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231 lines
7.4 KiB
231 lines
7.4 KiB
// Copyright (c) Facebook, Inc. and its affiliates.
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// All rights reserved.
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//
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// Copyright 2019 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 <cstddef>
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#include <cstdlib>
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#include <functional>
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#include <limits>
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#include <random>
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#include <vector>
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#include <fp16.h>
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#include <xnnpack.h>
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#include <xnnpack/params-init.h>
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#include <xnnpack/params.h>
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class ClampMicrokernelTester {
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public:
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enum class Variant {
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Native,
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Scalar,
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};
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inline ClampMicrokernelTester& 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 ClampMicrokernelTester& inplace(bool inplace) {
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this->inplace_ = inplace;
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return *this;
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}
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inline bool inplace() const {
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return this->inplace_;
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}
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inline ClampMicrokernelTester& 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 ClampMicrokernelTester& 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 ClampMicrokernelTester& 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 Test(xnn_u8_clamp_ukernel_function clamp, Variant variant = Variant::Native) 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 u8rng = std::bind(std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), rng);
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std::vector<uint8_t> x(batch_size() + XNN_EXTRA_BYTES / sizeof(uint8_t));
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std::vector<uint8_t> y(batch_size() + (inplace() ? XNN_EXTRA_BYTES / sizeof(uint8_t) : 0));
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std::vector<uint8_t> y_ref(batch_size());
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for (size_t iteration = 0; iteration < iterations(); iteration++) {
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std::generate(x.begin(), x.end(), std::ref(u8rng));
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if (inplace()) {
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std::generate(y.begin(), y.end(), std::ref(u8rng));
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} else {
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std::fill(y.begin(), y.end(), 0xA5);
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}
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const uint8_t* x_data = inplace() ? y.data() : x.data();
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// Prepare parameters.
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union xnn_u8_minmax_params params = { };
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switch (variant) {
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case Variant::Native:
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params = xnn_init_u8_minmax_params(qmin(), qmax());
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break;
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case Variant::Scalar:
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params = xnn_init_scalar_u8_minmax_params(qmin(), qmax());
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break;
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}
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// Compute reference results.
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for (size_t i = 0; i < batch_size(); i++) {
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y_ref[i] = std::max(std::min(x_data[i], qmax()), qmin());
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}
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// Call optimized micro-kernel.
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clamp(batch_size() * sizeof(uint8_t), x_data, y.data(), ¶ms);
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// Verify results.
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for (size_t i = 0; i < batch_size(); i++) {
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ASSERT_LE(uint32_t(y[i]), uint32_t(qmax()))
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<< "at position " << i << ", batch_size = " << batch_size();
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ASSERT_GE(uint32_t(y[i]), uint32_t(qmin()))
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<< "at position " << i << ", batch_size = " << batch_size();
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ASSERT_EQ(uint32_t(y_ref[i]), uint32_t(y[i]))
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<< "at position " << i << ", batch_size = " << batch_size()
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<< ", qmin = " << uint32_t(qmin()) << ", qmax = " << uint32_t(qmax());
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}
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}
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}
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void Test(xnn_f16_clamp_ukernel_function clamp) 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>(0.0f, 255.0f), rng);
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auto f16rng = std::bind(fp16_ieee_from_fp32_value, f32rng);
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std::vector<uint16_t> x(batch_size() + XNN_EXTRA_BYTES / sizeof(uint16_t));
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std::vector<uint16_t> y(batch_size() + (inplace() ? XNN_EXTRA_BYTES / sizeof(uint16_t) : 0));
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std::vector<float> y_ref(batch_size());
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for (size_t iteration = 0; iteration < iterations(); iteration++) {
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std::generate(x.begin(), x.end(), std::ref(f16rng));
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if (inplace()) {
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std::generate(y.begin(), y.end(), std::ref(f16rng));
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} else {
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std::fill(y.begin(), y.end(), UINT16_C(0x7E00) /* NaN */);
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}
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const uint16_t* x_data = inplace() ? y.data() : x.data();
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// Prepare parameters.
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xnn_f16_minmax_params params = xnn_init_f16_minmax_params(
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fp16_ieee_from_fp32_value(float(qmin())),
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fp16_ieee_from_fp32_value(float(qmax())));
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// Compute reference results.
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for (size_t i = 0; i < batch_size(); i++) {
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y_ref[i] = std::max(std::min(fp16_ieee_to_fp32_value(x_data[i]), float(qmax())), float(qmin()));
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}
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// Call optimized micro-kernel.
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clamp(batch_size() * sizeof(uint16_t), x_data, y.data(), ¶ms);
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// Verify results.
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for (size_t i = 0; i < batch_size(); i++) {
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ASSERT_LE(fp16_ieee_to_fp32_value(y[i]), float(qmax()))
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<< "at position " << i << ", batch_size = " << batch_size();
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ASSERT_GE(fp16_ieee_to_fp32_value(y[i]), float(qmin()))
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<< "at position " << i << ", batch_size = " << batch_size();
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ASSERT_EQ(y_ref[i], fp16_ieee_to_fp32_value(y[i]))
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<< "at position " << i << ", batch_size = " << batch_size()
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<< ", qmin = " << float(qmin()) << ", qmax = " << float(qmax());
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}
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}
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}
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void Test(xnn_f32_clamp_ukernel_function clamp, Variant variant = Variant::Native) 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>(0.0f, 255.0f), rng);
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std::vector<float> x(batch_size() + XNN_EXTRA_BYTES / sizeof(float));
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std::vector<float> y(batch_size() + (inplace() ? XNN_EXTRA_BYTES / sizeof(float) : 0));
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std::vector<float> y_ref(batch_size());
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for (size_t iteration = 0; iteration < iterations(); iteration++) {
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std::generate(x.begin(), x.end(), std::ref(f32rng));
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if (inplace()) {
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std::generate(y.begin(), y.end(), std::ref(f32rng));
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} else {
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std::fill(y.begin(), y.end(), std::nanf(""));
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}
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const float* x_data = inplace() ? y.data() : x.data();
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// Prepare parameters.
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xnn_f32_minmax_params params = { };
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switch (variant) {
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case Variant::Native:
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params = xnn_init_f32_minmax_params(float(qmin()), float(qmax()));
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break;
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case Variant::Scalar:
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params = xnn_init_scalar_f32_minmax_params(float(qmin()), float(qmax()));
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break;
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}
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// Compute reference results.
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for (size_t i = 0; i < batch_size(); i++) {
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y_ref[i] = std::max(std::min(x_data[i], float(qmax())), float(qmin()));
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}
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// Call optimized micro-kernel.
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clamp(batch_size() * sizeof(float), x_data, y.data(), ¶ms);
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// Verify results.
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for (size_t i = 0; i < batch_size(); i++) {
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ASSERT_LE(y[i], float(qmax()))
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<< "at position " << i << ", batch_size = " << batch_size();
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ASSERT_GE(y[i], float(qmin()))
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<< "at position " << i << ", batch_size = " << batch_size();
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ASSERT_EQ(y_ref[i], y[i])
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<< "at position " << i << ", batch_size = " << batch_size()
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<< ", qmin = " << uint32_t(qmin()) << ", qmax = " << uint32_t(qmax());
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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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bool inplace_{false};
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uint8_t qmin_{50};
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uint8_t qmax_{200};
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size_t iterations_{15};
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};
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