117 lines
2.0 KiB
YAML
117 lines
2.0 KiB
YAML
checkpoint_config:
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interval: 1
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data:
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samples_per_gpu: 1
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workers_per_gpu: 0
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log_config:
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hooks:
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- type: TextLoggerHook
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interval: 50
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lr_config:
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min_lr_ratio: 0.001
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policy: CosineAnnealing
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warmup: linear
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warmup_iters: 500
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warmup_ratio: 0.33333333
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model:
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encoders:
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lidar:
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backbone:
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encoder_channels:
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- - 16
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- 16
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- 32
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- - 32
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- 32
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- 64
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- - 64
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- 64
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- 128
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- - 128
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- 128
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encoder_paddings:
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- - 0
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- 0
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- 1
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- - 0
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- 0
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- 1
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- - 0
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- 0
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- - 1
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- 1
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- 0
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- - 0
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- 0
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in_channels: 5
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order:
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- conv
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- norm
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- act
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output_channels: 128
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sparse_shape:
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- 1440
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- 1440
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- 41
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type: SparseEncoder
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voxelize:
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max_num_points: 10
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max_voxels:
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- 120000
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- 160000
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point_cloud_range:
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- -54.0
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- -54.0
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- -5.0
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- 54.0
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- 54.0
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- 3.0
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voxel_size:
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- 0.075
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- 0.075
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- 0.2
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fuser:
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in_channels:
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- 256
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out_channels: 256
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type: ConvFuser
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heads:
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map:
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classes:
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- drivable_area
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- ped_crossing
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- walkway
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- stop_line
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- carpark_area
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- divider
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deep_supervision: true
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dice_weight: 0.5
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focal_alpha: 0.25
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focal_gamma: 2.0
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grid_transform:
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input_scope:
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- - -54.0
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- 54.0
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- 0.75
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- - -54.0
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- 54.0
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- 0.75
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output_scope:
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- - -50
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- 50
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- 0.167
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- - -50
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- 50
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- 0.167
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in_channels: 256
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loss: focal
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type: EnhancedBEVSegmentationHead
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use_dice_loss: true
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type: BEVFusion
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optimizer:
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lr: 0.0001
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type: AdamW
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runner:
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max_epochs: 1
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type: EpochBasedRunner
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