mirror of https://github.com/hpcaitech/ColossalAI
47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
#!/usr/bin/env python
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# -*- encoding: utf-8 -*-
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from functools import partial
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import pytest
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import torch
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import torch.multiprocessing as mp
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from colossalai.core import global_context as gpc
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from colossalai.logging import disable_existing_loggers
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from colossalai.initialize import launch
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from colossalai.utils import free_port
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from colossalai.testing import rerun_on_exception
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from checks_1d.check_layer_1d import *
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CONFIG = dict(parallel=dict(pipeline=dict(size=1), tensor=dict(size=4, mode='1d')),)
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def check_layer(rank, world_size, port):
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disable_existing_loggers()
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launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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check_linear_col()
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check_linear_row()
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check_embed()
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check_vocab_parallel_embed()
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check_classifier_no_given_weight()
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check_vocab_parallel_classifier_no_given_weight()
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check_classifier_given_embed_weight()
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check_vocab_parallel_classifier_given_embed_weight()
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check_vocab_parallel_loss()
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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_on_exception(exception_type=mp.ProcessRaisedException, pattern=".*Address already in use.*")
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def test_1d():
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world_size = 4
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run_func = partial(check_layer, world_size=world_size, 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_1d()
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