mirror of https://github.com/hpcaitech/ColossalAI
39 lines
1.2 KiB
Python
39 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 colossalai
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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.zero.shard_utils.tensor_shard_strategy import TensorShardStrategy
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from colossalai.zero.init_ctx import ZeroInitContext
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from common import CONFIG, Net
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from colossalai.utils import free_port
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def run_dist(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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with ZeroInitContext(convert_fp16=True, convert_cuda=True, shard_strategy=TensorShardStrategy(), shard_param=True):
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# Note Net(checkpoint=True).cuda() moving to cuda is useless
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model = Net(checkpoint=True)
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for param in model.parameters():
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assert hasattr(param, 'ca_attr')
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assert param.ca_attr.data.dtype == torch.half
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assert param.ca_attr._data_sharded_tensor.is_sharded
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assert param.ca_attr.data.device.type == 'cuda'
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@pytest.mark.dist
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def test_zero_init_context():
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world_size = 2
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run_func = partial(run_dist, 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_zero_init_context()
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