parameters: (self, x)
return_statement: return self.dropout(x)
docstring: r"""Inputs of forward function
          Args:
              x: the sequence fed to the positional encoder model (required).
          Shape:
              x: [sequence length, batch size, embed dim]
              output: [sequence length, batch size, embed dim]
          Examples:
              >>> output = pos_encoder(x)
docstring_summary: r"""Inputs of forward function
          Args:
              x: the sequence fed to the positional encoder model (required).
          Shape:
              x: [sequence length, batch size, embed dim]
              output: [sequence length, batch size, embed dim]
          Examples:
              >>> output = pos_encoder(x)
docstring_tokens: r Inputs of forward function Args : x : the sequence fed to the positional encoder model ( required ) . Shape : x : [ sequence length batch size embed dim ] output : [ sequence length batch size embed dim ] Examples : >>> output = pos_encoder ( x )
function: def forward(self, x):
          r"""Inputs of forward function
          Args:
              x: the sequence fed to the positional encoder model (required).
          Shape:
              x: [sequence length, batch size, embed dim]
              output: [sequence length, batch size, embed dim]
          Examples:
              >>> output = pos_encoder(x)
          """
  
          x = x + self.pe[:x.size(0), :]
          return self.dropout(x)
function_tokens: def forward ( self , x ) : x = x + self . pe [ : x . size ( 0 ) , : ] return self . dropout ( x )