mirror of https://github.com/hpcaitech/ColossalAI
fix
parent
6705dad41b
commit
3fab92166e
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@ -442,8 +442,7 @@ class RingAttention(torch.autograd.Function):
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Tuple[dist.ProcessGroup, dist.ProcessGroup]: Inner-ring process group and inter-ring process group.
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"""
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sp_size = dist.get_world_size(sp_group)
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dist.get_rank(sp_group)
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dist.get_world_size(tp_group)
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tp_size = dist.get_world_size(tp_group)
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if inner_ring_size is None:
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if torch.cuda.device_count() >= dist.get_world_size():
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@ -476,21 +475,38 @@ class RingAttention(torch.autograd.Function):
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rank = dist.get_rank()
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groups = int(world_size / sp_size)
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# Create inner ring groups
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for group_id in range(groups):
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for i in range(inner_ring_size):
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ranks = list(range(i + (group_id * sp_size), (1 + group_id) * sp_size, inner_ring_size))
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group = dist.new_group(ranks)
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if tp_size > 1:
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for group_id in range(groups):
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for i in range(inner_ring_size):
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ranks = list(range(i + (group_id * sp_size), (1 + group_id) * sp_size, inner_ring_size))
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group = dist.new_group(ranks)
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if rank in ranks:
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inner_ring_group = group
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for group_id in range(groups):
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for i in range(num_rings):
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ranks = list(range(i + group_id * num_rings, world_size, sp_size))
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group = dist.new_group(ranks)
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if rank in ranks:
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inter_ring_group = group
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else:
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for i in range(sp_size // 2):
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ranks = list(range((i) * num_rings, (i + 1) * num_rings, 1))
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if rank in ranks:
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print(
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"rank:",
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rank,
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"inner ranks:",
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ranks,
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)
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group = dist.new_group(ranks)
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inner_ring_group = group
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# Create inter ring groups
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for group_id in range(groups):
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for i in range(num_rings):
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ranks = list(range(i + group_id * num_rings, world_size, sp_size))
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group = dist.new_group(ranks)
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if rank in ranks:
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inter_ring_group = group
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for group_id in range(num_rings):
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for i in range(num_rings):
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ranks = list(range(i + group_id * num_rings, world_size, inner_ring_size))
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ranks = [0, 1, 4, 5] if rank == 0 or rank == 1 or rank == 4 or rank == 5 else [2, 3, 6, 7]
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if rank in ranks:
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group = dist.new_group(ranks)
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inter_ring_group = group
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return inner_ring_group, inter_ring_group
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