@neural_computation<EOL><INDENT>def get_initial_states(self, input_var, init_state=None):<DEDENT>
initial_states = {}<EOL>for state in self.state_names:<EOL><INDENT>if state != "<STR_LIT:state>" or not init_state:<EOL><INDENT>if self._input_type == '<STR_LIT>' and input_var.ndim == <NUM_LIT:2>:<EOL><INDENT>init_state = T.alloc(np.cast[env.FLOATX](<NUM_LIT:0.>), self.hidden_size)<EOL><DEDENT>else:<EOL><INDENT>init_state = T.alloc(np.cast[env.FLOATX](<NUM_LIT:0.>), input_var.shape[<NUM_LIT:0>], self.hidden_size)<EOL><DEDENT><DEDENT>initial_states[state] = init_state<EOL><DEDENT>return initial_states<EOL>
:type input_var: T.var
:rtype: dict