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)