mirror of https://github.com/open-mmlab/mmocr.git
40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
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# training schedule for 1x
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_base_ = [
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'../../_base_/textrec_default_runtime.py',
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'../../_base_/recog_datasets/toy_data.py',
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'../../_base_/schedules/schedule_adadelta_5e.py',
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'_base_crnn_mini-vgg.py',
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]
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# dataset settings
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train_list = [_base_.toy_rec_train]
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test_list = [_base_.toy_rec_test]
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default_hooks = dict(logger=dict(type='LoggerHook', interval=50), )
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train_dataloader = dict(
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batch_size=64,
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num_workers=8,
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persistent_workers=True,
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sampler=dict(type='DefaultSampler', shuffle=True),
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dataset=dict(
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type='ConcatDataset',
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datasets=train_list,
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pipeline=_base_.train_pipeline))
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val_dataloader = dict(
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batch_size=1,
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num_workers=4,
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persistent_workers=True,
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drop_last=False,
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sampler=dict(type='DefaultSampler', shuffle=False),
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dataset=dict(
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type='ConcatDataset',
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datasets=test_list,
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pipeline=_base_.test_pipeline))
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test_dataloader = val_dataloader
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model = dict(decoder=dict(dictionary=dict(with_unknown=True)))
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val_evaluator = dict(dataset_prefixes=['Toy'])
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test_evaluator = val_evaluator
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