code: def constant(
      pylist,
      dtype=None,
      ragged_rank=None,
      inner_shape=None,
      name=None,
      row_splits_dtype=dtypes.int64,
  ) -> Union[
      ragged_tensor.RaggedTensor, ops._EagerTensorBase, ops.Operation
  ]:
      """Constructs a constant RaggedTensor from a nested Python list.
  
      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`.
      """
  
      def ragged_factory(values, row_splits):
          row_splits = constant_op.constant(
              row_splits, dtype=row_splits_dtype
          )
          return ragged_tensor.RaggedTensor.from_row_splits(
              values, row_splits, validate=False
          )
  
      with ops.name_scope(name, "RaggedConstant"):
          return _constant_value(
              ragged_factory,
              constant_op.constant,
              pylist,
              dtype,
              ragged_rank,
              inner_shape,
          )
  
file_path: tensorflow-upstream/tensorflow/python/ops/ragged/ragged_factory_ops.py
imports: from typing import Union
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import ragged_tensor_value
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 for calling a global function with example usage: constant(pylist, dtype, ragged_rank, inner_shape, name, row_splits_dtype) and returns: ragged_tensor, _constant_value