forked from mindspore-Ecosystem/mindspore
!9936 is_save_on_master doesn't work ,it is ok now
From: @shuzigood Reviewed-by: @guoqi1024,@oacjiewen,@linqingke Signed-off-by: @linqingke
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commit
0db846978e
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@ -75,7 +75,6 @@ python train.py \
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--is_distributed=0 \
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--lr=0.001 \
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--loss_scale=1024 \
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--sens=1024 \
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--weight_decay=0.016 \
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--T_max=320 \
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--max_epoch=320 \
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@ -175,8 +174,6 @@ optional arguments:
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Whether to use label smooth in CE. Default:0
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--label_smooth_factor LABEL_SMOOTH_FACTOR
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Smooth strength of original one-hot. Default: 0.1
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--sens SENS
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Static sens. Default: 1024
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--log_interval LOG_INTERVAL
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Logging interval steps. Default: 100
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--ckpt_path CKPT_PATH
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@ -211,7 +208,6 @@ python train.py \
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--is_distributed=0 \
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--lr=0.001 \
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--loss_scale=1024 \
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--sens=1024 \
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--weight_decay=0.016 \
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--T_max=320 \
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--max_epoch=320 \
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@ -124,20 +124,6 @@ def parse_args():
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args.data_root = os.path.join(args.data_dir, 'train2014')
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args.annFile = os.path.join(args.data_dir, 'annotations/instances_train2014.json')
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# select for master rank save ckpt or all rank save, compatiable for model parallel
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args.rank_save_ckpt_flag = 0
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if args.is_save_on_master:
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if args.rank == 0:
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args.rank_save_ckpt_flag = 1
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else:
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args.rank_save_ckpt_flag = 1
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# logger
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args.outputs_dir = os.path.join(args.ckpt_path,
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datetime.datetime.now().strftime('%Y-%m-%d_time_%H_%M_%S'))
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args.logger = get_logger(args.outputs_dir, args.rank)
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args.logger.save_args(args)
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return args
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@ -160,6 +146,20 @@ def train():
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init("nccl")
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args.rank = get_rank()
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args.group_size = get_group_size()
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# select for master rank save ckpt or all rank save, compatiable for model parallel
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args.rank_save_ckpt_flag = 0
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if args.is_save_on_master:
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if args.rank == 0:
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args.rank_save_ckpt_flag = 1
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else:
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args.rank_save_ckpt_flag = 1
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# logger
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args.outputs_dir = os.path.join(args.ckpt_path,
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datetime.datetime.now().strftime('%Y-%m-%d_time_%H_%M_%S'))
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args.logger = get_logger(args.outputs_dir, args.rank)
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args.logger.save_args(args)
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if args.need_profiler:
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from mindspore.profiler.profiling import Profiler
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profiler = Profiler(output_path=args.outputs_dir, is_detail=True, is_show_op_path=True)
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