class_docstr: A causal version of nn.Conv2d where each location in the 2D matrix would have no access to locations on its right or down
  All arguments are the same as nn.Conv2d except padding which should be set as None
class_docstr_tok: ["A","causal","version","of","nn.Conv2d","where","each","location","in","the","2D","matrix","would","have","no","access","to","locations","on","its","right","or","down","All","arguments","are","the","same","as","nn.Conv2d","except","padding","which","should","be","set","as","None"]
code: def forward(
      self,
      x,
  ):
      x = F.pad(
          x,
          pad=(
              self._left_padding,
              self._right_padding,
              self._left_padding,
              self._right_padding,
          ),
      )
      x = super().forward(x)
      return x
  
file_path: NeMo/nemo/collections/asr/parts/submodules/causal_convs.py
imports: from typing import Union
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 2 for calling the CausalConv2D obj's underlying member method code with example usage: obj.forward(x) and returns: x