message: Use constant input test tensors instead of random tensors
  Otherwise the test sometimes fails depending on the generated
  random values.
diff: @@ -37,14 +37,11 @@ class ConstBroadcastTest(trt_test.TfTrtIntegrationTestBase):
  y1 = nn.conv2d(x, filt1, strides=[1, 1, 1, 1], padding='SAME', name='y1')
  z1 = nn.relu(y1, name='z1')
  filt2 = constant_op.constant(
  - np.random.randn(9), shape=(3, 3, 1, 1), dtype=dtype, name='filt2')
  + 0.3, shape=(3, 3, 1, 1), dtype=dtype, name='filt2')
  y2 = nn.conv2d(z1, filt2, strides=[1, 1, 1, 1], padding='SAME', name='y2')
  z2 = nn.relu(y2, name='z')
  filt3 = constant_op.constant(
  - np.random.randn(3, 3, 1, 1),
  - shape=(3, 3, 1, 1),
  - dtype=dtype,
  - name='filt3')
  + 0.3, shape=(3, 3, 1, 1), dtype=dtype, name='filt3')
  y3 = nn.conv2d(z2, filt3, strides=[1, 1, 1, 1], padding='SAME', name='y3')
  return nn.relu(y3, name='output_0')
  