/home/hxj/anaconda3/envs/vlnce/bin/python /home/hxj/VLN-CE/VLN-CE/run.py --exp-config vlnce_baselines/config/r2r_baselines/nonlearning.yaml --run-type eval
/home/hxj/anaconda3/envs/vlnce/lib/python3.6/site-packages/gym/core.py:27: UserWarning: WARN: Gym minimally supports python 3.6 as the python foundation not longer supports the version, please update your version to 3.7+
"Gym minimally supports python 3.6 as the python foundation not longer supports the version, please update your version to 3.7+"
Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.
Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.
Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.
See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.
2025-08-23 22:32:05,138 config: BASE_TASK_CONFIG_PATH: habitat_extensions/config/vlnce_task.yaml
CHECKPOINT_FOLDER: data/checkpoints
CHECKPOINT_INTERVAL: -1
CMD_TRAILING_OPTS: []
ENV_NAME: VLNCEDaggerEnv
EVAL:
EPISODE_COUNT: 10
EVAL_NONLEARNING: True
LANGUAGES: ['en-US', 'en-IN']
NONLEARNING:
AGENT: RandomAgent
SAMPLE: False
SAVE_RESULTS: True
SPLIT: val_unseen
USE_CKPT_CONFIG: True
EVAL_CKPT_PATH_DIR: data/checkpoints
FORCE_BLIND_POLICY: False
IL:
DAGGER:
drop_existing_lmdb_features: True
expert_policy_sensor: SHORTEST_PATH_SENSOR
expert_policy_sensor_uuid: shortest_path_sensor
iterations: 10
lmdb_commit_frequency: 500
lmdb_features_dir: data/trajectories_dirs/debug/trajectories.lmdb
lmdb_fp16: False
lmdb_map_size: 1200000000000.0
p: 0.75
preload_lmdb_features: False
start_iteration: 0
update_size: 5000
RECOLLECT_TRAINER:
effective_batch_size: -1
gt_file: data/datasets/RxR_VLNCE_v0/{split}/{split}_{role}_gt.json.gz
max_traj_len: -1
preload_size: 30
preload_trajectories_file: False
trajectories_file: data/trajectories_dirs/debug/trajectories.json.gz
batch_size: 5
ckpt_to_load: data/checkpoints/ckpt.0.pth
epochs: 4
inflection_weight_coef: 3.2
is_requeue: False
load_from_ckpt: False
lr: 0.00025
use_iw: True
INFERENCE:
CKPT_PATH: data/checkpoints/CMA_PM_DA_Aug.pth
FORMAT: rxr
INFERENCE_NONLEARNING: True
LANGUAGES: ['en-US', 'en-IN']
NONLEARNING:
AGENT: RandomAgent
PREDICTIONS_FILE: predictions.json
SAMPLE: False
SPLIT: val_unseen
USE_CKPT_CONFIG: True
LOG_FILE: train.log
LOG_INTERVAL: 10
MODEL:
DEPTH_ENCODER:
backbone: resnet50
cnn_type: VlnResnetDepthEncoder
ddppo_checkpoint: data/ddppo-models/gibson-2plus-resnet50.pth
output_size: 128
trainable: False
INSTRUCTION_ENCODER:
