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