89 lines
		
	
	
		
			2.5 KiB
		
	
	
	
		
			C++
		
	
	
	
			
		
		
	
	
			89 lines
		
	
	
		
			2.5 KiB
		
	
	
	
		
			C++
		
	
	
	
// 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 <chrono>
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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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#include <xnnpack/params.h>
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class VScaleExpMinusMaxMicrokernelTester {
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 public:
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  inline VScaleExpMinusMaxMicrokernelTester& elements(size_t elements) {
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    assert(elements != 0);
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    this->elements_ = elements;
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    return *this;
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  }
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  inline size_t elements() const {
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    return this->elements_;
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  }
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  inline VScaleExpMinusMaxMicrokernelTester& scale(float scale) {
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    assert(std::isfinite(scale));
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    assert(scale > 0);
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    this->scale_ = scale;
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    return *this;
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  }
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  inline float scale() const {
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    return this->scale_;
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  }
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  inline VScaleExpMinusMaxMicrokernelTester& 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_f32_vscaleexpminusmax_ukernel_function vscaleexpminusmax) const {
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    std::random_device random_device;
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    auto rng = std::mt19937(random_device());
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    // Choose such range that expf(x[i]) overflows, but expf(x[i] - x_max) doesn't.
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    // However, the range is still narrow enough that double-precision exp doesn't overflow.
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    auto f32rng = std::bind(std::uniform_real_distribution<float>(90.0f, 100.0f), rng);
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    std::vector<float> x(elements() + XNN_EXTRA_BYTES / sizeof(float));
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    std::vector<float> y(elements());
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    std::vector<double> y_ref(elements());
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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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      // Compute reference results.
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      const float x_max = *std::max_element(x.begin(), x.begin() + elements());
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      for (size_t i = 0; i < elements(); i++) {
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        y_ref[i] = double(scale()) * exp(double(x[i]) - double(x_max));
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      }
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      // Call optimized micro-kernel.
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      vscaleexpminusmax(elements() * sizeof(float), x.data(), y.data(), scale(), x_max);
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      // Verify results.
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      for (size_t i = 0; i < elements(); i++) {
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        ASSERT_NEAR(y_ref[i], y[i], std::abs(y_ref[i]) * 1.0e-6)
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          << "elements = " << elements() << ", scale = " << scale() << ", x_max = " << x_max;
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      }
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    }
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  }
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 private:
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  size_t elements_{1};
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  float scale_{1.0f};
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  size_t iterations_{15};
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};
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