github/ColossalAI
1
0
Fork 0
mirror of https://github.com/hpcaitech/ColossalAI.git synced 2025-09-10 13:30:19 +00:00
Code Issues Packages Projects Releases Wiki Activity

[misc] update pre-commit and run all files (#4752)

Browse Source 
* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format
This commit is contained in:
Hongxin Liu
2023-09-19 14:20:26 +08:00
committed by GitHub
parent 3c6b831c26
commit 079bf3cb26
1268 changed files with 50037 additions and 38444 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
tests/test_tensor/test_comm_spec_apply.py
View File

@@ -29,10 +29,9 @@ def check_all_gather(device_mesh, rank):
sharding_spec = ShardingSpec(device_mesh, tensor_to_check.shape, dim_partition_dict=dim_partition_dict)
# CommSpec:(comm_pattern:allgather, gather_dim:1, logical_process_axis:1)
comm_spec = CommSpec(CollectiveCommPattern.GATHER_FWD_SPLIT_BWD,
sharding_spec,
gather_dim=1,
logical_process_axis=1)
comm_spec = CommSpec(
CollectiveCommPattern.GATHER_FWD_SPLIT_BWD, sharding_spec, gather_dim=1, logical_process_axis=1
)
sharded_tensor_to_comm = sharded_tensor_to_comm = comm_spec.covert_spec_to_action(sharded_tensor_to_comm)
assert sharded_tensor_to_comm.equal(tensor_to_check)
@@ -101,11 +100,9 @@ def check_all_to_all(device_mesh, rank):
sharding_spec = ShardingSpec(device_mesh, torch.Size((4, 2)), dim_partition_dict=dim_partition_dict)
# CommSpec:(comm_pattern:shard, shard_dim:1, logical_process_axis:1)
comm_spec = CommSpec(CollectiveCommPattern.ALL2ALL_FWD_ALL2ALL_BWD,
sharding_spec,
gather_dim=0,
shard_dim=1,
logical_process_axis=0)
comm_spec = CommSpec(
CollectiveCommPattern.ALL2ALL_FWD_ALL2ALL_BWD, sharding_spec, gather_dim=0, shard_dim=1, logical_process_axis=0
)
tensor_to_comm = comm_spec.covert_spec_to_action(tensor_to_comm)
assert tensor_to_comm.equal(tensor_to_check)
@@ -181,7 +178,7 @@ def check_all_reduce_in_flatten_device_mesh(device_mesh, rank):
def check_comm(rank, world_size, port):
disable_existing_loggers()
launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
launch(config={}, rank=rank, world_size=world_size, host="localhost", port=port, backend="nccl")
physical_mesh_id = torch.arange(0, 4)
assert rank == dist.get_rank()
@@ -214,5 +211,5 @@ def test_comm_spec():
spawn(check_comm, world_size)
if __name__ == '__main__':
if __name__ == "__main__":
test_comm_spec()