imagenet21k_bs128.py

# dataset settings
dataset_type = 'ImageNet21k'
data_preprocessor = dict(
    num_classes=21842,
    # RGB format normalization parameters
    mean=[123.675, 116.28, 103.53],
    std=[58.395, 57.12, 57.375],
    # convert image from BGR to RGB
    to_rgb=True,
)

train_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(type='RandomResizedCrop', scale=224),
    dict(type='RandomFlip', prob=0.5, direction='horizontal'),
    dict(type='PackInputs'),
]

train_dataloader = dict(
    batch_size=128,
    num_workers=5,
    dataset=dict(
        type=dataset_type,
        data_root='data/imagenet21k',
        split='train',
        pipeline=train_pipeline),
    sampler=dict(type='DefaultSampler', shuffle=True),
)