test/add-operator-tester.h - platform/external/XNNPACK - Git at Google

 // Copyright (c) Facebook, Inc. and its affiliates.
 // All rights reserved.
 //
 // Copyright 2019 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 <cmath>
 #include <cstddef>
 #include <cstdlib>
 #include <functional>
 #include <random>
 #include <vector>

 #include <xnnpack.h>


 class AddOperatorTester {
  public:
   inline AddOperatorTester& channels(size_t channels) {
     assert(channels != 0);
     this->channels_ = channels;
     return *this;
   }

   inline size_t channels() const {
     return this->channels_;
   }

   inline AddOperatorTester& a_stride(size_t a_stride) {
     assert(a_stride != 0);
     this->a_stride_ = a_stride;
     return *this;
   }

   inline size_t a_stride() const {
     if (this->a_stride_ == 0) {
       return this->channels_;
     } else {
       assert(this->a_stride_ >= this->channels_);
       return this->a_stride_;
     }
   }

   inline AddOperatorTester& b_stride(size_t b_stride) {
     assert(b_stride != 0);
     this->b_stride_ = b_stride;
     return *this;
   }

   inline size_t b_stride() const {
     if (this->b_stride_ == 0) {
       return this->channels_;
     } else {
       assert(this->b_stride_ >= this->channels_);
       return this->b_stride_;
     }
   }

   inline AddOperatorTester& y_stride(size_t y_stride) {
     assert(y_stride != 0);
     this->y_stride_ = y_stride;
     return *this;
   }

   inline size_t y_stride() const {
     if (this->y_stride_ == 0) {
       return this->channels_;
     } else {
       assert(this->y_stride_ >= this->channels_);
       return this->y_stride_;
     }
   }

   inline AddOperatorTester& 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 AddOperatorTester& a_scale(float a_scale) {
     assert(a_scale > 0.0f);
     assert(std::isnormal(a_scale));
     this->a_scale_ = a_scale;
     return *this;
   }

   inline float a_scale() const {
     return this->a_scale_;
   }

   inline AddOperatorTester& a_zero_point(uint8_t a_zero_point) {
     this->a_zero_point_ = a_zero_point;
     return *this;
   }

   inline uint8_t a_zero_point() const {
     return this->a_zero_point_;
   }

   inline AddOperatorTester& b_scale(float b_scale) {
     assert(b_scale > 0.0f);
     assert(std::isnormal(b_scale));
     this->b_scale_ = b_scale;
     return *this;
   }

   inline float b_scale() const {
     return this->b_scale_;
   }

   inline AddOperatorTester& b_zero_point(uint8_t b_zero_point) {
     this->b_zero_point_ = b_zero_point;
     return *this;
   }

   inline uint8_t b_zero_point() const {
     return this->b_zero_point_;
   }

   inline AddOperatorTester& y_scale(float y_scale) {
     assert(y_scale > 0.0f);
     assert(std::isnormal(y_scale));
     this->y_scale_ = y_scale;
     return *this;
   }

   inline float y_scale() const {
     return this->y_scale_;
   }

   inline AddOperatorTester& y_zero_point(uint8_t y_zero_point) {
     this->y_zero_point_ = y_zero_point;
     return *this;
   }

   inline uint8_t y_zero_point() const {
     return this->y_zero_point_;
   }

   inline AddOperatorTester& qmin(uint8_t qmin) {
     this->qmin_ = qmin;
     return *this;
   }

   inline uint8_t qmin() const {
     return this->qmin_;
   }

   inline AddOperatorTester& qmax(uint8_t qmax) {
     this->qmax_ = qmax;
     return *this;
   }

   inline uint8_t qmax() const {
     return this->qmax_;
   }

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

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

   void TestQ8() const {
     std::random_device random_device;
     auto rng = std::mt19937(random_device());
     auto u8rng = std::bind(std::uniform_int_distribution<uint8_t>(), rng);

