LUTMicrokernelTester Class — pytorch Architecture

Source Code

aten/src/ATen/native/quantized/cpu/qnnpack/test/lut-microkernel-tester.h lines 21–90

class LUTMicrokernelTester {
 public:
  inline LUTMicrokernelTester& n(size_t n) {
    assert(n != 0);
    this->n_ = n;
    return *this;
  }

  inline size_t n() const {
    return this->n_;
  }

  inline LUTMicrokernelTester& inplace(bool inplace) {
    this->inplace_ = inplace;
    return *this;
  }

  inline bool inplace() const {
    return this->inplace_;
  }

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

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

  void test(pytorch_x8lut_ukernel_function x8lut) const {
    std::random_device randomDevice;
    auto rng = std::mt19937(randomDevice());
    auto u8rng = std::bind(std::uniform_int_distribution<uint8_t>(), rng);

    std::vector<uint8_t> x(n());
    std::vector<uint8_t> t(256);
    std::vector<uint8_t> y(n());
    std::vector<uint8_t> yRef(n());
    for (size_t iteration = 0; iteration < iterations(); iteration++) {
      std::generate(x.begin(), x.end(), std::ref(u8rng));
      std::generate(t.begin(), t.end(), std::ref(u8rng));
      if (inplace()) {
        std::generate(y.begin(), y.end(), std::ref(u8rng));
      } else {
        std::fill(y.begin(), y.end(), 0xA5);
      }
      const uint8_t* xData = inplace() ? y.data() : x.data();

      /* Compute reference results */
      for (size_t i = 0; i < n(); i++) {
        yRef[i] = t[xData[i]];
      }

      /* Call optimized micro-kernel */
      x8lut(n(), xData, t.data(), y.data());

      /* Verify results */
      for (size_t i = 0; i < n(); i++) {
        ASSERT_EQ(uint32_t(yRef[i]), uint32_t(y[i]))
            << "at position " << i << ", n = " << n();
      }
    }
  }

 private:
  size_t n_{1};
  bool inplace_{false};
  size_t iterations_{15};
};