311 lines
11 KiB
C++
311 lines
11 KiB
C++
// 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 <cassert>
|
|
#include <cstddef>
|
|
#include <cstdlib>
|
|
#include <functional>
|
|
#include <limits>
|
|
#include <random>
|
|
#include <vector>
|
|
|
|
#include <xnnpack.h>
|
|
|
|
|
|
class ClampOperatorTester {
|
|
public:
|
|
inline ClampOperatorTester& channels(size_t channels) {
|
|
assert(channels != 0);
|
|
this->channels_ = channels;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t channels() const {
|
|
return this->channels_;
|
|
}
|
|
|
|
inline ClampOperatorTester& 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 ClampOperatorTester& 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 ClampOperatorTester& 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 ClampOperatorTester& qmin(uint8_t qmin) {
|
|
this->qmin_ = qmin;
|
|
return *this;
|
|
}
|
|
|
|
inline uint8_t qmin() const {
|
|
return this->qmin_;
|
|
}
|
|
|
|
inline ClampOperatorTester& qmax(uint8_t qmax) {
|
|
this->qmax_ = qmax;
|
|
return *this;
|
|
}
|
|
|
|
inline uint8_t qmax() const {
|
|
return this->qmax_;
|
|
}
|
|
|
|
inline ClampOperatorTester& relu_activation(bool relu_activation) {
|
|
this->relu_activation_ = relu_activation;
|
|
return *this;
|
|
}
|
|
|
|
inline bool relu_activation() const {
|
|
return this->relu_activation_;
|
|
}
|
|
|
|
inline ClampOperatorTester& iterations(size_t iterations) {
|
|
this->iterations_ = iterations;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t iterations() const {
|
|
return this->iterations_;
|
|
}
|
|
|
|
void TestS8() 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(XNN_EXTRA_BYTES / sizeof(int8_t) +
|
|
(batch_size() - 1) * input_stride() + channels());
|
|
std::vector<int8_t> output((batch_size() - 1) * output_stride() + channels());
|
|
std::vector<int8_t> 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(), INT8_C(0xA5));
|
|
|
|
// Compute reference results.
|
|
for (size_t i = 0; i < batch_size(); i++) {
|
|
for (size_t c = 0; c < channels(); c++) {
|
|
const int8_t x = input[i * input_stride() + c];
|
|
const int8_t y = std::min(std::max(x, int8_t(qmin() - 0x80)), int8_t(qmax() - 0x80));
|
|
output_ref[i * channels() + c] = y;
|
|
}
|
|
}
|
|
|
|
// Create, setup, run, and destroy Clamp operator.
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
|
|
xnn_operator_t clamp_op = nullptr;
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_create_clamp_nc_s8(
|
|
channels(), input_stride(), output_stride(),
|
|
int8_t(qmin() - 0x80), int8_t(qmax() - 0x80),
|
|
0, &clamp_op));
|
|
ASSERT_NE(nullptr, clamp_op);
|
|
|
|
// Smart pointer to automatically delete clamp_op.
|
|
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_clamp_op(clamp_op, xnn_delete_operator);
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_setup_clamp_nc_s8(
|
|
clamp_op,
|
|
batch_size(),
|
|
input.data(), output.data(),
|
|
nullptr /* thread pool */));
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_run_operator(clamp_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(int32_t(output[i * output_stride() + c]), int32_t(qmax() - 0x80))
|
|
<< "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels();
|
|
ASSERT_GE(int32_t(output[i * output_stride() + c]), int32_t(qmin() - 0x80))
|
|
<< "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels();
|
|
ASSERT_EQ(int32_t(output_ref[i * channels() + c]), int32_t(output[i * output_stride() + c]))
|
|
<< "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels()
|
|
<< ", qmin = " << int32_t(qmin() - 0x80) << ", qmax = " << int32_t(qmax() - 0x80);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void TestU8() const {
|
|
std::random_device random_device;
|
|
auto rng = std::mt19937(random_device());
|
|
auto u8rng = std::bind(std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), rng);
|
|
|
|
std::vector<uint8_t> input(XNN_EXTRA_BYTES / sizeof(uint8_t) +
|
|
(batch_size() - 1) * input_stride() + channels());
|
|
std::vector<uint8_t> output((batch_size() - 1) * output_stride() + channels());
|
|
std::vector<uint8_t> output_ref(batch_size() * channels());
|
|
for (size_t iteration = 0; iteration < iterations(); iteration++) {
|
|
std::generate(input.begin(), input.end(), std::ref(u8rng));
|
|
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 uint8_t x = input[i * input_stride() + c];
|
|
const uint8_t y = std::min(std::max(x, qmin()), qmax());
|
|
output_ref[i * channels() + c] = y;
|
|
}
|
|
}
|
|
|
|
// Create, setup, run, and destroy Clamp operator.
