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# training schedule for 1x
_base_ = [
'../_base_/default_runtime.py',
'../_base_/datasets/toy_data.py',
'../_base_/schedules/schedule_adadelta_5e.py',
'_base_crnn_mini-vgg.py',
]
# dataset settings
train_list = [_base_.toy_rec_train]
test_list = [_base_.toy_rec_test]
default_hooks = dict(logger=dict(type='LoggerHook', interval=50), )
train_dataloader = dict(
batch_size=64,
num_workers=8,
persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=True),
dataset=dict(
type='ConcatDataset',
datasets=train_list,
pipeline=_base_.train_pipeline))
val_dataloader = dict(
batch_size=1,
num_workers=4,
persistent_workers=True,
drop_last=False,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=dict(
type='ConcatDataset',
datasets=test_list,
pipeline=_base_.test_pipeline))
test_dataloader = val_dataloader
_base_.model.decoder.dictionary.update(
dict(with_unknown=True, unknown_token=None))
_base_.train_cfg.update(dict(max_epochs=200, val_interval=10))
val_evaluator = dict(dataset_prefixes=['Toy'])
test_evaluator = val_evaluator
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