message: Remove 'not trainable' int types from NCCL gradient tests.
diff: @@ -19,6 +19,7 @@ from __future__ import division
  from __future__ import print_function
  from functools import partial
  +import os
  import numpy as np
  from tensorflow.contrib import nccl
  @@ -60,6 +61,7 @@ class NcclTestCase(test.TestCase):
  def _Test(self,
  nccl_reduce,
  numpy_fn,
  + dtypes=[np.float16, np.float32, np.int32, np.int64, np.float64],
  device_sets=(['/device:GPU:1', '/device:GPU:2', '/device:GPU:0'],
  ['/device:GPU:1', '/device:GPU:0'])):
  """Tests that nccl_reduce does the same as reduction with numpy_fn.
  @@ -72,7 +74,10 @@ class NcclTestCase(test.TestCase):
  two.
  device_sets: Tuple of virtual devices to run test on.
  """
  - for dtype in [np.float16, np.float32, np.int32, np.int64, np.float64]:
  + # Enable NCCL printouts.
  + os.environ["NCCL_DEBUG"] = "INFO"
  +
  + for dtype in dtypes:
  # Create session inside outer loop to test use of
  # same communicator across multiple sessions.
  with self.test_session(use_gpu=True) as sess:
  @@ -124,7 +129,8 @@ class NcclTestCase(test.TestCase):
  reduce_tensors, inputs, losses, colocate_gradients_with_ops=True)
  return [g for g in grads if g is not None]
  - self._Test(_Gradient, numpy_fn)
  + # int types are considered not 'trainable' and no gradients are generated.
  + self._Test(_Gradient, numpy_fn, dtypes=[np.float16, np.float32, np.float64])
  class AllReduceTest(NcclTestCase):
  