EVOLUTION-MANAGER

Edit File: array4d.h

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you may not use this file except in compliance with the License.
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==============================================================================*/

#ifndef TENSORFLOW_COMPILER_XLA_ARRAY4D_H_
#define TENSORFLOW_COMPILER_XLA_ARRAY4D_H_

#include <algorithm>
#include <functional>
#include <initializer_list>
#include <iterator>
#include <memory>
#include <numeric>
#include <random>
#include <string>
#include <vector>

#include "absl/strings/str_cat.h"
#include "absl/types/span.h"
#include "tensorflow/compiler/xla/array.h"
#include "tensorflow/compiler/xla/array2d.h"
#include "tensorflow/compiler/xla/types.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/platform/types.h"

namespace xla {

// Simple 4D array structure, similar in form to Array2D, for use primarily in
// testing and describing to XLA APIs values in the 4D array structures used
// in convolutions.
//
// The data layout is, in order from major to minor:
//
//    First dimension: plane, batch, n1
//   Second dimension: depth, feature, z, n2
//    Third dimension: height, y, n3
//   Fourth dimension: width, x, n4
//
// These dimensions are referred to by various names, so that is why
// more than one name is given above. See operator() for the exact
// calculation of 1d indices from 4d indices.
template <typename T>
class Array4D : public Array<T> {
 public:
  Array4D() : Array<T>(std::vector<int64>{0, 0, 0, 0}) {}

// Creates a 4D array, uninitialized values.
  Array4D(int64 planes, int64 depth, int64 height, int64 width)
      : Array<T>(std::vector<int64>{planes, depth, height, width}) {}

// Creates a 4D array, initialized to value.
  Array4D(int64 planes, int64 depth, int64 height, int64 width, T value)
      : Array<T>(std::vector<int64>{planes, depth, height, width}, value) {}

// Creates a 4D array, filled with values.
  //
  // We need to set a default type for Container so that code like
  // Array4D(1, 1, 1, 1, {1}) will work. The template cannot infer the
  // initializer_list type in that case without this default.
  template <typename Container = std::initializer_list<T>>
  Array4D(int64 planes, int64 depth, int64 height, int64 width,
          const Container& values)
      : Array4D(planes, depth, height, width) {
    this->SetValues(values);
  }

// Construct an Array4D with the given nested initializer list.
  Array4D(std::initializer_list<std::initializer_list<
              std::initializer_list<std::initializer_list<T>>>>
              values)
      : Array<T>(values) {}

// Creates an array of a floating-point type (half, bfloat16, float,
  // or double) from the given nested initializer list of float values.
  template <typename T2, typename = typename std::enable_if<
                             (std::is_same<T, Eigen::half>::value ||
                              std::is_same<T, bfloat16>::value ||
                              std::is_same<T, float>::value ||
                              std::is_same<T, double>::value) &&
                             std::is_same<T2, float>::value>::type>
  Array4D(std::initializer_list<std::initializer_list<
              std::initializer_list<std::initializer_list<T2>>>>
              values)
      : Array<T>(values) {}

// Numerically-named aliases for the various dimensions. This matches the
  // dimension names used in array3d.
  int64 n4() const { return this->dim(3); }
  int64 n3() const { return this->dim(2); }
  int64 n2() const { return this->dim(1); }
  int64 n1() const { return this->dim(0); }

int64 width() const { return this->dim(3); }
  int64 height() const { return this->dim(2); }
  int64 depth() const { return this->dim(1); }
  int64 planes() const { return this->dim(0); }

// Fills all of the {p,z} with the array provided, which specifies {y,x}.
  void FillWithYX(const Array2D<T>& value) {
    CHECK_EQ(value.height(), height());
    CHECK_EQ(value.width(), width());
    for (int64 plane = 0; plane < planes(); ++plane) {
      for (int64 depth = 0; depth < this->depth(); ++depth) {
        for (int64 height = 0; height < this->height(); ++height) {
          for (int64 width = 0; width < this->width(); ++width) {
            (*this)(plane, depth, height, width) = value(height, width);
          }
        }
      }
    }
  }

// Fills all of the {p,x} with the array provided, which specifies {z,y}.
  void FillWithZY(const Array2D<T>& value) {
    CHECK_EQ(value.height(), depth());
    CHECK_EQ(value.width(), height());
    for (int64 plane = 0; plane < planes(); ++plane) {
      for (int64 depth = 0; depth < this->depth(); ++depth) {
        for (int64 height = 0; height < this->height(); ++height) {
          for (int64 width = 0; width < this->width(); ++width) {
            (*this)(plane, depth, height, width) = value(depth, height);
          }
        }
      }
    }
  }

// Fills all of the {x,y} with the array provided, which specifies {p,z}.
  void FillWithPZ(const Array2D<T>& value) {
    CHECK_EQ(value.height(), planes());
    CHECK_EQ(value.width(), depth());
    for (int64 height = 0; height < this->height(); ++height) {
      for (int64 width = 0; width < this->width(); ++width) {
        for (int64 plane = 0; plane < planes(); ++plane) {
          for (int64 depth = 0; depth < this->depth(); ++depth) {
            (*this)(plane, depth, height, width) = value(plane, depth);
          }
        }
      }
    }
  }

// Fills each of the minor-dim matrices with a number designating which minor
  // dim matrix is enclosed by the shape.
  void FillWithMinorDimNum() {
    LOG(INFO) << "width: " << this->width();
    LOG(INFO) << "height: " << this->height();
    LOG(INFO) << "depth: " << this->depth();
    LOG(INFO) << "planes: " << this->planes();
    for (int64 height = 0; height < this->height(); ++height) {
      for (int64 width = 0; width < this->width(); ++width) {
        for (int64 plane = 0; plane < planes(); ++plane) {
          for (int64 depth = 0; depth < this->depth(); ++depth) {
            float this_val = plane * this->depth() + depth;
            (*this)(plane, depth, height, width) = this_val;
          }
        }
      }
    }
  }
};

}  // namespace xla

#endif  // TENSORFLOW_COMPILER_XLA_ARRAY4D_H_