:github_url: https://github.com/pytorch/pytorch


.. _program_listing_file_torch_csrc_api_include_torch_nn_modules_utils.h:

Program Listing for File utils.h
================================

|exhale_lsh| :ref:`Return to documentation for file <file_torch_csrc_api_include_torch_nn_modules_utils.h>` (``torch/csrc/api/include/torch/nn/modules/utils.h``)

.. |exhale_lsh| unicode:: U+021B0 .. UPWARDS ARROW WITH TIP LEFTWARDS

.. code-block:: cpp

   #pragma once
   
   #include <c10/util/ArrayRef.h>
   #include <c10/util/irange.h>
   #include <optional>
   
   #include <vector>
   
   namespace torch::nn::modules::utils {
   
   // Reverse the order of `t` and repeat each element for `n` times.
   // This can be used to translate padding arg used by Conv and Pooling modules
   // to the ones used by `F::pad`.
   //
   // This mirrors `_reverse_repeat_tuple` in `torch/nn/modules/utils.py`.
   inline std::vector<int64_t> _reverse_repeat_vector(
       c10::ArrayRef<int64_t> t,
       int64_t n) {
     TORCH_INTERNAL_ASSERT(n >= 0);
     std::vector<int64_t> ret;
     ret.reserve(t.size() * n);
     for (auto rit = t.rbegin(); rit != t.rend(); ++rit) {
       for ([[maybe_unused]] const auto i : c10::irange(n)) {
         ret.emplace_back(*rit);
       }
     }
     return ret;
   }
   
   inline std::vector<int64_t> _list_with_default(
       c10::ArrayRef<std::optional<int64_t>> out_size,
       c10::IntArrayRef defaults) {
     TORCH_CHECK(
         defaults.size() > out_size.size(),
         "Input dimension should be at least ",
         out_size.size() + 1);
     std::vector<int64_t> ret;
     c10::IntArrayRef defaults_slice =
         defaults.slice(defaults.size() - out_size.size(), out_size.size());
     for (const auto i : c10::irange(out_size.size())) {
       auto v = out_size.at(i);
       auto d = defaults_slice.at(i);
       ret.emplace_back(v.has_value() ? v.value() : d);
     }
     return ret;
   }
   
   } // namespace torch::nn::modules::utils