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Applies op
to the flat_values
of one or more RaggedTensors.
tf.ragged.map_flat_values(
op, *args, **kwargs
)
Replaces any RaggedTensor
in args
or kwargs
with its flat_values
tensor (which collapses all ragged dimensions), and then calls op
. Returns
a RaggedTensor
that is constructed from the input RaggedTensor
s'
nested_row_splits
and the value returned by the op
.
If the input arguments contain multiple RaggedTensor
s, then they must have
identical nested_row_splits
.
This operation is generally used to apply elementwise operations to each value
in a RaggedTensor
.
Examples:
rt = tf.ragged.constant([[1, 2, 3], [], [4, 5], [6]])
tf.ragged.map_flat_values(tf.ones_like, rt)
<tf.RaggedTensor [[1, 1, 1], [], [1, 1], [1]]>
tf.ragged.map_flat_values(tf.multiply, rt, rt)
<tf.RaggedTensor [[1, 4, 9], [], [16, 25], [36]]>
tf.ragged.map_flat_values(tf.add, rt, 5)
<tf.RaggedTensor [[6, 7, 8], [], [9, 10], [11]]>
Example with a non-elementwise operation (note that map_flat_values
and
map_fn
return different results):
rt = tf.ragged.constant([[1.0, 3.0], [], [3.0, 6.0, 3.0]])
def normalized(x):
return x / tf.reduce_sum(x)
tf.ragged.map_flat_values(normalized, rt)
<tf.RaggedTensor [[0.0625, 0.1875], [], [0.1875, 0.375, 0.1875]]>
tf.map_fn(normalized, rt)
<tf.RaggedTensor [[0.25, 0.75], [], [0.25, 0.5, 0.25]]>
Returns | |
---|---|
A RaggedTensor whose ragged_rank matches the ragged_rank of all
input RaggedTensor s.
|
Raises | |
---|---|
ValueError
|
If args contains no RaggedTensors , or if the nested_splits
of the input RaggedTensor s are not identical.
|