code: def testDropFinalBatch(self, batch_size, num_epochs):
      # Basic test: read from file 0.
      outputs = self.make_batch_feature(
          filenames=self._filenames[0],
          label_key="label",
          num_epochs=num_epochs,
          batch_size=batch_size,
          drop_final_batch=True,
      )
      for tensor in nest.flatten(outputs):
          if isinstance(
              tensor, tensor_lib.Tensor
          ):  # Guard against SparseTensor.
              self.assertEqual(tensor.shape[0], batch_size)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.ops import readers
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.kernel_tests import tf_record_test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import readers
  from tensorflow.python.data.util import nest
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import io_ops
  from tensorflow.python.ops import parsing_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 6 for calling the MakeBatchedFeaturesDatasetTest obj's underlying member method code with example usage: obj.testDropFinalBatch(batch_size, num_epochs) without return types