mirror of https://github.com/hpcaitech/ColossalAI
43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import pytest
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from colossalai.utils.cuda import get_current_device
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from colossalai.utils.memory_utils.utils import colo_model_data_tensor_move, colo_model_data_tensor_move_inline
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from colossalai.utils import free_port
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from colossalai.zero.sharded_param import ShardedTensor
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import colossalai
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import torch
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from functools import partial
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import torch.multiprocessing as mp
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def _run_colo_model_data_tensor_move_inline():
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for t in [torch.randn(2, 3), ShardedTensor(torch.randn(2, 3))]:
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colo_model_data_tensor_move_inline(t, torch.device(f"cuda:{get_current_device()}"))
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assert t.device == torch.device(f"cuda:{get_current_device()}")
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def _run_colo_model_data_tensor_move():
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for t in [(torch.ones(2, 3), torch.zeros(2, 3).cuda(get_current_device())),
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(ShardedTensor(torch.ones(2, 3)), ShardedTensor(torch.zeros(2, 3).cuda(get_current_device())))]:
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cpu_t, cuda_t = t
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colo_model_data_tensor_move(cpu_t, cuda_t)
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def run_dist(rank, world_size, port):
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colossalai.launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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_run_colo_model_data_tensor_move_inline()
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_run_colo_model_data_tensor_move()
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@pytest.mark.dist
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@pytest.mark.parametrize("world_size", [1, 4])
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def test_tensor_move(world_size):
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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_tensor_move(4)
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