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TensorFlow 1 version
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View source on GitHub
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Applies a boolean mask to data without flattening the mask dimensions.
tf.ragged.boolean_mask(
data, mask, name=None
)
Returns a potentially ragged tensor that is formed by retaining the elements
in data where the corresponding value in mask is True.
output[a1...aA, i, b1...bB] = data[a1...aA, j, b1...bB]Where
jis theithTrueentry ofmask[a1...aA].
Note that output preserves the mask dimensions a1...aA; this differs
from tf.boolean_mask, which flattens those dimensions.
Args | |
|---|---|
data
|
A potentially ragged tensor. |
mask
|
A potentially ragged boolean tensor. mask's shape must be a prefix
of data's shape. rank(mask) must be known statically.
|
name
|
A name prefix for the returned tensor (optional). |
Returns | |
|---|---|
A potentially ragged tensor that is formed by retaining the elements in
data where the corresponding value in mask is True.
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Raises | |
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ValueError
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if rank(mask) is not known statically; or if mask.shape is
not a prefix of data.shape.
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Examples:
# Aliases for True & False so data and mask line up.T, F = (True, False)
tf.ragged.boolean_mask( # Mask a 2D Tensor.data=[[1, 2, 3], [4, 5, 6], [7, 8, 9]],mask=[[T, F, T], [F, F, F], [T, F, F]]).to_list()[[1, 3], [], [7]]
tf.ragged.boolean_mask( # Mask a 2D RaggedTensor.tf.ragged.constant([[1, 2, 3], [4], [5, 6]]),tf.ragged.constant([[F, F, T], [F], [T, T]])).to_list()[[3], [], [5, 6]]
tf.ragged.boolean_mask( # Mask rows of a 2D RaggedTensor.tf.ragged.constant([[1, 2, 3], [4], [5, 6]]),tf.ragged.constant([True, False, True])).to_list()[[1, 2, 3], [5, 6]]