bidirectional: False
dataset_vocab: data/datasets/R2R_VLNCE_v1-3_preprocessed/train/train.json.gz
embedding_file: data/datasets/R2R_VLNCE_v1-3_preprocessed/embeddings.json.gz
embedding_size: 50
final_state_only: True
fine_tune_embeddings: False
hidden_size: 128
rnn_type: LSTM
sensor_uuid: instruction
use_pretrained_embeddings: True
vocab_size: 2504
PROGRESS_MONITOR:
alpha: 1.0
use: False
RGB_ENCODER:
cnn_type: TorchVisionResNet50
output_size: 256
trainable: False
SEQ2SEQ:
use_prev_action: False
STATE_ENCODER:
hidden_size: 512
rnn_type: GRU
WAYPOINT:
continuous_distance: True
continuous_offset: True
discrete_distances: 6
discrete_offsets: 7
max_distance_prediction: 2.75
max_distance_var: 3.52
max_offset_var: 0.0685
min_distance_prediction: 0.25
min_distance_var: 0.0625
min_offset_var: 0.011
offset_temperature: 1.0
predict_distance: True
predict_offset: True
ablate_depth: False
ablate_instruction: False
ablate_rgb: False
normalize_rgb: False
policy_name: CMAPolicy
NUM_CHECKPOINTS: 10
NUM_ENVIRONMENTS: 16
NUM_PROCESSES: -1
NUM_UPDATES: 10000
ORBSLAM2:
ANGLE_TH: 0.2617993877991494
BETA: 100
CAMERA_HEIGHT: 1.25
DEPTH_DENORM: 10.0
DIST_REACHED_TH: 0.15
DIST_TO_STOP: 0.05
D_OBSTACLE_MAX: 4.0
D_OBSTACLE_MIN: 0.1
H_OBSTACLE_MAX: 1.25
H_OBSTACLE_MIN: 0.375
MAP_CELL_SIZE: 0.1
MAP_SIZE: 40
MIN_PTS_IN_OBSTACLE: 320.0
NEXT_WAYPOINT_TH: 0.5
NUM_ACTIONS: 3
PLANNER_MAX_STEPS: 500
PREPROCESS_MAP: True
SLAM_SETTINGS_PATH: habitat_baselines/slambased/data/mp3d3_small1k.yaml
SLAM_VOCAB_PATH: habitat_baselines/slambased/data/ORBvoc.txt
PROFILING:
CAPTURE_START_STEP: -1
NUM_STEPS_TO_CAPTURE: -1
RESULTS_DIR: data/checkpoints/pretrained/evals
RL:
CHECKPOINT_INTERVAL: 250
DDPPO:
backbone: resnet18
distrib_backend: NCCL
force_distributed: False
num_recurrent_layers: 1
pretrained: False
pretrained_encoder: False
pretrained_weights: data/ddppo-models/gibson-2plus-resnet50.pth
requeue_path: data/interrupted_state.pth
reset_critic: True
rnn_type: GRU
start_from_requeue: False
sync_frac: 0.6
train_encoder: True
LOG_INTERVAL: 10
NUM_UPDATES: 200000
POLICY:
OBS_TRANSFORMS:
CENTER_CROPPER:
HEIGHT: 256
WIDTH: 256
CENTER_CROPPER_PER_SENSOR:
SENSOR_CROPS: [('rgb', (224, 224)), ('depth', (256, 256))]
CUBE2EQ:
HEIGHT: 256
SENSOR_UUIDS: []
WIDTH: 512
CUBE2FISH:
FOV: 180
HEIGHT: 256
PARAMS: (0.2, 0.2, 0.2)
SENSOR_UUIDS: []
WIDTH: 256
ENABLED_TRANSFORMS: ()
EQ2CUBE:
HEIGHT: 256
SENSOR_UUIDS: []
WIDTH: 256
OBS_STACK:
SENSOR_REWRITES: [('rgb', ['rgb', 'rgb_1', 'rgb_2', 'rgb_3', 'rgb_4', 'rgb_5', 'rgb_6', 'rgb_7', 'rgb_8', 'rgb_9', 'rgb_10', 'rgb_11']), ('depth', ['depth', 'depth_1', 'depth_2', 'depth_3', 'depth_4', 'depth_5', 'depth_6', 'depth_7', 'depth_8', 'depth_9', 'depth_10', 'depth_11'])]
RESIZE_SHORTEST_EDGE:
SIZE: 256
name: PointNavResNetPolicy
PPO:
clip_param: 0.2
clip_value_loss: True
distance_entropy_coef: 0.0
entropy_coef: 0.01
eps: 1e-05
gamma: 0.99
hidden_size: 512
lr: 0.0002
max_grad_norm: 0.2
num_mini_batch: 4
num_steps: 16
offset_entropy_coef: 0.0
offset_regularize_coef: 0.1146
pano_entropy_coef: 1.0
ppo_epoch: 2
reward_window_size: 50
tau: 0.95
use_double_buffered_sampler: False
use_gae: True
use_linear_clip_decay: False
use_linear_lr_decay: False
use_normalized_advantage: False
value_loss_coef: 0.5
REWARD_MEASURE: waypoint_reward_measure
SLACK_REWARD: -0.01
SUCCESS_MEASURE: success
SUCCESS_REWARD: 2.5
SENSORS: ['RGB_SENSOR', 'DEPTH_SENSOR']
SIMULATOR_GPU_IDS: [0]
TASK_CONFIG:
DATASET:
CONTENT_SCENES: ['*']
DATA_PATH: data/datasets/R2R_VLNCE_v1-3_preprocessed/{split}/{split}.json.gz
EPISODES_ALLOWED: ['*']
LANGUAGES: ['*']
ROLES: ['guide']
SCENES_DIR: data/scene_datasets/
SPLIT: train
TYPE: VLN-CE-v1
ENVIRONMENT:
ITERATOR_OPTIONS:
CYCLE: True
GROUP_BY_SCENE: True
MAX_SCENE_REPEAT_EPISODES: -1
MAX_SCENE_REPEAT_STEPS: 10000
NUM_EPISODE_SAMPLE: -1
SHUFFLE: True
STEP_REPETITION_RANGE: 0.2
MAX_EPISODE_SECONDS: 10000000
MAX_EPISODE_STEPS: 500
PYROBOT:
BASE_CONTROLLER: proportional
BASE_PLANNER: none
BUMP_SENSOR:
TYPE: PyRobotBumpSensor
DEPTH_SENSOR:
CENTER_CROP: False
HEIGHT: 480
MAX_DEPTH: 5.0
MIN_DEPTH: 0.0
NORMALIZE_DEPTH: True
TYPE: PyRobotDepthSensor
WIDTH: 640
LOCOBOT:
ACTIONS: ['BASE_ACTIONS', 'CAMERA_ACTIONS']
BASE_ACTIONS: ['go_to_relative', 'go_to_absolute']
CAMERA_ACTIONS: ['set_pan', 'set_tilt', 'set_pan_tilt']
RGB_SENSOR:
CENTER_CROP: False
HEIGHT: 480
TYPE: PyRobotRGBSensor
WIDTH: 640
ROBOT: locobot
ROBOTS: ['locobot']
SENSORS: ['RGB_SENSOR', 'DEPTH_SENSOR', 'BUMP_SENSOR']
SEED: 100
SIMULATOR:
ACTION_SPACE_CONFIG: v0
AGENTS: ['AGENT_0']
AGENT_0:
ANGULAR_ACCELERATION: 12.56
ANGULAR_FRICTION: 1.0
COEFFICIENT_OF_RESTITUTION: 0.0
HEIGHT: 1.5
IS_SET_START_STATE: False
LINEAR_ACCELERATION: 20.0
LINEAR_FRICTION: 0.5
MASS: 32.0
RADIUS: 0.1
SENSORS: ['RGB_SENSOR', 'DEPTH_SENSOR']
START_POSITION: [0, 0, 0]
START_ROTATION: [0, 0, 0, 1]
DEFAULT_AGENT_ID: 0
DEPTH_SENSOR:
HEIGHT: 256
HFOV: 90
MAX_DEPTH: 10.0
MIN_DEPTH: 0.0