     std::vector<uint8_t> a(XNN_EXTRA_BYTES / sizeof(uint8_t) + (batch_size() - 1) * a_stride() + channels());
     std::vector<uint8_t> b(XNN_EXTRA_BYTES / sizeof(uint8_t) + (batch_size() - 1) * b_stride() + channels());
     std::vector<uint8_t> y((batch_size() - 1) * y_stride() + channels());
     std::vector<float> y_ref(batch_size() * channels());
     for (size_t iteration = 0; iteration < iterations(); iteration++) {
       std::generate(a.begin(), a.end(), std::ref(u8rng));
       std::generate(b.begin(), b.end(), std::ref(u8rng));
       std::fill(y.begin(), y.end(), 0xA5);

       if (batch_size() * channels() > 3) {
         ASSERT_NE(*std::max_element(a.cbegin(), a.cend()), *std::min_element(a.cbegin(), a.cend()));
         ASSERT_NE(*std::max_element(b.cbegin(), b.cend()), *std::min_element(b.cbegin(), b.cend()));
       }

       // Compute reference results.
       for (size_t i = 0; i < batch_size(); i++) {
         for (size_t c = 0; c < channels(); c++) {
           y_ref[i * channels() + c] = float(y_zero_point()) +
             float(int32_t(a[i * a_stride() + c]) - int32_t(a_zero_point())) * (a_scale() / y_scale()) +
             float(int32_t(b[i * b_stride() + c]) - int32_t(b_zero_point())) * (b_scale() / y_scale());
           y_ref[i * channels() + c] = std::min<float>(y_ref[i * channels() + c], float(qmax()));
           y_ref[i * channels() + c] = std::max<float>(y_ref[i * channels() + c], float(qmin()));
         }
       }

       // Create, setup, run, and destroy Add operator.
       ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
       xnn_operator_t add_op = nullptr;

       ASSERT_EQ(xnn_status_success,
         xnn_create_add_nc_q8(
           channels(), a_stride(), b_stride(), y_stride(),
           a_zero_point(), a_scale(),
           b_zero_point(), b_scale(),
           y_zero_point(), y_scale(),
           qmin(), qmax(),
           0, &add_op));
       ASSERT_NE(nullptr, add_op);

       // Smart pointer to automatically delete add_op.
       std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_add_op(add_op, xnn_delete_operator);

       ASSERT_EQ(xnn_status_success,
         xnn_setup_add_nc_q8(
           add_op,
           batch_size(),
           a.data(), b.data(), y.data(),
           nullptr /* thread pool */));

       ASSERT_EQ(xnn_status_success,
         xnn_run_operator(add_op, nullptr /* thread pool */));

       /// Verify results.
       for (size_t i = 0; i < batch_size(); i++) {
         for (size_t c = 0; c < channels(); c++) {
           ASSERT_LE(uint32_t(y[i * y_stride() + c]), uint32_t(qmax()));
           ASSERT_GE(uint32_t(y[i * y_stride() + c]), uint32_t(qmin()));
           ASSERT_NEAR(float(int32_t(y[i * y_stride() + c])), y_ref[i * channels() + c], 0.6f);
         }
       }
     }
   }

   void TestF32() const {
     std::random_device random_device;
     auto rng = std::mt19937(random_device());
     auto f32rng = std::bind(std::uniform_real_distribution<float>(0.0f, 1.0f), rng);

     std::vector<float> a(XNN_EXTRA_BYTES / sizeof(float) + (batch_size() - 1) * a_stride() + channels());
     std::vector<float> b(XNN_EXTRA_BYTES / sizeof(float) + (batch_size() - 1) * b_stride() + channels());
     std::vector<float> y((batch_size() - 1) * y_stride() + channels());
     std::vector<float> y_ref(batch_size() * channels());
     for (size_t iteration = 0; iteration < iterations(); iteration++) {
       std::generate(a.begin(), a.end(), std::ref(f32rng));
       std::generate(b.begin(), b.end(), std::ref(f32rng));
       std::fill(y.begin(), y.end(), nanf(""));

