

@neural_computation
def get_initial_states(self, input_var):
    '\n        :type input_var: T.var\n        :rtype: dict\n        '
    initial_states = {
        
    }
    for state in self.state_names:
        initial_states[state] = T.alloc(np.cast[FLOATX](0.0), initial_states.shape[0], self.hidden_size)
    return initial_states

dataset/ETHPy150Open zomux/deepy/deepy/layers/recurrent.py RecurrentLayer.get_initial_states/VarMisuse@52/92 `input_var`->`initial_states`