mirror of https://github.com/hpcaitech/ColossalAI
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
from functools import partial
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import pytest
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import torch.multiprocessing as mp
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from colossalai.device import AlphaBetaProfiler
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from colossalai.initialize import launch
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from colossalai.logging import disable_existing_loggers
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from colossalai.testing import parameterize, rerun_if_address_is_in_use
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from colossalai.utils import free_port
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def check_extract_alpha_beta(rank, physical_devices, world_size, port):
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disable_existing_loggers()
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launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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profiler = AlphaBetaProfiler(physical_devices)
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mesh_alpha, mesh_beta = profiler.extract_alpha_beta_for_device_mesh()
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for alpha in mesh_alpha:
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assert alpha > 0 and alpha < 1e-3
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for beta in mesh_beta:
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assert beta > 0 and beta < 1e-10
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@pytest.mark.skip(reason="Skip because assertion may fail for CI devices")
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@pytest.mark.dist
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@parameterize('physical_devices', [[0, 1, 2, 3], [0, 3]])
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@rerun_if_address_is_in_use()
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def test_profile_alpha_beta(physical_devices):
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world_size = 4
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run_func = partial(check_extract_alpha_beta,
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physical_devices=physical_devices,
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world_size=world_size,
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port=free_port())
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mp.spawn(run_func, nprocs=world_size)
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if __name__ == '__main__':
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test_profile_alpha_beta()
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