       // Compute reference results.
       for (size_t i = 0; i < batch_size(); i++) {
         for (size_t c = 0; c < channels(); c++) {
           y_ref[i * channels() + c] = a[i * a_stride() + c] + b[i * b_stride() + c];
         }
       }
       const float accumulated_min = *std::min_element(y_ref.cbegin(), y_ref.cend());
       const float accumulated_max = *std::max_element(y_ref.cbegin(), y_ref.cend());
       const float accumulated_range = accumulated_max - accumulated_min;
       const float y_min = batch_size() * channels() == 1 ?
         -std::numeric_limits<float>::infinity() : accumulated_min + accumulated_range / 255.0f * float(qmin());
       const float y_max = batch_size() * channels() == 1 ?
         +std::numeric_limits<float>::infinity() : accumulated_max - accumulated_range / 255.0f * float(255 - qmax());
       for (size_t i = 0; i < batch_size(); i++) {
         for (size_t c = 0; c < channels(); c++) {
           y_ref[i * channels() + c] = std::min(std::max(y_ref[i * channels() + c], y_min), y_max);
         }
       }

       // Create, setup, run, and destroy Add operator.
       ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
       xnn_operator_t add_op = nullptr;

       ASSERT_EQ(xnn_status_success,
         xnn_create_add_nc_f32(
           channels(), a_stride(), b_stride(), y_stride(),
           y_min, y_max,
           0, &add_op));
       ASSERT_NE(nullptr, add_op);

       // Smart pointer to automatically delete add_op.
       std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_add_op(add_op, xnn_delete_operator);

       ASSERT_EQ(xnn_status_success,
         xnn_setup_add_nc_f32(
           add_op,
           batch_size(),
           a.data(), b.data(), y.data(),
           nullptr /* thread pool */));

       ASSERT_EQ(xnn_status_success,
         xnn_run_operator(add_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(y[i * y_stride() + c], y_ref[i * channels() + c], 1.0e-6f * y_ref[i * channels() + c])
             << "i = " << i << ", c = " << c;
         }
       }
     }
   }

  private:
   size_t batch_size_{1};
   size_t channels_{1};
   size_t a_stride_{0};
   size_t b_stride_{0};
   size_t y_stride_{0};
   float a_scale_{0.75f};
   float b_scale_{1.25f};
   float y_scale_{0.96875f};
   uint8_t a_zero_point_{121};
   uint8_t b_zero_point_{127};
   uint8_t y_zero_point_{133};
   uint8_t qmin_{0};
   uint8_t qmax_{255};
   size_t iterations_{15};
 };
	// Copyright (c) Facebook, Inc. and its affiliates.
	// All rights reserved.
	//
	// Copyright 2019 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 <cmath>
	#include <cstddef>
	#include <cstdlib>
	#include <functional>
	#include <random>
	#include <vector>

	#include <xnnpack.h>


	class AddOperatorTester {
	public:
	inline AddOperatorTester& channels(size_t channels) {
	assert(channels != 0);
	this->channels_ = channels;
	return *this;
	}

	inline size_t channels() const {
	return this->channels_;
	}

	inline AddOperatorTester& a_stride(size_t a_stride) {
	assert(a_stride != 0);
	this->a_stride_ = a_stride;
	return *this;
	}

	inline size_t a_stride() const {
	if (this->a_stride_ == 0) {
	return this->channels_;
	} else {
	assert(this->a_stride_ >= this->channels_);
	return this->a_stride_;
	}
	}

	inline AddOperatorTester& b_stride(size_t b_stride) {
	assert(b_stride != 0);
	this->b_stride_ = b_stride;
	return *this;
	}

	inline size_t b_stride() const {
	if (this->b_stride_ == 0) {
	return this->channels_;
	} else {
	assert(this->b_stride_ >= this->channels_);
	return this->b_stride_;
	}
	}

	inline AddOperatorTester& y_stride(size_t y_stride) {
	assert(y_stride != 0);
	this->y_stride_ = y_stride;
	return *this;
	}

	inline size_t y_stride() const {
	if (this->y_stride_ == 0) {
	return this->channels_;
	} else {
	assert(this->y_stride_ >= this->channels_);
	return this->y_stride_;
	}
	}

	inline AddOperatorTester& 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 AddOperatorTester& a_scale(float a_scale) {
	assert(a_scale > 0.0f);
	assert(std::isnormal(a_scale));
	this->a_scale_ = a_scale;
	return *this;
	}

	inline float a_scale() const {
	return this->a_scale_;
	}

	inline AddOperatorTester& a_zero_point(uint8_t a_zero_point) {
	this->a_zero_point_ = a_zero_point;
	return *this;
	}

