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: Trace with the layer/models inferred input signature if possible.
docstr_tok: ["Trace","with","the","layer\/models","inferred","input","signature","if","possible","."]
code: def trace_with_input_signature(self):
      """Trace with the layer/models inferred input signature if possible."""
      if (
          None not in nest.flatten(self._input_signature)
          and self._has_kwargs
      ):
          # Manually add traces for layers that have keyword arguments and have
          # a fully defined input signature.
          self.add_trace(*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 10 for calling the LayerCallCollection obj's underlying member method code with example usage: obj.trace_with_input_signature() without return types