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arena.h
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// Copyright 2020 LMNT, Inc. All Rights Reserved.
//
// 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.
// ==============================================================================
#pragma once
#include <cassert>
#include <string>
#include <utility>
#include <vector>
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/shape_inference.h"
template<typename T>
class TensorView {
public:
TensorView(T* ptr, const tensorflow::TensorShape& shape) {
ptr_ = ptr;
leading_dim_ = shape.dim_size(0);
stride_ = 1LL;
for (int i = 1; i < shape.dims(); ++i)
stride_ *= shape.dim_size(i);
}
tensorflow::int64 AllocatedBytes() const {
return leading_dim_ * stride_ * sizeof(T);
}
T* data() {
return ptr_;
}
T* SubSlicePtr(tensorflow::int64 i) {
assert(i >= 0);
assert(i < leading_dim_);
return ptr_ + (i * stride_);
}
const tensorflow::int64 NumElements() const {
return leading_dim_ * stride_;
}
private:
T* ptr_;
tensorflow::int64 leading_dim_;
tensorflow::int64 stride_;
};
template<typename T>
class Arena {
public:
struct Entry {
std::string name;
TensorView<T> view;
};
Arena(std::initializer_list<Entry> map) : map_(map) {}
Arena(const std::vector<Entry>& map) : map_(map) {}
TensorView<T> operator[](const std::string& name) {
for (auto& unit : map_)
if (name == unit.name)
return unit.view;
assert(false && "Invalid tensor name.");
}
private:
std::vector<Entry> map_;
};
template<typename T>
class ArenaLayout {
public:
struct Entry {
std::string name;
tensorflow::TensorShape shape;
};
ArenaLayout(std::initializer_list<Entry> layout) : layout_(layout) {}
tensorflow::int64 NumElements() const {
tensorflow::int64 total_elements = 0;
for (const auto& entry : layout_)
total_elements += entry.shape.num_elements();
return total_elements;
}
Arena<T> Realize(T* ptr) const {
std::vector<typename Arena<T>::Entry> map;
for (const auto& entry : layout_) {
map.push_back({ entry.name, TensorView<T>(ptr, entry.shape) });
ptr += entry.shape.num_elements();
}
return Arena<T>(map);
}
private:
std::vector<Entry> layout_;
};