	inline uint8_t a_zero_point() const {
	return this->a_zero_point_;
	}

	inline AddOperatorTester& b_scale(float b_scale) {
	assert(b_scale > 0.0f);
	assert(std::isnormal(b_scale));
	this->b_scale_ = b_scale;
	return *this;
	}

	inline float b_scale() const {
	return this->b_scale_;
	}

	inline AddOperatorTester& b_zero_point(uint8_t b_zero_point) {
	this->b_zero_point_ = b_zero_point;
	return *this;
	}

	inline uint8_t b_zero_point() const {
	return this->b_zero_point_;
	}

	inline AddOperatorTester& y_scale(float y_scale) {
	assert(y_scale > 0.0f);
	assert(std::isnormal(y_scale));
	this->y_scale_ = y_scale;
	return *this;
	}

	inline float y_scale() const {
	return this->y_scale_;
	}

	inline AddOperatorTester& y_zero_point(uint8_t y_zero_point) {
	this->y_zero_point_ = y_zero_point;
	return *this;
	}

	inline uint8_t y_zero_point() const {
	return this->y_zero_point_;
	}

	inline AddOperatorTester& qmin(uint8_t qmin) {
	this->qmin_ = qmin;
	return *this;
	}

	inline uint8_t qmin() const {
	return this->qmin_;
	}

	inline AddOperatorTester& qmax(uint8_t qmax) {
	this->qmax_ = qmax;
	return *this;
	}

	inline uint8_t qmax() const {
	return this->qmax_;
	}

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

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

	void TestQ8() const {
	std::random_device random_device;
	auto rng = std::mt19937(random_device());
	auto u8rng = std::bind(std::uniform_int_distribution<uint8_t>(), rng);

	std::vector<uint8_t> a(XNN_EXTRA_BYTES / sizeof(uint8_t) + (batch_size() - 1) * a_stride() + channels());
	std::vector<uint8_t> b(XNN_EXTRA_BYTES / sizeof(uint8_t) + (batch_size() - 1) * b_stride() + channels());
	std::vector<uint8_t> y((batch_size() - 1) * y_stride() + channels());
	std::vector<float> y_ref(batch_size() * channels());
	for (size_t iteration = 0; iteration < iterations(); iteration++) {
	std::generate(a.begin(), a.end(), std::ref(u8rng));
	std::generate(b.begin(), b.end(), std::ref(u8rng));
	std::fill(y.begin(), y.end(), 0xA5);

	if (batch_size() * channels() > 3) {
	ASSERT_NE(std::max_element(a.cbegin(), a.cend()), std::min_element(a.cbegin(), a.cend()));
	ASSERT_NE(std::max_element(b.cbegin(), b.cend()), std::min_element(b.cbegin(), b.cend()));
	}

	// Compute reference results.
	for (size_t i = 0; i < batch_size(); i++) {
	for (size_t c = 0; c < channels(); c++) {
	y_ref[i * channels() + c] = float(y_zero_point()) +
	float(int32_t(a[i * a_stride() + c]) - int32_t(a_zero_point())) * (a_scale() / y_scale()) +
	float(int32_t(b[i * b_stride() + c]) - int32_t(b_zero_point())) * (b_scale() / y_scale());
	y_ref[i * channels() + c] = std::min<float>(y_ref[i * channels() + c], float(qmax()));
	y_ref[i * channels() + c] = std::max<float>(y_ref[i * channels() + c], float(qmin()));
	}
	}

	// Create, setup, run, and destroy Add operator.
	ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
	xnn_operator_t add_op = nullptr;

	ASSERT_EQ(xnn_status_success,
	xnn_create_add_nc_q8(
	channels(), a_stride(), b_stride(), y_stride(),
	a_zero_point(), a_scale(),
	b_zero_point(), b_scale(),
	y_zero_point(), y_scale(),
	qmin(), qmax(),
	0, &add_op));
	ASSERT_NE(nullptr, add_op);

	// Smart pointer to automatically delete add_op.
	std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_add_op(add_op, xnn_delete_operator);

