text: // Copyright 2020 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 <gtest/gtest.h>
  
  #include <algorithm>
  #include <cassert>
  #include <cmath>
  #include <cstddef>
  #include <cstdlib>
  #include <functional>
  #include <random>
  #include <vector>
  
  #include <xnnpack.h>
  
  
  class ELUOperatorTester {
   public:
    inline ELUOperatorTester& channels(size_t channels) {
      assert(channels != 0);
      this->channels_ = channels;
      return *this;
    }
  
    inline size_t channels() const {
      return this->channels_;
    }
  
    inline ELUOperatorTester& input_stride(size_t input_stride) {
      assert(input_stride != 0);
      this->input_stride_ = input_stride;
      return *this;
    }
  
    inline size_t input_stride() const {
      if (this->input_stride_ == 0) {
        return this->channels_;
      } else {
        assert(this->input_stride_ >= this->channels_);
        return this->input_stride_;
      }
    }
  
    inline ELUOperatorTester& output_stride(size_t output_stride) {
      assert(output_stride != 0);
      this->output_stride_ = output_stride;
      return *this;
    }
  
    inline size_t output_stride() const {
      if (this->output_stride_ == 0) {
        return this->channels_;
      } else {
        assert(this->output_stride_ >= this->channels_);
        return this->output_stride_;
      }
    }
  
    inline ELUOperatorTester& batch_size(size_t batch_size) {
      assert(batch_size != 0);
      this->batch_size_ = batch_size;
      return *this;
    }
  
    inline size_t batch_size() const {
      return this->batch_size_;
    }
  
    inline ELUOperatorTester& alpha(float alpha) {
      assert(alpha > 0.0f);
      assert(alpha < 1.0f);
      this->alpha_ = alpha;
      return *this;
    }
  
    inline float alpha() const {
      return this->alpha_;
    }
  
    inline ELUOperatorTester& input_scale(float input_scale) {
      assert(input_scale > 0.0f);
      assert(std::isnormal(input_scale));
      this->input_scale_ = input_scale;
      return *this;
    }
  
    inline float input_scale() const {
      return this->input_scale_;
    }
  
    inline ELUOperatorTester& input_zero_point(uint8_t input_zero_point) {
      this->input_zero_point_ = input_zero_point;
      return *this;
    }
  
    inline uint8_t input_zero_point() const {
      return this->input_zero_point_;
    }
  
    inline ELUOperatorTester& output_scale(float output_scale) {
      assert(output_scale > 0.0f);
      assert(std::isnormal(output_scale));
      this->output_scale_ = output_scale;
      return *this;
    }
  
    inline float output_scale() const {
      return this->output_scale_;
    }
  
    inline ELUOperatorTester& output_zero_point(uint8_t output_zero_point) {
      this->output_zero_point_ = output_zero_point;
      return *this;
    }
  
    inline uint8_t output_zero_point() const {
      return this->output_zero_point_;
    }
  
    inline ELUOperatorTester& qmin(uint8_t qmin) {
      this->qmin_ = qmin;
      return *this;
    }
  
    inline uint8_t qmin() const {
      return this->qmin_;
    }
  
    inline ELUOperatorTester& qmax(uint8_t qmax) {
      this->qmax_ = qmax;
      return *this;
    }
  
    inline uint8_t qmax() const {
      return this->qmax_;
    }
  
    inline ELUOperatorTester& iterations(size_t iterations) {
      this->iterations_ = iterations;
      return *this;
    }
  
    inline size_t iterations() const {
      return this->iterations_;
    }
  
  #ifndef XNN_NO_F32_OPERATORS
    void TestF32() const {
      std::random_device random_device;
      auto rng = std::mt19937(random_device());
      auto f32rng = std::bind(std::uniform_real_distribution<float>(-20.0f, 20.0f), std::ref(rng));
  
      std::vector<float> input(XNN_EXTRA_BYTES / sizeof(float) + (batch_size() - 1) * input_stride() + channels());
      std::vector<float> output((batch_size() - 1) * output_stride() + channels());
      std::vector<double> output_ref(batch_size() * channels());
      for (size_t iteration = 0; iteration < iterations(); iteration++) {
        std::generate(input.begin(), input.end(), std::ref(f32rng));
        std::fill(output.begin(), output.end(), std::nanf(""));
  
        // Compute reference results.
        for (size_t i = 0; i < batch_size(); i++) {
          for (size_t c = 0; c < channels(); c++) {
            const double x = double(input[i * input_stride() + c]);
            output_ref[i * channels() + c] = std::signbit(x) ? std::expm1(x) * alpha() : x;
          }
        }
  
