android13/external/XNNPACK/test/transpose-microkernel-tester.h

// Copyright 2021 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.

#pragma once

#include <xnnpack.h>
#include <xnnpack/params.h>

#include <numeric>
#include <cassert>
#include <cstddef>
#include <cstdlib>
#include <vector>

#include <gtest/gtest.h>


class TransposeMicrokernelTester {
 public:
  inline TransposeMicrokernelTester& block_height(size_t block_height) {
    assert(block_height != 0);
    this->block_height_ = block_height;
    return *this;
  }

  inline size_t block_height() const { return this->block_height_; }

  inline TransposeMicrokernelTester& block_width(size_t block_width) {
    assert(block_width != 0);
    this->block_width_ = block_width;
    return *this;
  }

  inline size_t block_width() const { return this->block_width_; }

  inline TransposeMicrokernelTester& input_stride(size_t input_stride) {
    this->input_stride_ = input_stride;
    return *this;
  }

  inline size_t input_stride() const { return this->input_stride_; }

  inline TransposeMicrokernelTester& output_stride(size_t output_stride) {
    this->output_stride_ = output_stride;
    return *this;
  }

  inline size_t output_stride() const { return this->output_stride_; }

  inline TransposeMicrokernelTester& iterations(size_t iterations) {
    this->iterations_ = iterations;
    return *this;
  }

  inline size_t iterations() const { return this->iterations_; }

  void Test(xnn_x64_transpose_ukernel_function transpose) const {
    std::vector<uint64_t> input(input_stride() * output_stride() + XNN_EXTRA_BYTES / sizeof(uint64_t));
    std::vector<uint64_t> output(input_stride() * output_stride());
    for (size_t iteration = 0; iteration < iterations(); iteration++) {
      std::iota(input.begin(), input.end(), 0);
      std::fill(output.begin(), output.end(), 0);

      // Call optimized micro-kernel.
      transpose(input.data(),
                output.data(),
                input_stride() * sizeof(uint64_t),
                output_stride() * sizeof(uint64_t),
                block_width(),
                block_height());

      // Verify results.
      for (size_t c = 0; c < block_width(); c++) {
        for (size_t r = 0; r < block_height(); r++) {
          EXPECT_EQ(input[c + r * input_stride()], output[r + c * output_stride()])
              << "at row " << r << " / " << block_height()
              << ", at column " << c << " / " << block_width();
        }
      }
    }
  }

  void Test(xnn_x32_transpose_ukernel_function transpose) const {
    std::vector<uint32_t> input(input_stride() * output_stride() + XNN_EXTRA_BYTES / sizeof(uint32_t));
    std::vector<uint32_t> output(input_stride() * output_stride());
    for (size_t iteration = 0; iteration < iterations(); iteration++) {
      std::iota(input.begin(), input.end(), 0);
      std::fill(output.begin(), output.end(), 0);

      // Call optimized micro-kernel.
      transpose(input.data(),
                output.data(),
                input_stride() * sizeof(uint32_t),
                output_stride() * sizeof(uint32_t),
                block_width(),
                block_height());

      // Verify results.
      for (size_t c = 0; c < block_width(); c++) {
        for (size_t r = 0; r < block_height(); r++) {
          EXPECT_EQ(input[c + r * input_stride()], output[r + c * output_stride()])
              << "at row " << r << " / " << block_height()
              << ", at column " << c << " / " << block_width();
        }
      }
    }
  }

  void Test(xnn_x16_transpose_ukernel_function transpose) const {
    std::vector<uint16_t> input(input_stride() * output_stride() + XNN_EXTRA_BYTES / sizeof(uint16_t));
    std::vector<uint16_t> output(input_stride() * output_stride());
    for (size_t iteration = 0; iteration < iterations(); iteration++) {
      std::iota(input.begin(), input.end(), 0);
      std::fill(output.begin(), output.end(), 0);

      // Call optimized micro-kernel.
      transpose(input.data(),
                output.data(),
                input_stride() * sizeof(uint16_t),
                output_stride() * sizeof(uint16_t),
                block_width(),
                block_height());

      // Verify results.
      for (size_t c = 0; c < block_width(); c++) {
        for (size_t r = 0; r < block_height(); r++) {
          EXPECT_EQ(input[c + r * input_stride()], output[r + c * output_stride()])
              << "at row " << r << " / " << block_height()
              << ", at column " << c << " / " << block_width();
        }
      }
    }
  }

  void Test(xnn_x8_transpose_ukernel_function transpose) const {
    std::vector<uint8_t> input(input_stride() * output_stride() + XNN_EXTRA_BYTES);
    std::vector<uint8_t> output(input_stride() * output_stride());
    for (size_t iteration = 0; iteration < iterations(); iteration++) {
      std::iota(input.begin(), input.end(), 0);
      std::fill(output.begin(), output.end(), 0);

      // Call optimized micro-kernel.
      transpose(input.data(),
                output.data(),
                input_stride() * sizeof(uint8_t),
                output_stride() * sizeof(uint8_t),
                block_width(),
                block_height());

      // Verify results.
      for (size_t c = 0; c < block_width(); c++) {
        for (size_t r = 0; r < block_height(); r++) {
          EXPECT_EQ((int)input[c + r * input_stride()], (int)output[r + c * output_stride()])
              << "at row " << r << " / " << block_height()
              << ", at column " << c << " / " << block_width();
        }
      }
    }
  }

 private:
  size_t input_stride_ = 1;
  size_t output_stride_ = 1;
  size_t block_height_ = 1;
  size_t block_width_ = 1;
  size_t iterations_ = 15;
};