code: def testEmptyBatch(self):
      inputs = constant_op.constant(
          [], dtype=dtypes.float32, shape=(1, 0, 2)
      )
      sequence_lengths = constant_op.constant([], dtype=dtypes.int32)
      labels = sparse_tensor.SparseTensor(
          indices=constant_op.constant(
              [], shape=(0, 2), dtype=dtypes.int64
          ),
          values=constant_op.constant(
              [], shape=(0,), dtype=dtypes.int32
          ),
          dense_shape=[5, 5],
      )
  
      with self.session(use_gpu=False) as sess:
          with self.assertRaisesRegex(
              errors_impl.InvalidArgumentError,
              "batch_size must not be 0",
          ):
              sess.run(_ctc_loss_v2(labels, inputs, sequence_lengths))
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  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 errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import ctc_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling the CTCLossTest obj's underlying member method code with example usage: obj.testEmptyBatch() without return types