Constructs a RaggedTensorValue from a nested Python list.
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Compat aliases for migration
See Migration guide for more details.
tf.ragged.constant_value(
pylist, dtype=None, ragged_rank=None, inner_shape=None, row_splits_dtype='int64'
)
Example:
ragged.constant_value([[1, 2], [3], [4, 5, 6]])
RaggedTensorValue(values=[1, 2, 3, 4, 5, 6], splits=[0, 2, 3, 6])
All scalar values in pylist
must have the same nesting depth K
, and the
returned RaggedTensorValue
will have rank K
. If pylist
contains no
scalar values, then K
is one greater than the maximum depth of empty lists
in pylist
. All scalar values in pylist
must be compatible with dtype
.
Args | |
---|---|
pylist
|
A nested list , tuple or np. . Any nested element that
is not a list or tuple must be a scalar value compatible with dtype .
|
dtype
|
numpy. . The type of elements for the returned RaggedTensor .
If not specified, then a default is chosen based on the scalar values in
pylist .
|
ragged_
|
An integer specifying the ragged rank of the returned
RaggedTensorValue . Must be nonnegative and less than K . Defaults to
max( if inner_ is not specified. Defaults to `max(0, K
|
Returns | |
---|---|
A tf.RaggedTensorValue or numpy.array with rank K and the specified
ragged_rank , containing the values from pylist .
|
Raises | |
---|---|
ValueError
|
If the scalar values in pylist have inconsistent nesting
depth; or if ragged_rank or inner_shape are incompatible with pylist .
|