class_docstr: Tests of input_fn, doing end-to-end I/O.
  
  These tests instantiate an input stream and then check it in various ways,
  in increasing complexity.
class_docstr_tok: ["Tests","of","input_fn",",","doing","end-to-end","I\/O",".","These","tests","instantiate","an","input","stream","and","then","check","it","in","various","ways",",","in","increasing","complexity","."]
code: def get_batch_feed(self, batch_size=1, use_tpu=False):
      # This is an input_fn reading test_utils.N_GOLDEN_CALLING_EXAMPLES records.
      # Use PREDICT mode so we get finite input.
      dvi = data_providers.DeepVariantInput(
          mode=tf_estimator.ModeKeys.PREDICT,
          input_file_spec=testdata.GOLDEN_CALLING_EXAMPLES,
          num_examples=testdata.N_GOLDEN_CALLING_EXAMPLES,
          tensor_shape=None,
          use_tpu=use_tpu,
      )
      params = {"batch_size": batch_size}
      batch_feed = tf.compat.v1.data.make_one_shot_iterator(
          dvi(params)
      ).get_next()
      return batch_feed
  
imports: import math
  from absl.testing import absltest
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow import estimator
  from deepvariant import data_providers
  from deepvariant import dv_config
  from deepvariant import dv_constants
  from deepvariant import dv_utils
  from deepvariant import testdata
  from deepvariant.protos import deepvariant_pb2
  from third_party.nucleus.io import tfrecord
  from third_party.nucleus.testing import test_utils
  from third_party.nucleus.util import variant_utils
  from tensorflow.core.example import example_pb2
label_desc: Use image node_id 1 for calling the InputTest obj's underlying member method code with example usage: obj.get_batch_feed(batch_size, use_tpu) and returns: batch_feed