parameters: (self, x, states_prev, scope=None)
docstring: Long short-term memory cell (LSTM).
docstring_summary: Long short-term memory cell (LSTM).
docstring_tokens: Long short - term memory cell ( LSTM ) .
function: def __call__(self, x, states_prev, scope=None):
      """Long short-term memory cell (LSTM)."""
      with vs.variable_scope(scope or type(self).__name__):
        x_shape = x.get_shape().with_rank(2)
        if not x_shape[1]:
          raise ValueError("Expecting x_shape[1] to be sets: %s" % str(x_shape))
        if len(states_prev) != 2:
          raise ValueError("Expecting states_prev to be a tuple with length 2.")
        input_size = x_shape[1]
        w = vs.get_variable("W", [input_size + self._num_units,
                                  self._num_units * 4])
        b = vs.get_variable("b", [w.get_shape().with_rank(2)[1]],
                            initializer=init_ops.constant_initializer(0.0))
        wci = vs.get_variable("wci", [self._num_units])
        wco = vs.get_variable("wco", [self._num_units])
        wcf = vs.get_variable("wcf", [self._num_units])
        (cs_prev, h_prev) = states_prev
        (_, cs, _, _, _, _, h) = _lstm_fused_cell(x,
                                                  cs_prev,
                                                  h_prev,
                                                  w,
                                                  b,
                                                  wci=wci,
                                                  wco=wco,
                                                  wcf=wcf,
                                                  forget_bias=self._forget_bias,
                                                  use_peephole=self._use_peephole)
  
        return (h, (cs, h))
function_tokens: def __call__ ( self , x , states_prev , scope = None ) : with vs . variable_scope ( scope or type ( self ) . __name__ ) : x_shape = x . get_shape ( ) . with_rank ( 2 ) if not x_shape [ 1 ] : raise ValueError ( "Expecting x_shape[1] to be sets: %s" % str ( x_shape ) ) if len ( states_prev ) != 2 : raise ValueError ( "Expecting states_prev to be a tuple with length 2." ) input_size = x_shape [ 1 ] w = vs . get_variable ( "W" , [ input_size + self . _num_units , self . _num_units * 4 ] ) b = vs . get_variable ( "b" , [ w . get_shape ( ) . with_rank ( 2 ) [ 1 ] ] , initializer = init_ops . constant_initializer ( 0.0 ) ) wci = vs . get_variable ( "wci" , [ self . _num_units ] ) wco = vs . get_variable ( "wco" , [ self . _num_units ] ) wcf = vs . get_variable ( "wcf" , [ self . _num_units ] ) ( cs_prev , h_prev ) = states_prev ( _ , cs , _ , _ , _ , _ , h ) = _lstm_fused_cell ( x , cs_prev , h_prev , w , b , wci = wci , wco = wco , wcf = wcf , forget_bias = self . _forget_bias , use_peephole = self . _use_peephole ) return ( h , ( cs , h ) )