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
|
|
xnn_operator_t clamp_op = nullptr;
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_create_clamp_nc_u8(
|
|
channels(), input_stride(), output_stride(),
|
|
qmin(), qmax(),
|
|
0, &clamp_op));
|
|
ASSERT_NE(nullptr, clamp_op);
|
|
|
|
// Smart pointer to automatically delete clamp_op.
|
|
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_clamp_op(clamp_op, xnn_delete_operator);
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_setup_clamp_nc_u8(
|
|
clamp_op,
|
|
batch_size(),
|
|
input.data(), output.data(),
|
|
nullptr /* thread pool */));
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_run_operator(clamp_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(output[i * output_stride() + c]), uint32_t(qmax()))
|
|
<< "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels();
|
|
ASSERT_GE(uint32_t(output[i * output_stride() + c]), uint32_t(qmin()))
|
|
<< "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels();
|
|
ASSERT_EQ(uint32_t(output_ref[i * channels() + c]), uint32_t(output[i * output_stride() + c]))
|
|
<< "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels()
|
|
<< ", qmin = " << uint32_t(qmin()) << ", qmax = " << uint32_t(qmax());
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
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, 255.0f), 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<float> 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 float x = input[i * input_stride() + c];
|
|
const float y = relu_activation() ? std::max(x, 0.f) :
|
|
std::min(std::max(x, float(qmin())), float(qmax()));
|
|
output_ref[i * channels() + c] = y;
|
|
}
|
|
}
|
|
|
|
// Create, setup, run, and destroy Clamp operator.
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
|
|
xnn_operator_t clamp_op = nullptr;
|
|
|
|
const float output_min = relu_activation() ? 0.0f : float(qmin());
|
|
const float output_max = relu_activation() ? std::numeric_limits<float>::infinity() : float(qmax());
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_create_clamp_nc_f32(
|
|
channels(), input_stride(), output_stride(),
|
|
output_min, output_max,
|
|
0, &clamp_op));
|
|
ASSERT_NE(nullptr, clamp_op);
|
|
|
|
// Smart pointer to automatically delete clamp_op.
|
|
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_clamp_op(clamp_op, xnn_delete_operator);
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_setup_clamp_nc_f32(
|
|
clamp_op,
|
|
batch_size(),
|
|
input.data(), output.data(),
|
|
nullptr /* thread pool */));
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_run_operator(clamp_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(output[i * output_stride() + c], output_max)
|
|
<< "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels();
|
|
ASSERT_GE(output[i * output_stride() + c], output_min)
|
|
<< "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels();
|
|
ASSERT_EQ(output_ref[i * channels() + c], output[i * output_stride() + c])
|
|
<< "at position " << i << ", batch size = " << batch_size() << ", channels = " << channels()
|
|
<< ", min = " << output_min << ", max = " << output_max;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
private:
|
|
size_t batch_size_{1};
|
|
size_t channels_{1};
|
|
size_t input_stride_{0};
|
|
size_t output_stride_{0};
|
|
uint8_t qmin_{5};
|
|
uint8_t qmax_{250};
|
|
bool relu_activation_{false};
|
|
size_t iterations_{15};
|
|
};
|