	ASSERT_EQ(xnn_status_success,
	xnn_setup_add_nc_q8(
	add_op,
	batch_size(),
	a.data(), b.data(), y.data(),
	nullptr /* thread pool */));

	ASSERT_EQ(xnn_status_success,
	xnn_run_operator(add_op, nullptr /* thread pool */));

	/// Verify results.
	for (size_t i = 0; i < batch_size(); i++) {
	for (size_t c = 0; c < channels(); c++) {
	ASSERT_LE(uint32_t(y[i * y_stride() + c]), uint32_t(qmax()));
	ASSERT_GE(uint32_t(y[i * y_stride() + c]), uint32_t(qmin()));
	ASSERT_NEAR(float(int32_t(y[i * y_stride() + c])), y_ref[i * channels() + c], 0.6f);
	}
	}
	}
	}

	void TestF32() const {
	std::random_device random_device;
	auto rng = std::mt19937(random_device());
	auto f32rng = std::bind(std::uniform_real_distribution<float>(0.0f, 1.0f), rng);

	std::vector<float> a(XNN_EXTRA_BYTES / sizeof(float) + (batch_size() - 1) * a_stride() + channels());
	std::vector<float> b(XNN_EXTRA_BYTES / sizeof(float) + (batch_size() - 1) * b_stride() + channels());
	std::vector<float> y((batch_size() - 1) * y_stride() + channels());
	std::vector<float> y_ref(batch_size() * channels());
	for (size_t iteration = 0; iteration < iterations(); iteration++) {
	std::generate(a.begin(), a.end(), std::ref(f32rng));
	std::generate(b.begin(), b.end(), std::ref(f32rng));
	std::fill(y.begin(), y.end(), nanf(""));

	// Compute reference results.
	for (size_t i = 0; i < batch_size(); i++) {
	for (size_t c = 0; c < channels(); c++) {
	y_ref[i * channels() + c] = a[i * a_stride() + c] + b[i * b_stride() + c];
	}
	}
	const float accumulated_min = *std::min_element(y_ref.cbegin(), y_ref.cend());
	const float accumulated_max = *std::max_element(y_ref.cbegin(), y_ref.cend());
	const float accumulated_range = accumulated_max - accumulated_min;
	const float y_min = batch_size() * channels() == 1 ?
	-std::numeric_limits<float>::infinity() : accumulated_min + accumulated_range / 255.0f * float(qmin());
	const float y_max = batch_size() * channels() == 1 ?
	+std::numeric_limits<float>::infinity() : accumulated_max - accumulated_range / 255.0f * float(255 - qmax());
	for (size_t i = 0; i < batch_size(); i++) {
	for (size_t c = 0; c < channels(); c++) {
	y_ref[i * channels() + c] = std::min(std::max(y_ref[i * channels() + c], y_min), y_max);
	}
	}

	// Create, setup, run, and destroy Add operator.
	ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
	xnn_operator_t add_op = nullptr;

	ASSERT_EQ(xnn_status_success,
	xnn_create_add_nc_f32(
	channels(), a_stride(), b_stride(), y_stride(),
	y_min, y_max,
	0, &add_op));
	ASSERT_NE(nullptr, add_op);

	// Smart pointer to automatically delete add_op.
	std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_add_op(add_op, xnn_delete_operator);

	ASSERT_EQ(xnn_status_success,
	xnn_setup_add_nc_f32(
	add_op,
	batch_size(),
	a.data(), b.data(), y.data(),
	nullptr /* thread pool */));

	ASSERT_EQ(xnn_status_success,
	xnn_run_operator(add_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(y[i * y_stride() + c], y_ref[i * channels() + c], 1.0e-6f * y_ref[i * channels() + c])
	<< "i = " << i << ", c = " << c;
	}
	}
	}
	}

	private:
	size_t batch_size_{1};
	size_t channels_{1};
	size_t a_stride_{0};
	size_t b_stride_{0};
	size_t y_stride_{0};
	float a_scale_{0.75f};
	float b_scale_{1.25f};
	float y_scale_{0.96875f};
	uint8_t a_zero_point_{121};
	uint8_t b_zero_point_{127};
	uint8_t y_zero_point_{133};
	uint8_t qmin_{0};
	uint8_t qmax_{255};
	size_t iterations_{15};
	};