def apply_dropout(inputs, size = None, is_training = True , whether_dropout = False , whether_zoneout = False):
'''
Implementation of Zoneout from https://arxiv.org/pdf/1606.01305.pdf
'''
if whether_dropout is False and whether_zoneout is False:
return inputs
if whether_zoneout is not False:
return ZoneoutWrapper(inputs, state_zoneout_prob= whether_zoneout, is_training = is_training)
elif is_training:
return tf.contrib.rnn.DropoutWrapper(inputs,
output_keep_prob = 1 - whether_dropout, # if it is constant and 1, no output dropout will be added.
# variational_recurrent = True,
# input_size = size,
dtype = tf.float32)
else:
return inputs
def apply_dropout(inputs, size = None, is_training = True):
'''
Implementation of Zoneout from https://arxiv.org/pdf/1606.01305.pdf
'''
if Params.dropout is None and Params.zoneout is None:
return inputs
if Params.zoneout is not None:
return ZoneoutWrapper(inputs, state_zoneout_prob= Params.zoneout, is_training = is_training)
elif is_training:
return tf.contrib.rnn.DropoutWrapper(inputs,
output_keep_prob = 1 - Params.dropout,
# variational_recurrent = True,
# input_size = size,
dtype = tf.float32)
else:
return inputs