class_docstr: A tf.TypeSpec for `AutoCompositeTensor` objects.
class_docstr_tok: ["A","tf.TypeSpec","for","`","AutoCompositeTensor","`","objects","."]
docstr: Returns a TypeSpec compatible with `self`, with tensor names removed.
  
  Returns:
    A `TypeSpec` that is compatible with `self`, where the name of any
    `TensorSpec` is set to `None`.
docstr_tok: ["Returns","a","TypeSpec","compatible","with","`","self","`",",","with","tensor","names","removed",".","Returns",":","A","`","TypeSpec","`","that","is","compatible","with","`","self","`",",","where","the","name","of","any","`","TensorSpec","`","is","set","to","`","None","`","."]
code: def _without_tensor_names(self):
      """Returns a TypeSpec compatible with `self`, with tensor names removed.
  
      Returns:
        A `TypeSpec` that is compatible with `self`, where the name of any
        `TensorSpec` is set to `None`.
      """
  
      def rename(value):
          if isinstance(value, tf.TypeSpec):
              return (
                  value._without_tensor_names()
              )  # pylint: disable=protected-access
          else:
              return value
  
      return self._copy(
          param_specs=tf.nest.map_structure(rename, self._param_specs)
      )
  
imports: import contextlib
  import functools
  import threading
  import numpy
  import tensorflow.compat.v2
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import type_spec
  from tensorflow.python.framework import type_spec_registry
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.util import tf_inspect
  from tensorflow.python.util import variable_utils
label_desc: Use image node_id 13 for calling the _AutoCompositeTensorTypeSpec obj's underlying member method code with example usage: obj._without_tensor_names() and returns: self, value, value