code: def deserialize(name, custom_objects=None):
      if name is None:
          return None
  
      elif isinstance(name, str):
          if custom_objects and name in custom_objects:
              return custom_objects.get(name)
  
          # To replicate tensorflow framework
          elif (
              ivy.current_backend().__name__.split(".")[-1]
              == "tensorflow"
              and name in tf_frontend.keras.activations.__dict__
          ):  # noqa
              return tf_frontend.keras.activations.__dict__[name]
  
          # On other backends, query the function from global ivy dict
          elif name in ACTIVATION_FUNCTIONS:
              return ivy.__dict__[name]
  
          else:
              raise ValueError(f"Unknown activation function: {name}.")
  
      else:
          raise ValueError(
              f"Could not interpret activation function: {name}"
          )
  
file_path: ivy/ivy/functional/frontends/tensorflow/keras/activations.py
imports: import ivy
  import ivy.functional.frontends.tensorflow
  from ivy.functional.frontends.tensorflow.func_wrapper import to_ivy_arrays_and_back
  from ivy import with_supported_dtypes
label_desc: Use image node_id 1 for calling a global function with example usage: deserialize(name, custom_objects) and returns: None, custom_objects, tf_frontend, ivy