original_docstring: Implements forward computation of the model for a single recurrent step.
  
          Args:
              input of shape (batch, input_size): 
              tensor containing the features of the input sequence
  
          Returns:
              model output for current time step.
          
docstring: Implements forward computation of the model for a single recurrent step.
  Args:
  input of shape (batch, input_size):
  tensor containing the features of the input sequence
  
  model output for current time step.
docstring_tokens: Implements forward computation of the model for a single recurrent step . Args : input of shape ( batch input_size ) : tensor containing the features of the input sequence model output for current time step .
code: def step(self, input):
          """Implements forward computation of the model for a single recurrent step.
  
          Args:
              input of shape (batch, input_size): 
              tensor containing the features of the input sequence
  
          Returns:
              model output for current time step.
          """
          
          h = []
          h.append(self._Cells[0](input, self._h_prev[0]))
          for i, cell in enumerate(self._Cells):
              if i != 0:
                  h.append(cell(h[i-1]["h"], self._h_prev[i]))
          output = torch.add(torch.mm(h[-1]["h"], self._W_h2o), self._b_o)
          if self._output_activation_fn is not None:
              output = self._output_activation_fn(output)
          self._h_prev = h
          return output
code_tokens: def step ( self , input ) : h = [ ] h . append ( self . _Cells [ 0 ] ( input , self . _h_prev [ 0 ] ) ) for i , cell in enumerate ( self . _Cells ) : if i != 0 : h . append ( cell ( h [ i - 1 ] [ "h" ] , self . _h_prev [ i ] ) ) output = torch . add ( torch . mm ( h [ - 1 ] [ "h" ] , self . _W_h2o ) , self . _b_o ) if self . _output_activation_fn is not None : output = self . _output_activation_fn ( output ) self . _h_prev = h return output
short_docstring: Implements forward computation of the model for a single recurrent step.
short_docstring_tokens: Implements forward computation of the model for a single recurrent step .
comment: """Implements forward computation of the model for a single recurrent step.
  
          Args:
              input of shape (batch, input_size): 
              tensor containing the features of the input sequence
  
          Returns:
              model output for current time step.
          """