centerpoint_with_lion_with_128dim_retnet.yaml

CLASS_NAMES: ['Car', 'Bus', 'Truck', 'Pedestrian', 'Cyclist']

DATA_CONFIG:
    _BASE_CONFIG_: cfgs/dataset_configs/once_dataset.yaml
    POINT_CLOUD_RANGE: [-75.2, -75.2, -5.0, 75.2, 75.2, 3.0]

    DATA_PROCESSOR:
        - NAME: mask_points_and_boxes_outside_range
          REMOVE_OUTSIDE_BOXES: True

        - NAME: shuffle_points
          SHUFFLE_ENABLED: {
              'train': True,
              'test': False
          }

        - NAME: transform_points_to_voxels
          VOXEL_SIZE: [ 0.4, 0.4, 0.25 ]
          MAX_POINTS_PER_VOXEL: 5
          MAX_NUMBER_OF_VOXELS: {
              'train': 60000,
              'test': 60000
          }

MODEL:
    NAME: CenterPoint

    VFE:
        NAME: DynamicVoxelVFE
        WITH_DISTANCE: False
        USE_ABSLOTE_XYZ: True
        USE_NORM: True
        NUM_FILTERS: [128, 128]

    BACKBONE_3D:
        NAME: LION3DBackboneOneStride
        FEATURE_DIM: 128
        LAYER_DIM: [128, 128, 128, 128]
        NUM_LAYERS: 4
        DEPTHS: [2, 2, 2, 2]
        LAYER_DOWN_SCALES: [[[2, 2, 2], [2, 2, 2]], [[2, 2, 2], [2, 2, 2]], [[2, 2, 2], [2, 2, 2]], [[2, 2, 2], [2, 2, 2]]]
        WINDOW_SHAPE: [ [ 13, 13, 32 ], [ 13, 13, 16 ], [ 13, 13, 8 ], [ 13, 13, 4 ] ] #[[13, 13, 16], [13, 13, 8], [13, 13, 8], [13, 13, 4]]
        GROUP_SIZE: [4096, 2048, 1024, 512] #[2048, 1024, 1024, 512] #[1024, 1024, 1024, 512]
        DIRECTION: ['x', 'y']
        DIFF_SCALE: 0.2 #0.2
        DIFFUSION:  True #False #True
        SHIFT: True
        OPERATOR:
            NAME: 'RetNet' # TODO add cpe
            CFG:
                mode: 'chunk' # only support chunk
                n_head: 4 #2
                expand_k: 1
                expand_v: 2
                hidden_rate: 4
                used_MLP: True
                with_cp: True
                drop_path: 0.2

    MAP_TO_BEV:
        NAME: HeightCompression
        NUM_BEV_FEATURES: 256


    BACKBONE_2D:
        NAME: BaseBEVBackbone

        LAYER_NUMS: [5, 5]
        LAYER_STRIDES: [1, 2]
        NUM_FILTERS: [128, 256]
        UPSAMPLE_STRIDES: [1, 2]
        NUM_UPSAMPLE_FILTERS: [256, 256]

    DENSE_HEAD:
        NAME: CenterHead
        CLASS_AGNOSTIC: False

        CLASS_NAMES_EACH_HEAD: [
            ['Car', 'Bus', 'Truck', 'Pedestrian', 'Cyclist']
        ]

        SHARED_CONV_CHANNEL: 64
        USE_BIAS_BEFORE_NORM: True  # TODO
        NUM_HM_CONV: 2  # TODO
        SEPARATE_HEAD_CFG:
            HEAD_ORDER: ['center', 'center_z', 'dim', 'rot']
            HEAD_DICT: {
                'center': {'out_channels': 2, 'num_conv': 2},
                'center_z': {'out_channels': 1, 'num_conv': 2},
                'dim': {'out_channels': 3, 'num_conv': 2},
                'rot': {'out_channels': 2, 'num_conv': 2},
            }

        TARGET_ASSIGNER_CONFIG:
            FEATURE_MAP_STRIDE: 1 #8
            NUM_MAX_OBJS: 500
            GAUSSIAN_OVERLAP: 0.1
            MIN_RADIUS: 2
            DENSE_REG: 1

        LOSS_CONFIG:
            LOSS_WEIGHTS: {
                'cls_weight': 1.0,
                'loc_weight': 1.0,
                'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
            }

        POST_PROCESSING:
            SCORE_THRESH: 0.1
            POST_CENTER_LIMIT_RANGE: [-75.2, -75.2, -5.0, 75.2, 75.2, 3.0]
            MAX_OBJ_PER_SAMPLE: 500
            NMS_CONFIG:
                MULTI_CLASSES_NMS: False
                NMS_TYPE: nms_gpu
                NMS_THRESH: 0.01
                NMS_PRE_MAXSIZE: 4096
                NMS_POST_MAXSIZE: 500
            

    POST_PROCESSING:
      RECALL_THRESH_LIST: [0.3, 0.5, 0.7]

      OUTPUT_RAW_SCORE: False

      EVAL_METRIC: once

OPTIMIZATION:
    BATCH_SIZE_PER_GPU: 4
    NUM_EPOCHS: 80

    OPTIMIZER: adam_onecycle
    LR: 0.003
    WEIGHT_DECAY: 0.01
    MOMENTUM: 0.9

    MOMS: [0.95, 0.85]
    PCT_START: 0.4
    DIV_FACTOR: 10
    DECAY_STEP_LIST: [35, 45]
    LR_DECAY: 0.1
    LR_CLIP: 0.0000001

    LR_WARMUP: False
    WARMUP_EPOCH: 1

    GRAD_NORM_CLIP: 35