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# dataset settings
dataset_type = 'CIFAR10'
data_preprocessor = dict(
num_classes=10,
# RGB format normalization parameters
mean=[125.307, 122.961, 113.8575],
std=[51.5865, 50.847, 51.255],
# loaded images are already RGB format
to_rgb=False)
train_pipeline = [
dict(type='RandomCrop', crop_size=32, padding=4),
dict(type='RandomFlip', prob=0.5, direction='horizontal'),
dict(type='PackClsInputs'),
]
test_pipeline = [
dict(type='PackClsInputs'),
]
train_dataloader = dict(
batch_size=16,
num_workers=2,
dataset=dict(
type=dataset_type,
data_prefix='data/cifar10',
test_mode=False,
pipeline=train_pipeline),
sampler=dict(type='DefaultSampler', shuffle=True),
)
val_dataloader = dict(
batch_size=16,
num_workers=2,
dataset=dict(
type=dataset_type,
data_prefix='data/cifar10/',
test_mode=True,
pipeline=test_pipeline),
sampler=dict(type='DefaultSampler', shuffle=False),
)
val_evaluator = dict(type='Accuracy', topk=(1, ))
test_dataloader = val_dataloader
test_evaluator = val_evaluator
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