code: def populate_deserializable_objects():
      """Populates dict ALL_OBJECTS with every built-in layer."""
      global LOCAL
      if not hasattr(LOCAL, "ALL_OBJECTS"):
          LOCAL.ALL_OBJECTS = {}
          LOCAL.GENERATED_WITH_V2 = None
  
      if LOCAL.ALL_OBJECTS and LOCAL.GENERATED_WITH_V2 == tf2.enabled():
          # Objects dict is already generated for the proper TF version:
          # do nothing.
          return
  
      LOCAL.ALL_OBJECTS = {}
      LOCAL.GENERATED_WITH_V2 = tf2.enabled()
  
      base_cls = base_layer.Layer
      generic_utils.populate_dict_with_module_objects(
          LOCAL.ALL_OBJECTS,
          ALL_MODULES,
          obj_filter=lambda x: inspect.isclass(x)
          and issubclass(x, base_cls),
      )
  
      # Overwrite certain V1 objects with V2 versions
      if tf2.enabled():
          generic_utils.populate_dict_with_module_objects(
              LOCAL.ALL_OBJECTS,
              ALL_V2_MODULES,
              obj_filter=lambda x: inspect.isclass(x)
              and issubclass(x, base_cls),
          )
  
      # Prevent circular dependencies.
      from tensorflow.python.keras import (
          models,
      )  # pylint: disable=g-import-not-at-top
  
      LOCAL.ALL_OBJECTS["Input"] = input_layer.Input
      LOCAL.ALL_OBJECTS["InputSpec"] = input_spec.InputSpec
      LOCAL.ALL_OBJECTS["Functional"] = models.Functional
      LOCAL.ALL_OBJECTS["Model"] = models.Model
      LOCAL.ALL_OBJECTS["Sequential"] = models.Sequential
  
      # Merge layers, function versions.
      LOCAL.ALL_OBJECTS["add"] = merge.add
      LOCAL.ALL_OBJECTS["subtract"] = merge.subtract
      LOCAL.ALL_OBJECTS["multiply"] = merge.multiply
      LOCAL.ALL_OBJECTS["average"] = merge.average
      LOCAL.ALL_OBJECTS["maximum"] = merge.maximum
      LOCAL.ALL_OBJECTS["minimum"] = merge.minimum
      LOCAL.ALL_OBJECTS["concatenate"] = merge.concatenate
      LOCAL.ALL_OBJECTS["dot"] = merge.dot
  
file_path: tensorflow-upstream/tensorflow/python/keras/layers/serialization.py
imports: import threading
  from tensorflow.python import tf2
  from tensorflow.python.keras.engine import base_layer
  from tensorflow.python.keras.engine import input_layer
  from tensorflow.python.keras.engine import input_spec
  from tensorflow.python.keras.layers import advanced_activations
  from tensorflow.python.keras.layers import convolutional
  from tensorflow.python.keras.layers import convolutional_recurrent
  from tensorflow.python.keras.layers import core
  from tensorflow.python.keras.layers import dense_attention
  from tensorflow.python.keras.layers import embeddings
  from tensorflow.python.keras.layers import merge
  from tensorflow.python.keras.layers import pooling
  from tensorflow.python.keras.layers import recurrent
  from tensorflow.python.keras.layers import rnn_cell_wrapper_v2
  from tensorflow.python.keras.utils import generic_utils
  from tensorflow.python.keras.utils import tf_inspect
label_desc: Use image node_id 1 for calling a global function with example usage: populate_deserializable_objects() without return types