mirror of https://github.com/hpcaitech/ColossalAI
37 lines
1.0 KiB
Python
37 lines
1.0 KiB
Python
import torch
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from colossalai.utils.model.lazy_init_context import LazyInitContext
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from torchvision.models import resnet34
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import random
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import numpy as np
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MANUAL_SEED = 0
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random.seed(MANUAL_SEED)
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np.random.seed(MANUAL_SEED)
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torch.manual_seed(MANUAL_SEED)
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def test_lazy_init():
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cpu_rng_state = torch.get_rng_state()
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origin_model = resnet34(num_classes=10)
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origin_param_dict = dict(origin_model.named_parameters())
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torch.set_rng_state(cpu_rng_state)
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ctx = LazyInitContext()
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with ctx:
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model = resnet34(num_classes=10)
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for param in model.parameters():
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assert param.is_meta
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for buffer in model.buffers():
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assert buffer.is_meta
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ctx.lazy_init_parameters(model)
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for param in model.parameters():
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assert not param.is_meta
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for buffer in model.buffers():
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assert not buffer.is_meta
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param_dict = dict(model.named_parameters())
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for key in origin_param_dict.keys():
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assert origin_param_dict[key].data.equal(param_dict[key].data)
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if __name__ == '__main__':
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test_lazy_init()
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