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72 lines
2.4 KiB
72 lines
2.4 KiB
import pytest
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import torch
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import torch.distributed as dist
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from colossalai.legacy.communication import all_gather, all_reduce, reduce_scatter
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from colossalai.legacy.context import ParallelMode
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from colossalai.legacy.core import global_context as gpc
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from colossalai.legacy.initialize import launch
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from colossalai.testing import rerun_if_address_is_in_use, spawn
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from colossalai.utils import get_current_device
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CONFIG = dict(parallel=dict(data=8, pipeline=1, tensor=dict(mode=None, size=1)))
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SIZE = 8
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def check_all_gather():
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tensor = torch.tensor([dist.get_rank() * SIZE + j for j in range(SIZE)])
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tensor = tensor.to(get_current_device())
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print('Before: Rank {0} - {1}'.format(dist.get_rank(), tensor))
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tensor, op = all_gather(tensor, 0, ParallelMode.GLOBAL, async_op=True)
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print('After: Rank {0} - {1}'.format(dist.get_rank(), tensor))
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op.wait()
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print('Complete: Rank {0} - {1}'.format(dist.get_rank(), tensor))
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torch.cuda.synchronize()
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def check_reduce_scatter():
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tensor = torch.tensor([dist.get_rank() * SIZE + j for j in range(SIZE)])
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tensor = tensor.to(get_current_device())
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print('Before: Rank {0} - {1}'.format(dist.get_rank(), tensor))
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tensor, op = reduce_scatter(tensor, 0, ParallelMode.GLOBAL, async_op=True)
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print('After: Rank {0} - {1}'.format(dist.get_rank(), tensor))
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op.wait()
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print('Complete: Rank {0} - {1}'.format(dist.get_rank(), tensor))
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torch.cuda.synchronize()
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def check_all_reduce():
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tensor = torch.tensor([dist.get_rank() * SIZE + j for j in range(SIZE)])
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tensor = tensor.to(get_current_device())
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print('Before: Rank {0} - {1}'.format(dist.get_rank(), tensor))
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tensor, op = all_reduce(tensor, ParallelMode.GLOBAL, async_op=True)
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print('After: Rank {0} - {1}'.format(dist.get_rank(), tensor))
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op.wait()
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print('Complete: Rank {0} - {1}'.format(dist.get_rank(), tensor))
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torch.cuda.synchronize()
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def check_layer(rank, world_size, port):
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launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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assert dist.get_rank() == gpc.get_global_rank()
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print('Rank {} / {}'.format(dist.get_rank(), dist.get_world_size()))
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check_all_gather()
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check_reduce_scatter()
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check_all_reduce()
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gpc.destroy()
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torch.cuda.empty_cache()
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@pytest.mark.dist
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@rerun_if_address_is_in_use()
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def test_comm():
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spawn(check_layer, 4)
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if __name__ == '__main__':
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test_comm()
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