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_base_ = [ | |
'_base_master_resnet31.py', | |
'../_base_/datasets/toy_data.py', | |
'../_base_/default_runtime.py', | |
'../_base_/schedules/schedule_adam_base.py', | |
] | |
optim_wrapper = dict(optimizer=dict(lr=4e-4)) | |
train_cfg = dict(max_epochs=12) | |
# learning policy | |
param_scheduler = [ | |
dict(type='LinearLR', end=100, by_epoch=False), | |
dict(type='MultiStepLR', milestones=[11], end=12), | |
] | |
# dataset settings | |
train_list = [_base_.toy_rec_train] | |
test_list = [_base_.toy_rec_test] | |
train_dataset = dict( | |
type='ConcatDataset', datasets=train_list, pipeline=_base_.train_pipeline) | |
test_dataset = dict( | |
type='ConcatDataset', datasets=test_list, pipeline=_base_.test_pipeline) | |
train_dataloader = dict( | |
batch_size=2, | |
num_workers=1, | |
persistent_workers=True, | |
sampler=dict(type='DefaultSampler', shuffle=True), | |
dataset=train_dataset) | |
val_dataloader = dict( | |
batch_size=2, | |
num_workers=1, | |
persistent_workers=True, | |
drop_last=False, | |
sampler=dict(type='DefaultSampler', shuffle=False), | |
dataset=test_dataset) | |
test_dataloader = val_dataloader | |
val_evaluator = dict(dataset_prefixes=['Toy']) | |
test_evaluator = val_evaluator | |