code: def patch_model_callback():
      # if you have tensorboard, we assume you use TensorboardLogger, which we catch, so no need to patch.
      if (
          "tensorboard" in sys.modules
          and IsTensorboardInit.tensorboard_used()
      ):
          return
  
      try:
          from fastai.basic_train import Recorder
  
          Recorder.on_batch_end = _patched_call(
              Recorder.on_batch_end, PatchFastaiV1._on_batch_end
          )
          Recorder.on_backward_end = _patched_call(
              Recorder.on_backward_end, PatchFastaiV1._on_backward_end
          )
          Recorder.on_epoch_end = _patched_call(
              Recorder.on_epoch_end, PatchFastaiV1._on_epoch_end
          )
          Recorder.on_train_begin = _patched_call(
              Recorder.on_train_begin, PatchFastaiV1._on_train_begin
          )
      except ImportError:
          pass
      except Exception as ex:
          LoggerRoot.get_base_logger(PatchFastaiV1).debug(str(ex))
  
imports: import sys
  import numpy
  from clearml.utilities.version import Version
  from .None import _patched_call
  from .tensorflow_bind import WeightsGradientHistHelper
  from ..import_bind import PostImportHookPatching
  from ...debugging.log import LoggerRoot
  from .tensorflow_bind import IsTensorboardInit
label_desc: Use image node_id 2 for calling the PatchFastaiV1 obj's underlying member method code with example usage: obj.patch_model_callback() without return types