Constructs a constant RaggedTensor from a nested Python list.
tf.ragged.constant(
pylist, dtype=None, ragged_rank=None, inner_shape=None, name=None,
row_splits_dtype=tf.dtypes.int64
)
Example:
tf.ragged.constant([[1, 2], [3], [4, 5, 6]])
<tf.RaggedTensor [[1, 2], [3], [4, 5, 6]]>
All scalar values in pylist must have the same nesting depth K, and the
returned RaggedTensor 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.ndarray. Any nested element that
is not a list, tuple or np.ndarray must be a scalar value
compatible with dtype.
|
dtype
|
The type of elements for the returned RaggedTensor. If not
specified, then a default is chosen based on the scalar values in
pylist.
|
ragged_rank
|
An integer specifying the ragged rank of the returned
RaggedTensor. Must be nonnegative and less than K. Defaults to
max(0, K - 1) if inner_shape is not specified. Defaults to `max(0, K
- 1 - len(inner_shape))
ifinner_shapeis specified.
</td>
</tr><tr>
<td>inner_shape</td>
<td>
A tuple of integers specifying the shape for individual inner
values in the returnedRaggedTensor. Defaults to()ifragged_rankis not specified. Ifragged_rankis specified, then a default is chosen
based on the contents ofpylist.
</td>
</tr><tr>
<td>name</td>
<td>
A name prefix for the returned tensor (optional).
</td>
</tr><tr>
<td>row_splits_dtype</td>
<td>
data type for the constructedRaggedTensor`'s row_splits.
One of tf.int32 or tf.int64.
|
Returns |
A potentially ragged tensor 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.
|