trn_r50.py

# model settings
model = dict(
    type='Recognizer2D',
    backbone=dict(
        type='ResNet',
        pretrained='torchvision://resnet50',
        depth=50,
        norm_eval=False,
        partial_bn=True),
    cls_head=dict(
        type='TRNHead',
        num_classes=400,
        in_channels=2048,
        num_segments=8,
        spatial_type='avg',
        relation_type='TRNMultiScale',
        hidden_dim=256,
        dropout_ratio=0.8,
        init_std=0.001),
    # model training and testing settings
    train_cfg=None,
    test_cfg=dict(average_clips='prob'))