slowonly_imagenet-pretrained-r50_8xb16-8x8x1-steplr-150e_kinetics400-rgb.py

_base_ = ['slowonly_r50_8xb16-8x8x1-256e_kinetics400-rgb.py']

model = dict(
    backbone=dict(
        pretrained='https://download.pytorch.org/models/resnet50-11ad3fa6.pth')
)

optim_wrapper = dict(
    optimizer=dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=1e-4),
    clip_grad=dict(max_norm=40, norm_type=2))

train_cfg = dict(
    type='EpochBasedTrainLoop', max_epochs=150, val_begin=1, val_interval=5)
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')

# learning policy
param_scheduler = [
    dict(type='LinearLR', start_factor=0.1, by_epoch=True, begin=0, end=10),
    dict(
        type='MultiStepLR',
        begin=10,
        end=150,
        by_epoch=True,
        milestones=[90, 130],
        gamma=0.1)
]