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https://github.com/hpcaitech/ColossalAI.git
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40 lines
1.2 KiB
Python
40 lines
1.2 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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import colossalai
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from colossalai.zero.sharded_model.param_manager import Zero3ParameterManager
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from colossalai.core import global_context as gpc
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from colossalai.context.parallel_mode import ParallelMode
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from colossalai.utils import free_port
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from common import CONFIG
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def run_shard_shape_check(rank, world_size, port):
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colossalai.launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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model = torch.nn.Linear(2, 4 * world_size)
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gpc.init_parallel_groups()
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Zero3ParameterManager(module=model,
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process_group=gpc.get_group(ParallelMode.DATA),
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offload_config=CONFIG.get('offload_param_config'))
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assert (model.weight.numel() == 4 * 2)
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assert (model.bias.numel() == 4)
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@pytest.mark.dist
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@pytest.mark.parametrize("world_size", [1, 2, 4])
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def test_run_shard_shape(world_size):
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run_func = partial(run_shard_shape_check, 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_run_shard_shape(2)
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