mirror of https://github.com/hpcaitech/ColossalAI
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
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from colossalai.utils.commons import BucketizedTensorCopy
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from colossalai.zero.sharded_param import ShardedParamV2
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from colossalai.utils import free_port
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import torch
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import colossalai
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def test_bucket_copy():
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# init dist env
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colossalai.launch(config={}, rank=0, world_size=1, host='localhost', port=free_port(), backend='nccl')
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copyer = BucketizedTensorCopy(20)
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shape_list = [(2, 3), (5), (8), (12)]
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src_param_list = []
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tgt_param_list = []
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for shape in shape_list:
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# on CPU
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src_param = torch.nn.Parameter(torch.randn(shape, dtype=torch.float, device=torch.device('cpu')))
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print(src_param)
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# on GPU
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tgt_param = ShardedParamV2(torch.nn.Parameter(torch.ones(shape, dtype=torch.half, device=torch.device('cuda'))))
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src_param_list.append(src_param)
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tgt_param_list.append(tgt_param)
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copyer.copy(src_param, tgt_param)
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copyer.flush()
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for src_param, tgt_param in zip(src_param_list, tgt_param_list):
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print(tgt_param.data.payload)
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diff = src_param.cpu().float() - tgt_param.data.payload.cpu().float()
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assert torch.allclose(src_param.cpu().float(), tgt_param.data.payload.cpu().float(), rtol=1e-03,
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atol=1e-03), f"diff {diff}"
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if __name__ == '__main__':
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test_bucket_copy()
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