def learning_function(self):
network_updates = list(self.network.updates) + list(self.network.training_updates)<EOL>learning_updates = list(self._learning_updates())<EOL>update_list = network_updates + learning_updates<EOL>logging.info("<STR_LIT>" % "<STR_LIT:U+0020>".join(map(str, [x[<NUM_LIT:0>] for x in network_updates])))<EOL>logging.info("<STR_LIT>" % "<STR_LIT:U+0020>".join(map(str, [x[<NUM_LIT:0>] for x in learning_updates])))<EOL>variables = self.network.input_variables + self.network.target_variables<EOL>givens = None<EOL>return theano.function(<EOL>variables,<EOL>map(lambda v: theano.Out(v, borrow=True), self.training_variables),<EOL>updates=update_list, allow_input_downcast=True,<EOL>mode=self.config.get("<STR_LIT>", None),<EOL>givens=givens)<EOL>
Get the learning function.
:param func:
:return: