sample_gamma Class — pytorch Architecture

Source Code

aten/src/ATen/native/Distributions.h lines 83–112

template<typename scalar_t, typename accscalar_t, typename uniform_sampler_t, typename normal_sampler_t>
C10_DEVICE scalar_t sample_gamma(scalar_t alpha, BaseSampler<accscalar_t, uniform_sampler_t>& standard_uniform, BaseSampler<accscalar_t, normal_sampler_t>& standard_normal) {
  accscalar_t scale = 1.0f;

  // Boost alpha for higher acceptance probability.
  if (alpha < 1.0f) {
    if (alpha == 0.f) return 0.f;
    scale *= compat_pow(1 - standard_uniform.sample(), 1.0f / alpha);
    alpha += 1.0f;
  }

  // This implements the acceptance-rejection method of Marsaglia and Tsang (2000)
  // doi:10.1145/358407.358414
  const accscalar_t d = alpha - 1.0f / 3.0f;
  const accscalar_t c = 1.0f / compat_sqrt(9.0f * d);
  for (;;) {
    accscalar_t x, y;
    do {
      x = standard_normal.sample();
      y = 1.0f + c * x;
    } while (y <= 0);
    const accscalar_t v = y * y * y;
    const accscalar_t u = 1 - standard_uniform.sample();
    const accscalar_t xx = x * x;
    if (u < 1.0f - 0.0331f * xx * xx)
      return static_cast<scalar_t>(scale * d * v);
    if (compat_log(u) < 0.5f * xx + d * (1.0f - v + compat_log(v)))
      return static_cast<scalar_t>(scale * d * v);
  }
}