def restore(self, x):
"""Add padding back to the given tensor.
Args:
x (tf.Tensor): of shape [dim_compressed,...]
Returns:
a tensor of shape [dim_origin,...] with dim_compressed >= dim_origin. The
dim is restored from the original reference tensor
"""
with tf.name_scope("pad_reduce/restore"):
x = tf.scatter_nd(
indices=self.nonpad_ids,
updates=x,
shape=tf.concat([self.dim_origin, tf.shape(x)[1:]], axis=0),
)
return x
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