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.
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)) if inner_shape is specified.
inner_shape A tuple of integers specifying the shape for individual inner values in the returned RaggedTensor. Defaults to () if ragged_rank is not specified. If ragged_rank is specified, then a default is chosen based on the contents of pylist.
name A name prefix for the returned tensor (optional).
row_splits_dtype data type for the constructed RaggedTensor'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.