class_docstr: Function that triggers traces of other functions in the same collection.
class_docstr_tok: ["Function","that","triggers","traces","of","other","functions","in","the","same","collection","."]
docstr: Initializes a LayerCall object.
  
  Args:
    call_collection: a LayerCallCollection, which contains the other layer
      call functions (e.g. call_with_conditional_losses, call). These
      functions should be traced with the same arguments.
    call_fn: A call function.
    name: Name of the call function.
    input_signature: Input signature of call_fn (can be None).
docstr_tok: ["Initializes","a","LayerCall","object",".","Args",":","call_collection",":","a","LayerCallCollection",",","which","contains","the","other","layer","call","functions","(","e.g",".","call_with_conditional_losses",",","call",")",".","These","functions","should","be","traced","with","the","same","arguments",".","call_fn",":","A","call","function",".","name",":","Name","of","the","call","function",".","input_signature",":","Input","signature","of","call_fn","(","can","be","None",")","."]
code: def __init__(self, call_collection, call_fn, name, input_signature):
      """Initializes a LayerCall object.
  
      Args:
        call_collection: a LayerCallCollection, which contains the other layer
          call functions (e.g. call_with_conditional_losses, call). These
          functions should be traced with the same arguments.
        call_fn: A call function.
        name: Name of the call function.
        input_signature: Input signature of call_fn (can be None).
      """
      self.call_collection = call_collection
      self.input_signature = input_signature
      self.wrapped_call = def_function.function(
          layer_call_wrapper(call_collection, call_fn, name),
          input_signature=input_signature,
      )
      self.original_layer_call = call_collection.layer_call_method
  
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 1 to create a new LayerCall object from inherited base classes: object with example: obj = LayerCall(call_collection, call_fn, name, input_signature)