code: def testDotDifferentBatchDimensionsSizes(self):
      a = array_ops.placeholder(np.float32, shape=(2, 2, 2, 2))
      b = array_ops.placeholder(np.float32, shape=(4, 4, 4, 2))
  
      dim_nums = xla_data_pb2.DotDimensionNumbers()
      dim_nums.lhs_contracting_dimensions.append(2)
      dim_nums.rhs_contracting_dimensions.append(3)
      dim_nums.lhs_batch_dimensions.append(0)
      dim_nums.rhs_batch_dimensions.append(0)
  
      with self.assertRaisesRegex(
          ValueError, "Dimensions must be equal, but are 2 and 4"
      ):
          xla.dot_general(a, b, dim_nums)
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.compiler.tf2xla.ops import gen_xla_ops
  from tensorflow.compiler.tf2xla.python import xla
  from local_xla.xla import xla_data_pb2
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import function
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import random_ops_util
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 5 for calling the XlaOpsShapeInferenceTest obj's underlying member method code with example usage: obj.testDotDifferentBatchDimensionsSizes() without return types