code: def model_supports_jit(model):
      # XLA not supported with TF on MacOS GPU
      if (
          platform.system() == "Darwin"
          and "arm" in platform.processor().lower()
      ):
          if backend.backend() == "tensorflow":
              from keras.utils.module_utils import tensorflow as tf
  
              if tf.config.list_physical_devices("GPU"):
                  return False
      # XLA not supported by some layers
      if all(x.supports_jit for x in model._flatten_layers()):
          return True
      return False
  
imports: import platform
  import warnings
  import tree
  from keras import backend
  from keras import metrics
  from keras import ops
  from keras import optimizers
  from keras.optimizers.loss_scale_optimizer import LossScaleOptimizer
  from keras.saving import serialization_lib
  from keras.trainers.compile_utils import CompileLoss
  from keras.trainers.compile_utils import CompileMetrics
  from keras.trainers.data_adapters import data_adapter_utils
  from keras.utils import traceback_utils
  from keras.utils import tracking
label_desc: Use image node_id 1 for calling a global function with example usage: model_supports_jit(model) and returns: False, True, False