From f6a5b733d539fd18b4577c9940189492cf4559e8 Mon Sep 17 00:00:00 2001 From: Eric Liang Date: Wed, 25 Nov 2020 12:45:47 -0800 Subject: [PATCH] Remove flaky object manager test that's no longer needed --- python/ray/tests/test_object_manager.py | 56 ------------------------- 1 file changed, 56 deletions(-) diff --git a/python/ray/tests/test_object_manager.py b/python/ray/tests/test_object_manager.py index 57074df1a..3d46c133d 100644 --- a/python/ray/tests/test_object_manager.py +++ b/python/ray/tests/test_object_manager.py @@ -7,7 +7,6 @@ import warnings import ray from ray.cluster_utils import Cluster -from ray.test_utils import wait_for_condition if (multiprocessing.cpu_count() < 40 or ray.utils.get_system_memory() < 50 * 10**9): @@ -194,61 +193,6 @@ def test_actor_broadcast(ray_start_cluster_with_resource): assert all(value == 1 for value in send_counts.values()) -# The purpose of this test is to make sure that an object that was already been -# transferred to a node can be transferred again. -def test_object_transfer_retry(ray_start_cluster): - cluster = ray_start_cluster - - # Force the sending object manager to allow duplicate pushes again sooner. - # Also, force the receiving object manager to retry the pull sooner. We - # make the chunk size smaller in order to make it easier to test objects - # with multiple chunks. - config = { - "object_manager_default_chunk_size": 1000, - "object_store_full_max_retries": 1, - } - object_store_memory = 150 * 1024 * 1024 - cluster.add_node( - object_store_memory=object_store_memory, _system_config=config) - cluster.add_node(num_gpus=1, object_store_memory=object_store_memory) - ray.init(address=cluster.address) - - @ray.remote(num_gpus=1) - def f(size): - return np.zeros(size, dtype=np.uint8) - - # Transfer an object to warm up the object manager. - ray.get(f.remote(10**6)) - - x_id = f.remote(10**6) - assert not ray.worker.global_worker.core_worker.object_exists(x_id) - - # Get the objects locally to cause them to be transferred. This is the - # first time the objects are getting transferred, so it should happen - # quickly. - ray.get(x_id) - - def not_exists(): - return not ray.worker.global_worker.core_worker.object_exists(x_id) - - def force_eviction(): - refs = [] - for _ in range(20): - try: - refs.append( - ray.put( - np.zeros(object_store_memory // 10, dtype=np.uint8))) - except Exception: - break - wait_for_condition(not_exists) - - # Force the object to be evicted from the local node. - force_eviction() - - # Get the object again and make sure it gets transferred. - ray.get(x_id) - - # The purpose of this test is to make sure we can transfer many objects. In the # past, this has caused failures in which object managers create too many open # files and run out of resources.