clean up logger in examples for distributed case
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@@ -40,9 +40,6 @@ from pytorch_pretrained_bert.modeling import BertForSequenceClassification, Bert
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from pytorch_pretrained_bert.tokenization import BertTokenizer
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from pytorch_pretrained_bert.optimization import BertAdam, warmup_linear
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logging.basicConfig(format = '%(asctime)s - %(levelname)s - %(name)s - %(message)s',
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datefmt = '%m/%d/%Y %H:%M:%S',
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level = logging.INFO)
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logger = logging.getLogger(__name__)
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@@ -697,6 +694,11 @@ def main():
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n_gpu = 1
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# Initializes the distributed backend which will take care of sychronizing nodes/GPUs
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torch.distributed.init_process_group(backend='nccl')
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logging.basicConfig(format = '%(asctime)s - %(levelname)s - %(name)s - %(message)s',
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datefmt = '%m/%d/%Y %H:%M:%S',
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level = logging.INFO if args.local_rank in [-1, 0] else logging.WARN)
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logger.info("device: {} n_gpu: {}, distributed training: {}, 16-bits training: {}".format(
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device, n_gpu, bool(args.local_rank != -1), args.fp16))
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