dataset_type = 'GrowScaleImgDataset'

train_pipeline = [
    dict(
        type='LoadImageFromFile',
        key='real_img',
        io_backend='disk',
    ),
    dict(type='Flip', keys=['real_img'], direction='horizontal'),
    dict(
        type='Normalize',
        keys=['real_img'],
        mean=[127.5, 127.5, 127.5],
        std=[127.5, 127.5, 127.5],
        to_rgb=False),
    dict(type='ImageToTensor', keys=['real_img']),
    dict(type='Collect', keys=['real_img'], meta_keys=['real_img_path'])
]

data = dict(
    samples_per_gpu=64,
    workers_per_gpu=4,
    train=dict(
        type='GrowScaleImgDataset',
        imgs_roots=dict({
            '1024': './data/ffhq/images',
            '256': './data/ffhq/ffhq_imgs/ffhq_256',
            '64': './data/ffhq/ffhq_imgs/ffhq_64'
        }),
        pipeline=train_pipeline,
        gpu_samples_base=4,
        gpu_samples_per_scale={
            '4': 64,
            '8': 32,
            '16': 16,
            '32': 8,
            '64': 4,
            '128': 4,
            '256': 4,
            '512': 4,
            '1024': 4
        },
        len_per_stage=300000))

a4a96bb805bccd5a1c971d7a788524506df5b000
<mask token>

dataset_type = 'GrowScaleImgDataset'
train_pipeline = [dict(type='LoadImageFromFile', key='real_img', io_backend
    ='disk'), dict(type='Flip', keys=['real_img'], direction='horizontal'),
    dict(type='Normalize', keys=['real_img'], mean=[127.5, 127.5, 127.5],
    std=[127.5, 127.5, 127.5], to_rgb=False), dict(type='ImageToTensor',
    keys=['real_img']), dict(type='Collect', keys=['real_img'], meta_keys=[
    'real_img_path'])]
data = dict(samples_per_gpu=64, workers_per_gpu=4, train=dict(type=
    'GrowScaleImgDataset', imgs_roots=dict({'1024': './data/ffhq/images',
    '256': './data/ffhq/ffhq_imgs/ffhq_256', '64':
    './data/ffhq/ffhq_imgs/ffhq_64'}), pipeline=train_pipeline,
    gpu_samples_base=4, gpu_samples_per_scale={'4': 64, '8': 32, '16': 16,
    '32': 8, '64': 4, '128': 4, '256': 4, '512': 4, '1024': 4},
    len_per_stage=300000))

dataset_type = 'GrowScaleImgDataset'

train_pipeline = [
    dict(
        type='LoadImageFromFile',
        key='real_img',
        io_backend='disk',
    ),
    dict(type='Flip', keys=['real_img'], direction='horizontal'),
    dict(
        type='Normalize',
        keys=['real_img'],
        mean=[127.5, 127.5, 127.5],
        std=[127.5, 127.5, 127.5],
        to_rgb=False),
    dict(type='ImageToTensor', keys=['real_img']),
    dict(type='Collect', keys=['real_img'], meta_keys=['real_img_path'])
]

data = dict(
    samples_per_gpu=64,
    workers_per_gpu=4,
    train=dict(
        type='GrowScaleImgDataset',
        imgs_roots=dict({
            '1024': './data/ffhq/images',
            '256': './data/ffhq/ffhq_imgs/ffhq_256',
            '64': './data/ffhq/ffhq_imgs/ffhq_64'
        }),
        pipeline=train_pipeline,
        gpu_samples_base=4,
        gpu_samples_per_scale={
            '4': 64,
            '8': 32,
            '16': 16,
            '32': 8,
            '64': 4,
            '128': 4,
            '256': 4,
            '512': 4,
            '1024': 4
        },
        len_per_stage=300000))
