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mtr+20_percent_data.yaml
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mtr+20_percent_data.yaml
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DATA_CONFIG:
DATASET: WaymoDataset
OBJECT_TYPE: &object_type ['TYPE_VEHICLE', 'TYPE_PEDESTRIAN', 'TYPE_CYCLIST']
DATA_ROOT: 'data/waymo'
SPLIT_DIR: {
'train': 'processed_scenarios_training',
'test': 'processed_scenarios_validation'
}
INFO_FILE: {
'train': 'processed_scenarios_training_infos.pkl',
'test': 'processed_scenarios_val_infos.pkl'
}
SAMPLE_INTERVAL: {
'train': 5,
'test': 1
}
INFO_FILTER_DICT:
filter_info_by_object_type: *object_type
# for map feature encoding
POINT_SAMPLED_INTERVAL: 1
NUM_POINTS_EACH_POLYLINE: 20
VECTOR_BREAK_DIST_THRESH: 1.0
NUM_OF_SRC_POLYLINES: 768
CENTER_OFFSET_OF_MAP: ¢er_offset [30.0, 0]
MODEL:
CONTEXT_ENCODER:
NAME: MTREncoder
NUM_OF_ATTN_NEIGHBORS: 16
NUM_INPUT_ATTR_AGENT: 29
NUM_INPUT_ATTR_MAP: 9
NUM_CHANNEL_IN_MLP_AGENT: 256
NUM_CHANNEL_IN_MLP_MAP: 64
NUM_LAYER_IN_MLP_AGENT: 3
NUM_LAYER_IN_MLP_MAP: 5
NUM_LAYER_IN_PRE_MLP_MAP: 3
D_MODEL: 256
NUM_ATTN_LAYERS: 6
NUM_ATTN_HEAD: 8
DROPOUT_OF_ATTN: 0.1
USE_LOCAL_ATTN: True
MOTION_DECODER:
NAME: MTRDecoder
OBJECT_TYPE: *object_type
CENTER_OFFSET_OF_MAP: *center_offset
NUM_FUTURE_FRAMES: 80
NUM_MOTION_MODES: 6
INTENTION_POINTS_FILE: data/waymo/cluster_64_center_dict.pkl
D_MODEL: 512
NUM_DECODER_LAYERS: 6
NUM_ATTN_HEAD: 8
MAP_D_MODEL: 256
DROPOUT_OF_ATTN: 0.1
NUM_BASE_MAP_POLYLINES: 256
NUM_WAYPOINT_MAP_POLYLINES: 128
LOSS_WEIGHTS: {
'cls': 1.0,
'reg': 1.0,
'vel': 0.5
}
NMS_DIST_THRESH: 2.5
OPTIMIZATION:
BATCH_SIZE_PER_GPU: 10
NUM_EPOCHS: 30
OPTIMIZER: AdamW
LR: 0.0001
WEIGHT_DECAY: 0.01
SCHEDULER: lambdaLR
DECAY_STEP_LIST: [22, 24, 26, 28]
LR_DECAY: 0.5
LR_CLIP: 0.000001
GRAD_NORM_CLIP: 1000.0