensor& operator=(const Tensor& src) = delete;

template <typename T>
const T* Data() const {
PADDLE_ASSERT(holder_ != nullptr);
PADDLE_ASSERT(holder_->Place() == place_);
PADDLE_ASSERT(holder_->Size() >= product(dims_) * sizeof(T));
return static_cast<const T*>(holder->Ptr());
}

template <typename T>
bool NeedReset() const {
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I think @hedaoyuan 's comment means these functions can be inlined by using inline keyword.

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I think there is no inline keyword that will also be inline.

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NeedReset is not something should be exposed.

return (holder_ == nullptr || holder_->Place() != place_ ||
holder_->Size() < product(dims_) * sizeof(T));
}

// must be POD types
template <typename T, typename = std::enable_if<std::is_pod<T>::value>::type>
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Also, I followed @qingqing01 's suggestion and removed multiple signatures of mutable_data.

T* MutableData() {
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Please follow Google C++ style guide carefully -- there is a reason there of using the name mutable_data.

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Accessors and mutators (get and set functions) may be named like variables. These often correspond to actual member variables, but this is not required.

Yes, it' ok to using mutable_data().

By the way, do we need to rename functions in DDim and Place to follow Google C++ style?

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I think it is a good idea.

if (NeedReset<T>()) {
holder_.reset(new PlaceholderImpl(place_, product(dims_) * sizeof(T)));
}
return static_cast<T*>(holder_->Ptr());
}

template <typename T, typename = std::enable_if<std::is_pod<T>::value>::type>
T* MutableData(const DDim& dims) {
dims_ = dims;
return MutableData<T>();
}

template <typename T, typename = std::enable_if<std::is_pod<T>::value>::type>
T* MutableData(const DDim& dims, const Place& place) {
dims_ = dims;
place_ = place;
return MutableData<T>();
}

int Rank() const;

int Numel() const;

void Resize(const DDim& dims);

void Reshape(const DDim& dims);

template <typename T>
void ShareData(const Tensor& src) {
if (src.NeedReset<T>()) {
// TODO: error: "Src tensor need to be reseted before calling
// ShareData()".
}
holder_ = src.Holder();
dims_ = src.Dims();
place_ = src.Place();
return;
}

template <typename T>
void CopyFrom(const Tensor& src) {
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Why we need CopyFrom?

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We may need CopyFrom when the src Tensor is on GPU. We may need to copy GPU Tensor to CPU and do something such as writing to a file.

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@JiayiFeng JiayiFeng Jun 29, 2017

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I agree with @Xreki .

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@wangkuiyi wangkuiyi Jun 29, 2017

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Sounds like what we need is a method Serialize that fills in a protobuf message; instead a Copy or CopyFrom?

void Tensor::Serialize(TensorProto* proto) {
  if (is_gpu_place(Place()) {
    Tensor cpu_tensor;
    cudaMemcpy(cpu_tensor.mutable_data(Size(), CPUPlace()), data(), Size());
    cpu_tensor.Serialize(proto);
  } else {
    // fill in proto
  }
}

if ((void*)&src == (void*)this) {
return;
}
int len = product(src.Dims());
T* src_ptr = src.Data<T>();
T* dst_ptr = MutableData<T>(src.Dims());
for (int i = 0; i < len; ++i) {
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Why not use memcpy?

dst_ptr[i] = src_ptr[i];
}
return;
}

const std::shared_ptr<Placeholder>& Holder() const;

const DDim& Dims() const;

const paddle::platform::Place& Place() const;

template <typename T>
bool IsType() const {
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IsType should be removed because we can interpret a Tensor of any type -- just call mutable_data<T>(place, dim).

return typeid(T) == holder_.TypeInfo();
}

// Placeholder hides type T, so it doesn't appear as a template
struct Placeholder {
virtual ~Placeholder() {}
virtual std::type_info TypeInfo() const = 0;
virtual void* Ptr() const = 0;
virtual Place Place() const = 0;
virtual size_t Size() const = 0;
};

private:
template <typename T>
struct PlaceholderImpl : public Placeholder {
PlaceholderImpl(Place place, size_t size)
: ptr_(paddle::memory::Alloc(place, size),
paddle::memory::Deleter(place)),
place_(place),
size_(size) {}

virtual std::type_info TypeInfo() const { return typeid(T); }
virtual void* Ptr() const { return static_cast<void*>(ptr_.get()); }
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Maybe Ptr() should not be added in interface, it should return T* like

struct Placeholder {
  virtual ~Placeholder() {}  // for rtti
};

template <typename T>
struct PlaceholderImpl : public Placeholder {
  T* Ptr() const { return ptr_.get(); }
};

template <typename T>
const T* Data() const {
  auto holder = std::dynamic_pointer_cast<PlaceholderImpl<T>>(holder_);
  ASSERT(holder != nullptr);
  return holder->Ptr();
}

Using static_cast everywhere make compiler cannot check type for us.

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See PR #2647

virtual size_t Size() const { return size_; }
virtual Place Place() const { return place_; }

std::unique_ptr<T, paddle::memory::Deleter> ptr_;
Place place_; // record the place of ptr_.
size_t size_; // size of the memory block.
};

std::shared_ptr<Placeholder> holder_; // holds the memory block if allocated.
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Following @qingqing01 's suggestion, dims_ and place should be removed.

DDim dims_; // could be smallers than the holder_->Size().
Place place_;
};

} // namespace framework
} // namespace paddle