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| _base_ = ['models'] | |
| # model settings | |
| model = dict( | |
| type='R2Tuning', | |
| arch='ViT-B/32', | |
| init=False, | |
| dims=256, | |
| strides=(1, 2, 4, 8), | |
| buffer_size=1024, | |
| max_num_moment=50, | |
| adapter_cfg=dict( | |
| type='R2Block', | |
| k=4, | |
| dropout=0.5, | |
| use_tef=True, | |
| pos_cfg=dict(type='PositionalEncoding', normalize=True, max_len=1024), | |
| tem_cfg=dict( | |
| type='TransformerDecoderLayer', | |
| heads=8, | |
| ratio=4, | |
| att_dropout=0.0, | |
| ffn_dropout=0.0, | |
| att_out_dropout=0.0, | |
| ffn_out_dropout=0.0, | |
| droppath=0.1, | |
| pre_norm=False, | |
| bias=True, | |
| norm_cfg=dict(type='LN'), | |
| act_cfg=dict(type='ReLU', inplace=True), | |
| order=('cross_att', 'self_att', 'ffn'), | |
| att_init_cfg=dict(type='xavier', distribution='uniform'), | |
| ffn_init_cfg=dict(type='kaiming'))), | |
| pyramid_cfg=dict(type='ConvPyramid'), | |
| pooling_cfg=dict(type='AdaPooling'), | |
| class_head_cfg=dict(type='ConvHead', kernal_size=3), | |
| coord_head_cfg=dict(type='ConvHead', kernal_size=3), | |
| loss_cfg=dict( | |
| type='BundleLoss', | |
| sample_radius=1.5, | |
| loss_cls=dict(type='FocalLoss', loss_weight=1.0), | |
| loss_reg=dict(type='L1Loss', loss_weight=0.2), | |
| loss_sal=dict(type='SampledNCELoss', loss_weight=0.1), | |
| loss_video_cal=dict(type='InfoNCELoss', loss_weight=0.1), | |
| loss_layer_cal=dict(type='InfoNCELoss', loss_weight=0.1))) | |