OpenPCDet/tools/cfgs/waymo_models/mppnet_e2e_memorybank_inference.yaml

CLASS_NAMES: ['Vehicle', 'Pedestrian', 'Cyclist']

DATA_CONFIG: 

    _BASE_CONFIG_: cfgs/dataset_configs/waymo_dataset_multiframe.yaml
    PROCESSED_DATA_TAG: 'waymo_processed_data_v0_5_0'

    SEQUENCE_CONFIG:
        ENABLED: True
        SAMPLE_OFFSET: [-3, 0] #16frame using [-15,0]

    POINT_FEATURE_ENCODING: {
    encoding_type: absolute_coordinates_encoding,
    used_feature_list: ['x', 'y', 'z', 'intensity', 'elongation','time'],
    src_feature_list: ['x', 'y', 'z', 'intensity', 'elongation','time'],
    }


MODEL:
    NAME: MPPNetE2E

    VFE:
        NAME: DynMeanVFE

    BACKBONE_3D:
        NAME: VoxelResBackBone8x

    MAP_TO_BEV:
        NAME: HeightCompression
        NUM_BEV_FEATURES: 256

    BACKBONE_2D:
        NAME: BaseBEVBackbone 
        NUM_FRAME: 2
        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: [
            ['Vehicle', 'Pedestrian', 'Cyclist']
        ]

        SHARED_CONV_CHANNEL: 64
        USE_BIAS_BEFORE_NORM: True
        NUM_HM_CONV: 2
        SEPARATE_HEAD_CFG:
            HEAD_ORDER: ['center', 'center_z', 'dim', 'rot','vel']
            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},
                'vel': {'out_channels': 2, 'num_conv': 2},

            }

        TARGET_ASSIGNER_CONFIG:
            FEATURE_MAP_STRIDE: 8
            NUM_MAX_OBJS: 500
            GAUSSIAN_OVERLAP: 0.1
            MIN_RADIUS: 2

        LOSS_CONFIG:
            LOSS_WEIGHTS: {
                'cls_weight': 1.0,
                'loc_weight': 2.0,
                'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2]
            }

        POST_PROCESSING:
            SCORE_THRESH: 0.1
            POST_CENTER_LIMIT_RANGE: [-75.2, -75.2, -2, 75.2, 75.2, 4]
            MAX_OBJ_PER_SAMPLE: 500
            NMS_CONFIG:
                NMS_TYPE: nms_gpu
                NMS_THRESH: 0.7
                NMS_PRE_MAXSIZE: 4096
                NMS_POST_MAXSIZE: 500

    ROI_HEAD:
        NAME: MPPNetHeadE2E
        TRANS_INPUT: 256
        CLASS_AGNOSTIC: True
        USE_BOX_ENCODING:
            ENABLED: True 
            NORM_T0: True
            ALL_YAW_T0: True
        AVG_STAGE1_SCORE: True
        USE_TRAJ_EMPTY_MASK: True
        USE_AUX_LOSS: True
        IOU_WEIGHT: [0.5,0.4]

        ROI_GRID_POOL: #if using 16frame, change to the corresponding setting 
            GRID_SIZE: 4
            MLPS: [[128,128], [128,128]]
            POOL_RADIUS: [0.8, 1.6]
            NSAMPLE: [16, 16]
            POOL_METHOD: max_pool
            
        Transformer:
            num_lidar_points: 128
            num_proxy_points: 64
            pos_hidden_dim: 64
            enc_layers: 3
            dim_feedforward: 512
            hidden_dim: 256
            dropout: 0.1
            nheads: 4
            pre_norm: False
            num_frames: 4 #16frame using 16
            num_groups: 4
            sequence_stride: 1 #16frame using 4
            use_grid_pos:
                enabled: True
                init_type: index
            use_mlp_mixer:
                enabled: True
                hidden_dim: 16

        TARGET_CONFIG:
            BOX_CODER: ResidualCoder
            ROI_PER_IMAGE: 96
            FG_RATIO: 0.5
            REG_AUG_METHOD: single
            ROI_FG_AUG_TIMES: 10
            RATIO: 0.2
            USE_ROI_AUG: True
            USE_TRAJ_AUG:
                ENABLED: True
                THRESHOD: 0.8
            SAMPLE_ROI_BY_EACH_CLASS: True
            CLS_SCORE_TYPE: roi_iou

            CLS_FG_THRESH: 0.75
            CLS_BG_THRESH: 0.25
            CLS_BG_THRESH_LO: 0.1
            HARD_BG_RATIO: 0.8

            REG_FG_THRESH: 0.55

        LOSS_CONFIG:
            CLS_LOSS: BinaryCrossEntropy
            REG_LOSS: smooth-l1
            CORNER_LOSS_REGULARIZATION: True
            LOSS_WEIGHTS: {
                'rcnn_cls_weight': 1.0,
                'rcnn_reg_weight': 1.0,
                'rcnn_corner_weight': 2.0,
                'traj_reg_weight': [2.0, 2.0, 2.0],
                'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
            }

    POST_PROCESSING:
        RECALL_THRESH_LIST: [0.3, 0.5, 0.7]
        SCORE_THRESH: 0.1
        OUTPUT_RAW_SCORE: False
        SAVE_BBOX: False
        EVAL_METRIC: waymo
        NOT_APPLY_NMS_FOR_VEL: True

        NMS_CONFIG:
            MULTI_CLASSES_NMS: False
            NMS_TYPE: nms_gpu
            NMS_THRESH: 0.7
            NMS_PRE_MAXSIZE: 4096
            NMS_POST_MAXSIZE: 500


OPTIMIZATION:
    BATCH_SIZE_PER_GPU: 2
    NUM_EPOCHS: 6

    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: 10