NORMALIZE_DEPTH: True
ORIENTATION: [0.0, 0.0, 0.0]
POSITION: [0, 1.25, 0]
TYPE: HabitatSimDepthSensor
WIDTH: 256
FORWARD_STEP_SIZE: 0.25
HABITAT_SIM_V0:
ALLOW_SLIDING: True
ENABLE_PHYSICS: False
GPU_DEVICE_ID: 0
GPU_GPU: False
PHYSICS_CONFIG_FILE: ./data/default.physics_config.json
RGB_SENSOR:
HEIGHT: 224
HFOV: 90
ORIENTATION: [0.0, 0.0, 0.0]
POSITION: [0, 1.25, 0]
TYPE: HabitatSimRGBSensor
WIDTH: 224
SCENE: data/scene_datasets/habitat-test-scenes/van-gogh-room.glb
SEED: 100
SEMANTIC_SENSOR:
HEIGHT: 480
HFOV: 90
ORIENTATION: [0.0, 0.0, 0.0]
POSITION: [0, 1.25, 0]
TYPE: HabitatSimSemanticSensor
WIDTH: 640
TILT_ANGLE: 15
TURN_ANGLE: 15
TYPE: Sim-v0
TASK:
ACTIONS:
ANSWER:
TYPE: AnswerAction
GO_TOWARD_POINT:
TYPE: GoTowardPoint
rotate_agent: True
LOOK_DOWN:
TYPE: LookDownAction
LOOK_UP:
TYPE: LookUpAction
MOVE_FORWARD:
TYPE: MoveForwardAction
STOP:
TYPE: StopAction
TELEPORT:
TYPE: TeleportAction
TURN_LEFT:
TYPE: TurnLeftAction
TURN_RIGHT:
TYPE: TurnRightAction
ANSWER_ACCURACY:
TYPE: AnswerAccuracy
COLLISIONS:
TYPE: Collisions
COMPASS_SENSOR:
TYPE: CompassSensor
CORRECT_ANSWER:
TYPE: CorrectAnswer
DISTANCE_TO_GOAL:
DISTANCE_TO: POINT
TYPE: DistanceToGoal
EPISODE_INFO:
TYPE: EpisodeInfo
GLOBAL_GPS_SENSOR:
DIMENSIONALITY: 2
TYPE: GlobalGPSSensor
GOAL_SENSOR_UUID: pointgoal
GPS_SENSOR:
DIMENSIONALITY: 2
TYPE: GPSSensor
HEADING_SENSOR:
TYPE: HeadingSensor
IMAGEGOAL_SENSOR:
TYPE: ImageGoalSensor
INSTRUCTION_SENSOR:
TYPE: InstructionSensor
INSTRUCTION_SENSOR_UUID: instruction
MEASUREMENTS: ['DISTANCE_TO_GOAL', 'SUCCESS', 'SPL', 'NDTW', 'PATH_LENGTH', 'ORACLE_SUCCESS', 'STEPS_TAKEN']
NDTW:
FDTW: True
GT_PATH: data/datasets/R2R_VLNCE_v1-3_preprocessed/{split}/{split}_gt.json.gz
SPLIT: train
SUCCESS_DISTANCE: 3.0
TYPE: NDTW
OBJECTGOAL_SENSOR:
GOAL_SPEC: TASK_CATEGORY_ID
GOAL_SPEC_MAX_VAL: 50
TYPE: ObjectGoalSensor
ORACLE_ACTION_SENSOR:
GOAL_RADIUS: 0.5
TYPE: OracleActionSensor
ORACLE_NAVIGATION_ERROR:
TYPE: OracleNavigationError
ORACLE_SPL:
TYPE: OracleSPL
ORACLE_SUCCESS:
SUCCESS_DISTANCE: 3.0
TYPE: OracleSuccess
PANO_ANGLE_FEATURE_SENSOR:
CAMERA_NUM: 12
TYPE: AngleFeaturesSensor
PANO_ROTATIONS: 12
PATH_LENGTH:
TYPE: PathLength
POINTGOAL_SENSOR:
DIMENSIONALITY: 2
GOAL_FORMAT: POLAR
TYPE: PointGoalSensor
POINTGOAL_WITH_GPS_COMPASS_SENSOR:
DIMENSIONALITY: 2
GOAL_FORMAT: POLAR
TYPE: PointGoalWithGPSCompassSensor
POSSIBLE_ACTIONS: ['STOP', 'MOVE_FORWARD', 'TURN_LEFT', 'TURN_RIGHT']
PROXIMITY_SENSOR:
