code: def testConv3D1x1x1Filter2x1x1Dilation(
      self, data_format, use_gpu, op_name
  ):
      ctx = context.context()
      is_eager = ctx is not None and ctx.executing_eagerly()
      if test.is_gpu_available(cuda_only=True) or (
          test_util.IsMklEnabled() and is_eager is False
      ):
          self._VerifyDilatedConvValues(
              tensor_in_sizes=[1, 3, 6, 1, 1],
              filter_in_sizes=[1, 1, 1, 1, 1],
              stride=1,
              padding="VALID",
              dilations=[2, 1, 1],
              data_format=data_format,
              use_gpu=use_gpu,
              op_name=op_name,
          )
  
imports: import math
  from absl.testing import parameterized
  import numpy
  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 tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import nn_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util.compat import collections_abc
  from tensorflow.python.eager import context
label_desc: Use image node_id 11 for calling the Conv3DTest obj's underlying member method code with example usage: obj.testConv3D1x1x1Filter2x1x1Dilation(data_format, use_gpu, op_name) without return types