Fix `args.gradient_accumulation_steps` used before assigment.
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@ -404,6 +404,10 @@ def main():
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type=int,
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default=42,
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help="random seed for initialization")
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parser.add_argument('--gradient_accumulation_steps',
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type=int,
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default=1,
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help="Number of updates steps to accumualte before performing a backward/update pass.")
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args = parser.parse_args()
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processors = {
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@ -469,7 +473,7 @@ def main():
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model = BertForSequenceClassification(bert_config, len(label_list))
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if args.init_checkpoint is not None:
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model.load_state_dict(torch.load(args.init_checkpoint, map_location='cpu'))
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model.bert.load_state_dict(torch.load(args.init_checkpoint, map_location='cpu'))
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model.to(device)
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if args.local_rank != -1:
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@ -739,7 +739,11 @@ def main():
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type=int,
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default=42,
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help="random seed for initialization")
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parser.add_argument('--gradient_accumulation_steps',
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type=int,
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default=1,
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help="Number of updates steps to accumualte before performing a backward/update pass.")
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args = parser.parse_args()
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if args.local_rank == -1 or args.no_cuda:
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