fix data replication for multi-cards sampling
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@ -51,7 +51,7 @@ signal.signal(signal.SIGINT, term_mp)
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signal.signal(signal.SIGTERM, term_mp)
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def build_dataloader(config, mode, device, logger):
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def build_dataloader(config, mode, device, logger, seed=None):
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config = copy.deepcopy(config)
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support_dict = ['SimpleDataSet', 'LMDBDateSet']
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@ -61,7 +61,7 @@ def build_dataloader(config, mode, device, logger):
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assert mode in ['Train', 'Eval', 'Test'
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], "Mode should be Train, Eval or Test."
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dataset = eval(module_name)(config, mode, logger)
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dataset = eval(module_name)(config, mode, logger, seed)
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loader_config = config[mode]['loader']
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batch_size = loader_config['batch_size_per_card']
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drop_last = loader_config['drop_last']
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@ -21,7 +21,7 @@ from .imaug import transform, create_operators
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class LMDBDateSet(Dataset):
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def __init__(self, config, mode, logger):
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def __init__(self, config, mode, logger, seed=None):
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super(LMDBDateSet, self).__init__()
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global_config = config['Global']
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@ -20,7 +20,7 @@ from .imaug import transform, create_operators
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class SimpleDataSet(Dataset):
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def __init__(self, config, mode, logger):
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def __init__(self, config, mode, logger, seed=None):
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super(SimpleDataSet, self).__init__()
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self.logger = logger
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@ -41,6 +41,7 @@ class SimpleDataSet(Dataset):
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self.data_dir = dataset_config['data_dir']
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self.do_shuffle = loader_config['shuffle']
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self.seed = seed
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logger.info("Initialize indexs of datasets:%s" % label_file_list)
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self.data_lines = self.get_image_info_list(label_file_list, ratio_list)
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self.data_idx_order_list = list(range(len(self.data_lines)))
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@ -55,6 +56,7 @@ class SimpleDataSet(Dataset):
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for idx, file in enumerate(file_list):
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with open(file, "rb") as f:
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lines = f.readlines()
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random.seed(self.seed)
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lines = random.sample(lines,
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round(len(lines) * ratio_list[idx]))
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data_lines.extend(lines)
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@ -62,6 +64,7 @@ class SimpleDataSet(Dataset):
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def shuffle_data_random(self):
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if self.do_shuffle:
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random.seed(self.seed)
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random.shuffle(self.data_lines)
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return
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@ -182,8 +182,8 @@ def train(config,
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start_epoch = 1
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for epoch in range(start_epoch, epoch_num + 1):
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if epoch > 0:
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train_dataloader = build_dataloader(config, 'Train', device, logger)
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train_dataloader = build_dataloader(
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config, 'Train', device, logger, seed=epoch)
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train_batch_cost = 0.0
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train_reader_cost = 0.0
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batch_sum = 0
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