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@ -974,6 +974,10 @@ def run(rank, world_size, args):
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pre_trained2 = torch.load(path2)
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pre_trained_model2 = pre_trained2["model"]
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for n, p in pre_trained_model2.items():
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if rank == 0:
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print(n)
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for n, p in model.named_parameters():
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if 'layer' not in n:
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try: p.data = pre_trained_model1[n]
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