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


.. _program_listing_file_torch_csrc_api_include_torch_nn_init.h:

Program Listing for File init.h
===============================

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

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

.. code-block:: cpp

   #pragma once
   
   #include <torch/csrc/Export.h>
   #include <torch/enum.h>
   #include <torch/types.h>
   
   namespace torch {
   
   namespace nn::init {
   
   using NonlinearityType = std::variant<
       enumtype::kLinear,
       enumtype::kConv1D,
       enumtype::kConv2D,
       enumtype::kConv3D,
       enumtype::kConvTranspose1D,
       enumtype::kConvTranspose2D,
       enumtype::kConvTranspose3D,
       enumtype::kSigmoid,
       enumtype::kTanh,
       enumtype::kReLU,
       enumtype::kLeakyReLU>;
   
   using FanModeType = std::variant<enumtype::kFanIn, enumtype::kFanOut>;
   
   } // namespace nn::init
   
   namespace nn::init {
   
   TORCH_API double calculate_gain(
       NonlinearityType nonlinearity,
       double param = 0.01);
   
   TORCH_API Tensor constant_(Tensor tensor, Scalar value);
   
   TORCH_API Tensor dirac_(Tensor tensor);
   
   TORCH_API Tensor eye_(Tensor matrix);
   
   TORCH_API Tensor normal_(Tensor tensor, double mean = 0, double std = 1);
   
   TORCH_API Tensor ones_(Tensor tensor);
   
   TORCH_API Tensor orthogonal_(Tensor tensor, double gain = 1.0);
   
   TORCH_API Tensor sparse_(Tensor tensor, double sparsity, double std = 0.01);
   
   TORCH_API Tensor uniform_(Tensor tensor, double low = 0, double high = 1);
   
   TORCH_API Tensor kaiming_normal_(
       Tensor tensor,
       double a = 0,
       FanModeType mode = torch::kFanIn,
       NonlinearityType nonlinearity = torch::kLeakyReLU);
   
   TORCH_API Tensor kaiming_uniform_(
       Tensor tensor,
       double a = 0,
       FanModeType mode = torch::kFanIn,
       NonlinearityType nonlinearity = torch::kLeakyReLU);
   
   TORCH_API Tensor xavier_normal_(Tensor tensor, double gain = 1.0);
   
   TORCH_API Tensor xavier_uniform_(Tensor tensor, double gain = 1.0);
   
   TORCH_API Tensor zeros_(Tensor tensor);
   
   TORCH_API std::tuple<int64_t, int64_t> _calculate_fan_in_and_fan_out(
       const Tensor& tensor);
   
   } // namespace nn::init
   
   } // namespace torch