87 lines
1.9 KiB
YAML
87 lines
1.9 KiB
YAML
model:
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encoders:
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lidar: null
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camera:
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backbone:
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type: SwinTransformer
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embed_dims: 96
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depths: [2, 2, 6, 2]
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num_heads: [3, 6, 12, 24]
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window_size: 7
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mlp_ratio: 4
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qkv_bias: true
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qk_scale: null
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drop_rate: 0.
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attn_drop_rate: 0.
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drop_path_rate: 0.3
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patch_norm: true
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out_indices: [1, 2, 3]
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with_cp: false
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convert_weights: true
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init_cfg:
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type: Pretrained
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checkpoint: https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_tiny_patch4_window7_224.pth
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neck:
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type: GeneralizedLSSFPN
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in_channels: [192, 384, 768]
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out_channels: 256
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start_level: 0
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num_outs: 3
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norm_cfg:
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type: BN2d
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requires_grad: true
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act_cfg:
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type: ReLU
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inplace: true
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upsample_cfg:
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mode: bilinear
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align_corners: false
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vtransform:
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type: LSSTransform
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in_channels: 256
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out_channels: 80
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image_size: ${image_size}
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feature_size: ${[image_size[0] // 8, image_size[1] // 8]}
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xbound: [-51.2, 51.2, 0.4]
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ybound: [-51.2, 51.2, 0.4]
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zbound: [-10.0, 10.0, 20.0]
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dbound: [1.0, 60.0, 0.5]
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downsample: 2
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fuser: null
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decoder:
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backbone:
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type: GeneralizedResNet
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in_channels: 80
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blocks:
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- [2, 160, 2]
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- [2, 320, 2]
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- [2, 640, 1]
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neck:
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type: LSSFPN
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in_indices: [-1, 0]
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in_channels: [640, 160]
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out_channels: 256
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scale_factor: 2
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optimizer:
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type: AdamW
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lr: 1.0e-4
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weight_decay: 0.01
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paramwise_cfg:
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custom_keys:
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absolute_pos_embed:
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decay_mult: 0
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relative_position_bias_table:
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decay_mult: 0
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optimizer_config:
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grad_clip:
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max_norm: 35
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norm_type: 2
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lr_config:
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policy: cyclic
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momentum_config:
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policy: cyclic
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