code: def _get_strategy(self):
      # We can cache the strategy as TPUEmbeddingV0 doesn't require
      # reconfiguration to the tpu.
      if hasattr(self, "strategy"):
          return self.strategy
      return super(TPUEmbeddingCheckpointTest, self)._get_strategy()
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.ops import init_ops_v2
  from tensorflow.python.platform import test
  from tensorflow.python.saved_model import load
  from tensorflow.python.saved_model import save
  from tensorflow.python.tpu import tpu_embedding_for_serving
  from tensorflow.python.tpu import tpu_embedding_v1
  from tensorflow.python.tpu import tpu_embedding_v2_utils
  from tensorflow.python.tpu.tests import tpu_embedding_base_test
  from tensorflow.python.training import checkpoint_utils
label_desc: Use image node_id 1 for calling the TPUEmbeddingCheckpointTest obj's underlying member method code with example usage: obj._get_strategy() and returns: super, self