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)) 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.
 | 
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.
 |