code: def concat(
      values: typing.List[ragged_tensor.RaggedOrDense], axis, name=None
  ):
      """Concatenates potentially ragged tensors along one dimension.
  
      Given a list of tensors with the same rank `K` (`K >= axis`), returns a
      rank-`K` `RaggedTensor` `result` such that `result[i0...iaxis]` is the
      concatenation of `[rt[i0...iaxis] for rt in values]`.
  
      Args:
        values: A list of potentially ragged tensors.  May not be empty. All
          `values` must have the same rank and the same dtype; but unlike
          `tf.concat`, they can have arbitrary shapes.
        axis: A python integer, indicating the dimension along which to concatenate.
          (Note: Unlike `tf.concat`, the `axis` parameter must be statically known.)
            Negative values are supported only if the rank of at least one
            `values` value is statically known.
        name: A name prefix for the returned tensor (optional).
  
      Returns:
        A `RaggedTensor` with rank `K`.
        `result.ragged_rank=max(axis, max(rt.ragged_rank for rt in values]))`.
  
      Raises:
        ValueError: If `values` is empty, if `axis` is out of bounds or if
          the input tensors have different ranks.
  
      #### Example:
  
      >>> t1 = tf.ragged.constant([[1, 2], [3, 4, 5]])
      >>> t2 = tf.ragged.constant([[6], [7, 8, 9]])
      >>> tf.concat([t1, t2], axis=0)
      <tf.RaggedTensor [[1, 2], [3, 4, 5], [6], [7, 8, 9]]>
      >>> tf.concat([t1, t2], axis=1)
      <tf.RaggedTensor [[1, 2, 6], [3, 4, 5, 7, 8, 9]]>
      """
      if not isinstance(values, (list, tuple)):
          values = [values]
      with ops.name_scope(name, "RaggedConcat", values):
          return _ragged_stack_concat_helper(
              values, axis, stack_values=False
          )
  
file_path: tensorflow-upstream/tensorflow/python/ops/ragged/ragged_concat_ops.py
imports: import typing
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_gather_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import ragged_util
  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: concat(values, axis, name) and returns: _ragged_stack_concat_helper