tf.ragged.constant

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
) -> Union[tf.RaggedTensor, ops._EagerTensorBase, tf.Operation]

Used in the notebooks

Used in the guide Used in the tutorials

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.

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. If there are no scalar values in pylist, then the default is tf.float32.
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<a id="inner_shape"></a> </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<a id="name"></a> </td> <td> A name prefix for the returned tensor (optional). </td> </tr><tr> <td>row_splits_dtype<a id="row_splits_dtype"></a> </td> <td> data type for the constructedRaggedTensor`'s row_splits. One of tf.int32 or tf.int64.

A potentially ragged tensor with rank K and the specified ragged_rank, containing the values from pylist.

ValueError If the scalar values in pylist have inconsistent nesting depth; or if ragged_rank or inner_shape are incompatible with pylist.