class_docstr: Groups wrapped layer call functions.
  
  This is used to ensure that all layer call functions are traced with the same
  inputs-
    - call
    - call_and_return_conditional_losses
    - call_and_return_all_conditional_losses
class_docstr_tok: ["Groups","wrapped","layer","call","functions",".","This","is","used","to","ensure","that","all","layer","call","functions","are","traced","with","the","same","inputs-","-","call","-","call_and_return_conditional_losses","-","call_and_return_all_conditional_losses"]
docstr: Returns input signature for the wrapped layer call function.
docstr_tok: ["Returns","input","signature","for","the","wrapped","layer","call","function","."]
code: def fn_input_signature(self):
      """Returns input signature for the wrapped layer call function."""
      if self._has_kwargs:
          # Input signatures may only describe tensor arguments and kwargs are not
          # supported.
          return None
      if None in nest.flatten(self._input_signature):
          # TODO(b/134962016): If input signature cannot be partially defined.
          return None
      return self._input_signature
  
imports: import functools
  import threading
  import weakref
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import base_layer_utils
  from tensorflow.python.keras.engine import input_spec
  from tensorflow.python.keras.mixed_precision import autocast_variable
  from tensorflow.python.keras.saving import saving_utils
  from tensorflow.python.keras.saving.saved_model import constants
  from tensorflow.python.keras.saving.saved_model import load
  from tensorflow.python.keras.saving.saved_model import serialized_attributes
  from tensorflow.python.keras.saving.saved_model import utils
  from tensorflow.python.keras.utils import tf_contextlib
  from tensorflow.python.keras.utils import tf_inspect
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.keras.utils import version_utils
  from tensorflow.python.keras.utils.generic_utils import LazyLoader
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.trackable import data_structures
  from tensorflow.python.util import nest
  from tensorflow.python.util import tf_decorator
label_desc: Use image node_id 4 for calling the LayerCallCollection obj's underlying member method code with example usage: obj.fn_input_signature() and returns: self, None, None