(self, x, sequence_length)
Returns all outputs after iteration for all time steps
        
        High level overview of __call__:
        for step in steps:
            output, state = self.step(data[step])
        self.notify(all_states)
        
        
        :param x: inputs for all time steps of shape [batch_size, input_size, sequence_length]
        :return: list of two tensors [all_outputs, all_summaries]
Returns all outputs after iteration for all time steps
        
        High level overview of __call__:
        for step in steps:
            output, state = self.step(data[step])
        self.notify(all_states)
        
        
        :param x: inputs for all time steps of shape [batch_size, input_size, sequence_length]
        :return: list of two tensors [all_outputs, all_summaries]
Returns all outputs after iteration for all time steps High level overview of __call__ : for step in steps : output state = self . step ( data [ step ] ) self . notify ( all_states ) : param x : inputs for all time steps of shape [ batch_size input_size sequence_length ] : return : list of two tensors [ all_outputs all_summaries ]
def __call__(self, x, sequence_length):
        """
        Returns all outputs after iteration for all time steps
        
        High level overview of __call__:
        for step in steps:
            output, state = self.step(data[step])
        self.notify(all_states)
        
        
        :param x: inputs for all time steps of shape [batch_size, input_size, sequence_length]
        :return: list of two tensors [all_outputs, all_summaries]
        """
        raise NotImplementedError()
def __call__ ( self , x , sequence_length ) : raise NotImplementedError ( )