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[tensor]add 1D device mesh (#1492)

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YuliangLiu0306
2022-08-25 16:48:12 +08:00
committed by GitHub
parent b8d0e39eaf
commit 4b03c25f85
4 changed files with 66 additions and 13 deletions
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28
tests/test_tensor/test_comm_spec_apply.py
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@@ -133,13 +133,36 @@ def check_all_reduce(device_mesh, rank):
# device_mesh_shape: (2, 2)
sharding_spec = ShardingSpec(device_mesh, tensor_to_comm.shape, dim_partition_dict=dim_partition_dict)
# CommSpec:CommSpec:(comm_pattern:all_reduce, logical_process_axis:0)
# CommSpec:(comm_pattern:all_reduce, logical_process_axis:0)
comm_spec = CommSpec(CollectiveCommPattern.ALLREDUCE, sharding_spec, logical_process_axis=0)
comm_spec.covert_spec_to_action(tensor_to_comm)
assert tensor_to_comm.equal(tensor_to_check)
def check_all_reduce_in_flatten_device_mesh(device_mesh, rank):
# tensor to comm
tensor_to_comm = torch.ones(2, 2).cuda() * rank
# reduce through logical process axis 0 at flatten device mesh
# tensor to check
# tensor([[6., 6.],
# [6., 6.]])
tensor_to_check = torch.tensor([[6, 6], [6, 6]], dtype=tensor_to_comm.dtype).cuda()
dim_partition_dict = {}
# DistSpec:
# shard_sequence: R,R
# device_mesh_shape: (2, 2)
sharding_spec = ShardingSpec(device_mesh, tensor_to_comm.shape, dim_partition_dict=dim_partition_dict)
# CommSpec:(comm_pattern:all_reduce, logical_process_axis:[0, 1])
comm_spec = CommSpec(CollectiveCommPattern.ALLREDUCE, sharding_spec, logical_process_axis=[0, 1])
comm_spec.covert_spec_to_action(tensor_to_comm)
assert tensor_to_comm.equal(tensor_to_check)
def check_comm(rank, world_size, port):
disable_existing_loggers()
launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
@@ -162,6 +185,9 @@ def check_comm(rank, world_size, port):
# test all reduce
check_all_reduce(device_mesh, rank)
# test all reduce in 1D flatten device mesh
check_all_reduce_in_flatten_device_mesh(device_mesh, rank)
gpc.destroy()

1
tests/test_tensor/test_shape_consistency_apply.py
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@@ -64,7 +64,6 @@ def check_apply(rank, world_size, port):
tensor_to_comm.sharding_spec = sharding_spec_source
shape_consistency_manager.apply(tensor_to_comm, sharding_spec_target)
print(tensor_to_comm)
assert tensor_to_comm.equal(tensor_to_check)
assert str(tensor_to_comm.sharding_spec.sharding_sequence) == str(sharding_spec_target.sharding_sequence)