tf.ragged.constant

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Constructs a constant RaggedTensor from a nested Python list.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.ragged.constant, `tf.compat.v2.ragged.constant`

tf.ragged.constant(
    pylist, dtype=None, ragged_rank=None, inner_shape=None, name=None,
    row_splits_dtype=tf.dtypes.int64
)

Example:

ragged.constant([[1, 2], [3], [4, 5, 6]]).eval()
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 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.