MAX_DETECTION_RADIUS: 2.0
TYPE: ProximitySensor
QUESTION_SENSOR:
TYPE: QuestionSensor
RXR_INSTRUCTION_SENSOR:
TYPE: RxRInstructionSensor
features_path: data/datasets/RxR_VLNCE_v0/text_features/rxr_{split}/{id:06}_{lang}_text_features.npz
SDTW:
TYPE: SDTW
SENSORS: ['INSTRUCTION_SENSOR', 'SHORTEST_PATH_SENSOR', 'VLN_ORACLE_PROGRESS_SENSOR']
SHORTEST_PATH_SENSOR:
GOAL_RADIUS: 0.5
TYPE: ShortestPathSensor
USE_ORIGINAL_FOLLOWER: False
SOFT_SPL:
TYPE: SoftSPL
SPL:
SUCCESS_DISTANCE: 3.0
TYPE: SPL
STEPS_TAKEN:
TYPE: StepsTaken
SUCCESS:
SUCCESS_DISTANCE: 3.0
TYPE: Success
SUCCESS_DISTANCE: 3.0
TOP_DOWN_MAP:
DRAW_BORDER: True
DRAW_GOAL_AABBS: True
DRAW_GOAL_POSITIONS: True
DRAW_SHORTEST_PATH: True
DRAW_SOURCE: True
DRAW_VIEW_POINTS: True
FOG_OF_WAR:
DRAW: True
FOV: 90
VISIBILITY_DIST: 5.0
MAP_PADDING: 3
MAP_RESOLUTION: 1024
MAX_EPISODE_STEPS: 1000
TYPE: TopDownMap
TOP_DOWN_MAP_VLNCE:
DRAW_BORDER: True
DRAW_FIXED_WAYPOINTS: True
DRAW_MP3D_AGENT_PATH: True
DRAW_REFERENCE_PATH: True
DRAW_SHORTEST_PATH: True
DRAW_SOURCE_AND_TARGET: True
FOG_OF_WAR:
DRAW: True
FOV: 90
VISIBILITY_DIST: 5.0
GRAPHS_FILE: data/connectivity_graphs.pkl
MAP_RESOLUTION: 1024
MAX_EPISODE_STEPS: 1000
TYPE: TopDownMapVLNCE
TYPE: VLN-v0
VLN_ORACLE_PROGRESS_SENSOR:
TYPE: VLNOracleProgressSensor
WAYPOINT_REWARD_MEASURE:
TYPE: WaypointRewardMeasure
distance_scalar: 1.0
scale_slack_on_prediction: True
slack_reward: -0.05
success_reward: 2.5
use_distance_scaled_slack_reward: True
TENSORBOARD_DIR: data/tensorboard_dirs/debug
TORCH_GPU_ID: 0
TOTAL_NUM_STEPS: -1.0
TRAINER_NAME: dagger
VERBOSE: True
VIDEO_DIR: data/videos/debug
VIDEO_OPTION: []
2025-08-23 22:32:05,231 Initializing dataset VLN-CE-v1
2025-08-23 22:32:05,266 initializing sim Sim-v0
WARNING: Logging before InitGoogleLogging() is written to STDERR
I0823 22:32:05.266547 21439 ManagedContainerBase.cpp:19] ManagedContainerBase::convertFilenameToJSON : Filename : default changed to proposed JSON configuration filename : default.scene_dataset_config.json
I0823 22:32:05.266567 21439 AttributesManagerBase.h:283] AttributesManager<T>::createFromJsonOrDefaultInternal (Dataset) : Proposing JSON name : default.scene_dataset_config.json from original name : default | This file does not exist.
I0823 22:32:05.266610 21439 AssetAttributesManager.cpp:117] Asset attributes (capsule3DSolid : capsule3DSolid_hemiRings_4_cylRings_1_segments_12_halfLen_0.75_useTexCoords_false_useTangents_false) created and registered.
