问题
I have a tensor of lengths in tensorflow, let's say it looks like this:
[4, 3, 5, 2]
I wish to create a mask of 1s and 0s whose number of 1s correspond to the entries to this tensor, padded by 0s to a total length of 8. I.e. I want to create this tensor:
[[1,1,1,1,0,0,0,0],
[1,1,1,0,0,0,0,0],
[1,1,1,1,1,0,0,0],
[1,1,0,0,0,0,0,0]
]
How might I do this?
回答1:
This can be achieved using a variety of TensorFlow transformations:
# Make a 4 x 8 matrix where each row contains the length repeated 8 times.
lengths = [4, 3, 5, 2]
lengths_transposed = tf.expand_dims(lengths, 1)
# Make a 4 x 8 matrix where each row contains [0, 1, ..., 7]
range = tf.range(0, 8, 1)
range_row = tf.expand_dims(range, 0)
# Use the logical operations to create a mask
mask = tf.less(range_row, lengths_transposed)
# Use the select operation to select between 1 or 0 for each value.
result = tf.select(mask, tf.ones([4, 8]), tf.zeros([4, 8]))
回答2:
This can now be achieved by tf.sequence_mask
. More details here.
回答3:
I've got a bit shorter version, than previous answer. Not sure if it is more efficient or not
def mask(self, seq_length, max_seq_length):
return tf.map_fn(
lambda x: tf.pad(tf.ones([x], dtype=tf.int32), [[0, max_seq_length - x]]),
seq_length)
来源:https://stackoverflow.com/questions/34128104/tensorflow-creating-mask-of-varied-lengths