def reverse_sequence(self, inputs, mask=None):
if mask is None:
return [x[:, ::-1] for x in inputs]
else:
length = K.cast(K.sum(mask, 1), 'int32')
return [tf.reverse_sequence(x, length, seq_axis=1) for x in inputs]
def beta2(self):
if self._beta2 is None:
iterations = K.cast(self.iterations + 1, K.floatx())
return 1.0 - K.pow(iterations, -0.8)
else:
return self._beta2
def call(self, inputs, mask=None):
if mask is not None:
mask = K.cast(mask, K.floatx())
return sequence_masking(inputs, mask, 1, 1)
