wassname/ray
1
0
Fork 0
mirror of https://github.com/wassname/ray.git synced 2026-07-23 13:10:11 +08:00
Code Issues Packages Projects Releases Wiki Activity

[testing] Adding useful error messages for long_running_tests (#8960)

Browse Source
This commit is contained in:
Ian Rodney
2020-06-17 18:32:35 -07:00
committed by GitHub
parent 8f9b465968
commit 5208f8db12
4 changed files with 4 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files
ci/long_running_tests/workloads/actor_deaths.py
+1 -1
View File
@@ -15,7 +15,7 @@ num_nodes = 2
message = ("Make sure there is enough memory on this machine to run this "
"workload. We divide the system memory by 2 to provide a buffer.")
assert (num_nodes * object_store_memory + num_redis_shards * redis_max_memory <
ray.utils.get_system_memory() / 2)
ray.utils.get_system_memory() / 2), message
# Simulate a cluster on one machine.
ci/long_running_tests/workloads/many_drivers.py
+1 -1
View File
@@ -14,7 +14,7 @@ num_nodes = 4
message = ("Make sure there is enough memory on this machine to run this "
"workload. We divide the system memory by 2 to provide a buffer.")
assert (num_nodes * object_store_memory + num_redis_shards * redis_max_memory <
ray.utils.get_system_memory() / 2)
ray.utils.get_system_memory() / 2), message
# Simulate a cluster on one machine.
ci/long_running_tests/workloads/many_tasks.py
+1 -1
View File
@@ -15,7 +15,7 @@ num_nodes = 10
message = ("Make sure there is enough memory on this machine to run this "
"workload. We divide the system memory by 2 to provide a buffer.")
assert (num_nodes * object_store_memory + num_redis_shards * redis_max_memory <
ray.utils.get_system_memory() / 2)
ray.utils.get_system_memory() / 2), message
# Simulate a cluster on one machine.
ci/long_running_tests/workloads/many_tasks_serialized_ids.py
+1 -1
View File
@@ -18,7 +18,7 @@ num_nodes = 10
message = ("Make sure there is enough memory on this machine to run this "
"workload. We divide the system memory by 2 to provide a buffer.")
assert (num_nodes * object_store_memory + num_redis_shards * redis_max_memory <
ray.utils.get_system_memory() / 2)
ray.utils.get_system_memory() / 2), message
# Simulate a cluster on one machine.