        // Create, setup, run, and destroy ELU operator.
        ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
        xnn_operator_t elu_op = nullptr;
  
        ASSERT_EQ(xnn_status_success,
          xnn_create_elu_nc_f32(
            channels(), input_stride(), output_stride(),
            alpha(),
            0, &elu_op));
        ASSERT_NE(nullptr, elu_op);
  
        // Smart pointer to automatically delete elu_op.
        std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_elu_op(elu_op, xnn_delete_operator);
  
        ASSERT_EQ(xnn_status_success,
          xnn_setup_elu_nc_f32(
            elu_op,
            batch_size(),
            input.data(), output.data(),
            nullptr /* thread pool */));
  
        ASSERT_EQ(xnn_status_success,
          xnn_run_operator(elu_op, nullptr /* thread pool */));
  
        // Verify results.
        for (size_t i = 0; i < batch_size(); i++) {
          for (size_t c = 0; c < channels(); c++) {
            ASSERT_NEAR(output[i * output_stride() + c],
                        output_ref[i * channels() + c],
                        std::abs(output_ref[i * channels() + c]) * 1.0e-5)
              << "at batch " << i << " / " << batch_size() << ", channel " << c << " / " << channels()
              << ", input " << input[i * input_stride() + c] << ", alpha " << alpha();
          }
        }
      }
    }
  #endif
  
  #ifndef XNN_NO_QS8_OPERATORS
    void TestQS8() const {
      std::random_device random_device;
      auto rng = std::mt19937(random_device());
      auto i8rng = std::bind(
        std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()),
        std::ref(rng));
  
      std::vector<int8_t> input((batch_size() - 1) * input_stride() + channels() + XNN_EXTRA_BYTES / sizeof(int8_t));
      std::vector<int8_t> output((batch_size() - 1) * output_stride() + channels());
      std::vector<float> output_ref(batch_size() * channels());
      for (size_t iteration = 0; iteration < iterations(); iteration++) {
        std::generate(input.begin(), input.end(), std::ref(i8rng));
        std::fill(output.begin(), output.end(), 0xA5);
  
        // Compute reference results.
        for (size_t i = 0; i < batch_size(); i++) {
          for (size_t c = 0; c < channels(); c++) {
            const float x = input_scale() *
              (int32_t(input[i * input_stride() + c]) - int32_t(input_zero_point() - 0x80));
            const float elu_x = std::signbit(x) ? alpha() * std::expm1(x) : x;
            const float scaled_elu_x = elu_x / output_scale();
            float y = scaled_elu_x;
            y = std::min<float>(y, int32_t(qmax() - 0x80) - int32_t(output_zero_point() - 0x80));
            y = std::max<float>(y, int32_t(qmin() - 0x80) - int32_t(output_zero_point() - 0x80));
            output_ref[i * channels() + c] = y + int32_t(output_zero_point() - 0x80);
          }
        }
  
        // Create, setup, run, and destroy Sigmoid operator.
        ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
        xnn_operator_t elu_op = nullptr;
  
        ASSERT_EQ(xnn_status_success,
          xnn_create_elu_nc_qs8(
            channels(), input_stride(), output_stride(),
            alpha(),
            int8_t(input_zero_point() - 0x80), input_scale(),
            int8_t(output_zero_point() - 0x80), output_scale(),
            int8_t(qmin() - 0x80), int8_t(qmax() - 0x80),
            0, &elu_op));
        ASSERT_NE(nullptr, elu_op);
  
        // Smart pointer to automatically delete elu_op.
        std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_sigmoid_op(elu_op, xnn_delete_operator);
  
        ASSERT_EQ(xnn_status_success,
          xnn_setup_elu_nc_qs8(
            elu_op,
            batch_size(),
            input.data(), output.data(),
            nullptr /* thread pool */));
  
        ASSERT_EQ(xnn_status_success,
          xnn_run_operator(elu_op, nullptr /* thread pool */));
  
        // Verify results.
        for (size_t i = 0; i < batch_size(); i++) {
          for (size_t c = 0; c < channels(); c++) {
            ASSERT_NEAR(float(int32_t(output[i * output_stride() + c])), output_ref[i * channels() + c], 0.6f);
          }
        }
      }
    }
  #endif
  
   private:
    size_t batch_size_{1};
    size_t channels_{1};
    size_t input_stride_{0};
    size_t output_stride_{0};
    float alpha_{0.5f};
    float input_scale_{0.75f};
    uint8_t input_zero_point_{121};
    float output_scale_{0.75f};
    uint8_t output_zero_point_{121};
    uint8_t qmin_{0};
    uint8_t qmax_{255};
    size_t iterations_{15};
  };
  