class_docstr: Tests for deterministic cuDNN functionality.
code: def testConvForwardXLA(self):
      in_shape = LayerShapeNCDHW(
          batch=2, channels=8, depth=5, height=12, width=15
      )
      filter_shape = FilterShape3D(
          depth=3, height=3, width=3, in_channels=8, out_channels=1
      )
      in_op = self._random_data_op(in_shape)
      filter_op = self._random_data_op(filter_shape)
      self._assert_reproducible(
          lambda: nn_ops.conv3d(
              in_op,
              filter_op,
              strides=[1, 1, 1, 1, 1],
              padding="VALID",
              data_format="NCDHW",
              dilations=[1, 1, 2, 2, 2],
          )
      )
  
imports: import collections
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling the ConvolutionTest obj's underlying member method code with example usage: obj.testConvForwardXLA() without return types