class_docstr: A tf.TypeSpec for `AutoCompositeTensor` objects.
class_docstr_tok: ["A","tf.TypeSpec","for","`","AutoCompositeTensor","`","objects","."]
docstr: Returns true if `spec_or_value` is compatible with this TypeSpec.
docstr_tok: ["Returns","true","if","`","spec_or_value","`","is","compatible","with","this","TypeSpec","."]
code: def is_compatible_with(self, spec_or_value):
      """Returns true if `spec_or_value` is compatible with this TypeSpec."""
      if not isinstance(spec_or_value, tf.TypeSpec):
          spec_or_value = type_spec.type_spec_from_value(spec_or_value)
      if type(self) is not type(spec_or_value):
          return False
      return self._TypeSpec__is_compatible(
          self._comparable, spec_or_value._comparable
      )
  
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 10 for calling the _AutoCompositeTensorTypeSpec obj's underlying member method code with example usage: obj.is_compatible_with(spec_or_value) and returns: self, False