experiments/STT-tensorflow
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Remove async runs of cluster update with pending nodes tests.

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Cluster update in parallel with async nodes is not supported yet.

PiperOrigin-RevId: 309269820
Change-Id: I825049e44f7098bcf323b381275b384b6636b1ff
This commit is contained in:
Haoyu Zhang 2020-04-30 11:51:27 -07:00 committed by TensorFlower Gardener
parent 0dc4fd5959
commit 3df3300d58
2 changed files with 0 additions and 4 deletions
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1
tensorflow/python/eager/BUILD
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@ -960,7 +960,6 @@ cuda_py_test(
shard_count = 8, shard_count = 8,
tags = [ tags = [
"no_oss", # This test launches local server "no_oss", # This test launches local server
"notap", # TODO(b/155407846)
], ],
deps = [ deps = [
"//tensorflow/python:array_ops", "//tensorflow/python:array_ops",

3
tensorflow/python/eager/remote_cluster_test.py
View File

@ -300,7 +300,6 @@ class DynamicClusterTest(test.TestCase, parameterized.TestCase):
y = worker_fn(x1) y = worker_fn(x1)
np.testing.assert_array_equal([[2, 2], [2, 2]], y.numpy()) np.testing.assert_array_equal([[2, 2], [2, 2]], y.numpy())
@test_util.run_in_async_and_sync_mode
def testPendingNodesServerReplaced(self): def testPendingNodesServerReplaced(self):
"""Update cluster when nodes are still pending on remote workers.""" """Update cluster when nodes are still pending on remote workers."""
with ops.device(self.device_local): with ops.device(self.device_local):
@ -371,10 +370,8 @@ class DynamicClusterTest(test.TestCase, parameterized.TestCase):
for result in t1_results + t2_results: for result in t1_results + t2_results:
np.testing.assert_array_equal([[2, 2], [2, 2]], result) np.testing.assert_array_equal([[2, 2], [2, 2]], result)
@test_util.run_in_async_and_sync_mode
def testMultiThreadPendingNodesLockFree(self): def testMultiThreadPendingNodesLockFree(self):
"""Update cluster when other remote function calls are being launched.""" """Update cluster when other remote function calls are being launched."""
self.skipTest("b/154053481")
with ops.device(self.device_t1): with ops.device(self.device_t1):
x1 = array_ops.ones([2, 2]) x1 = array_ops.ones([2, 2])