code: def _shape_match(model_shape, dataset_shape):
      for i in range(len(dataset_shape)):
          if dataset_shape[i].value is None:
              return model_shape[i].value is None
          else:
              return (
                  dataset_shape[i].value == model_shape[i].value
                  or model_shape[i].value is None
              )
  
imports: import json
  import logging
  import os
  import sys
  import tempfile
  from bigdl.dllib.nn.criterion import Criterion
  from bigdl.dllib.nn.layer import Layer
  from bigdl.dllib.optim.optimizer import MaxEpoch, EveryEpoch
  from bigdl.dllib.utils.common import to_list, JavaValue
  from bigdl.dllib.utils.file_utils import callZooFunc
  from bigdl.dllib.feature.common import FeatureSet
  from bigdl.dllib.keras.engine.topology import to_bigdl_metric, Loss, OptimMethod
  from bigdl.dllib.net.utils import find_placeholders, to_bigdl_optim_method, find_tensors
  from bigdl.dllib.estimator.estimator import Estimator
  from bigdl.dllib.utils import nest
  from bigdl.dllib.utils.triggers import EveryEpoch
  from bigdl.dllib.utils.triggers import ZooTrigger
  from bigdl.orca.tfpark.tf_dataset import TFNdarrayDataset, check_data_compatible
  from bigdl.orca.tfpark.tf_dataset import _standarize_feature_label_dataset
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 11 for calling the TFOptimizer obj's underlying member method code with example usage: obj._shape_match(model_shape, dataset_shape) and returns: unknown, unknown