deepy/core/graph.py
def scan(self, func, sequences=None, outputs=None, non_sequences=None, block=None, **kwargs):
        """
        A loop function, the usage is identical with the theano one.
        :type block: deepy.layers.Block
        """
        results, updates = Scanner(func, sequences, outputs, non_sequences, neural_computation=True, **kwargs).compute()
        if block and updates:
            if type(updates) == dict:
                updates = updates.items()
            block.register_updates(*updates)
        return results
def scan(self, func, sequences=None, outputs=None, non_sequences=None, block=None, **kwargs):
        """
        A loop function, the usage is identical with the theano one.
        :type block: deepy.layers.Block
        """
        results, updates = Scanner(func, sequences, outputs, non_sequences, neural_computation=True, **kwargs).compute()
        if block and updates:
            if type(updates) == dict:
                updates = updates.items()
            block.register_updates(*updates)
        return results
def scan ( self , func , sequences = None , outputs = None , non_sequences = None , block = None , * * kwargs ) : results , updates = Scanner ( func , sequences , outputs , non_sequences , neural_computation = True , * * kwargs ) . compute ( ) if block and updates : if type ( updates ) == dict : updates = updates . items ( ) block . register_updates ( * updates ) return results
A loop function, the usage is identical with the theano one.
        :type block: deepy.layers.Block
A loop function the usage is identical with the theano one . : type block : deepy . layers . Block