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@ -976,7 +976,7 @@ def run(rank, world_size, args):
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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_model2[n]
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try: p.data = pre_trained_model1[n]
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except: print(f'pre-trained model has no parameter named {n}.')
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else:
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layer_name_splited = n.split('.')
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@ -984,13 +984,13 @@ def run(rank, world_size, args):
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layer_name_splited[0] = 'pt_encoder'
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layer_name_splited[3] = str(int(layer_name_splited[3])//2)
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old_name = '.'.join(layer_name_splited)
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try: p.data = pre_trained_model[old_name]
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try: p.data = pre_trained_model2[old_name]
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except: print(f'pre-trained model has no parameter named {n}.')
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else:
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layer_name_splited[0] = 'inter_encoder'
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layer_name_splited[3] = str(int(layer_name_splited[3])//2+1)
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old_name = '.'.join(layer_name_splited)
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try: p.data = pre_trained_model[old_name]
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try: p.data = pre_trained_model2[old_name]
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except: print(f'pre-trained model has no parameter named {n}.')
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