code: def jit_compile(self, value):
      if value and not model_supports_jit(self):
          warnings.warn(
              "Model doesn't support `jit_compile=True`. "
              "Proceeding with `jit_compile=False`."
          )
          self._jit_compile = False
      else:
          self._jit_compile = value
  
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 4 for calling the Trainer obj's underlying member method code with example usage: obj.jit_compile(value) without return types