Method ReduceWindow1DGeneric

tensorflow/compiler/xla/reference_util.cc:143–173

static */

}

/* static  */ std::unique_ptr<std::vector<float>>
ReferenceUtil::ReduceWindow1DGeneric(
    absl::Span<const float> operand, float init,
    const std::function<float(float, float)>& reduce_func,
    absl::Span<const int64> window, absl::Span<const int64> stride,
    absl::Span<const std::pair<int64, int64>> padding) {
  CHECK_EQ(window.size(), 1);
  CHECK_EQ(stride.size(), 1);
  CHECK_EQ(padding.size(), 1);

  int64 padded_width = padding[0].first + operand.size() + padding[0].second;
  int64 stride_amount = stride[0];
  int64 window_size = window[0];
  int64 result_size =
      window_util::StridedBound(padded_width, window_size, stride_amount);
  int64 pad_low = padding[0].first;
  auto result = absl::make_unique<std::vector<float>>(result_size);

  // Do a full 1D reduce window.
  for (int64 i0 = 0; i0 < result_size; ++i0) {
    int64 i0_base = i0 * stride_amount - pad_low;
    float val = init;
    for (int64 i0_win = 0; i0_win < window_size; ++i0_win) {
      if (i0_base + i0_win >= 0 && i0_base + i0_win < operand.size()) {
        val = reduce_func(val, operand[i0_base + i0_win]);
      }
    }
    (*result)[i0] = val;
  }
  return result;
}

/* static  */ std::unique_ptr<std::vector<float>>
ReferenceUtil::ReduceWindow1DAdd(absl::Span<const float> operand, float init,