I0823 22:32:05.266628 21439 AssetAttributesManager.cpp:117] Asset attributes (capsule3DWireframe : capsule3DWireframe_hemiRings_8_cylRings_1_segments_16_halfLen_1) created and registered.
I0823 22:32:05.266644 21439 AssetAttributesManager.cpp:117] Asset attributes (coneSolid : coneSolid_segments_12_halfLen_1.25_rings_1_useTexCoords_false_useTangents_false_capEnd_true) created and registered.
I0823 22:32:05.266654 21439 AssetAttributesManager.cpp:117] Asset attributes (coneWireframe : coneWireframe_segments_32_halfLen_1.25) created and registered.
I0823 22:32:05.266659 21439 AssetAttributesManager.cpp:117] Asset attributes (cubeSolid : cubeSolid) created and registered.
I0823 22:32:05.266664 21439 AssetAttributesManager.cpp:117] Asset attributes (cubeWireframe : cubeWireframe) created and registered.
I0823 22:32:05.266676 21439 AssetAttributesManager.cpp:117] Asset attributes (cylinderSolid : cylinderSolid_rings_1_segments_12_halfLen_1_useTexCoords_false_useTangents_false_capEnds_true) created and registered.
I0823 22:32:05.266686 21439 AssetAttributesManager.cpp:117] Asset attributes (cylinderWireframe : cylinderWireframe_rings_1_segments_32_halfLen_1) created and registered.
I0823 22:32:05.266692 21439 AssetAttributesManager.cpp:117] Asset attributes (icosphereSolid : icosphereSolid_subdivs_1) created and registered.
I0823 22:32:05.266697 21439 AssetAttributesManager.cpp:117] Asset attributes (icosphereWireframe : icosphereWireframe_subdivs_1) created and registered.
I0823 22:32:05.266705 21439 AssetAttributesManager.cpp:117] Asset attributes (uvSphereSolid : uvSphereSolid_rings_8_segments_16_useTexCoords_false_useTangents_false) created and registered.
I0823 22:32:05.266713 21439 AssetAttributesManager.cpp:117] Asset attributes (uvSphereWireframe : uvSphereWireframe_rings_16_segments_32) created and registered.
I0823 22:32:05.266716 21439 AssetAttributesManager.cpp:105] AssetAttributesManager::buildCtorFuncPtrMaps : Built default primitive asset templates : 12
I0823 22:32:05.266949 21439 SceneDatasetAttributesManager.cpp:23] File (default) not found, so new default dataset attributes created and registered.
I0823 22:32:05.266952 21439 MetadataMediator.cpp:47] MetadataMediator::createDataset : Dataset default successfully created.
I0823 22:32:05.268803 21439 AttributesManagerBase.h:283] AttributesManager<T>::createFromJsonOrDefaultInternal (Physics Manager) : Proposing JSON name : ./data/default.physics_config.json from original name : ./data/default.physics_config.json | This file does not exist.
I0823 22:32:05.268810 21439 PhysicsAttributesManager.cpp:27] File (./data/default.physics_config.json) not found, so new default physics manager attributes created and registered.
I0823 22:32:05.268812 21439 AbstractObjectAttributesManagerBase.h:175] AbstractObjectAttributesManager<T>::createObject (Stage) : Making attributes with handle : data/scene_datasets/mp3d/zsNo4HB9uLZ/zsNo4HB9uLZ.glb
I0823 22:32:05.268814 21439 ManagedContainerBase.cpp:19] ManagedContainerBase::convertFilenameToJSON : Filename : data/scene_datasets/mp3d/zsNo4HB9uLZ/zsNo4HB9uLZ.glb changed to proposed JSON configuration filename : data/scene_datasets/mp3d/zsNo4HB9uLZ/zsNo4HB9uLZ.stage_config.json
I0823 22:32:05.268816 21439 AttributesManagerBase.h:283] AttributesManager<T>::createFromJsonOrDefaultInternal (Stage) : Proposing JSON name : data/scene_datasets/mp3d/zsNo4HB9uLZ/zsNo4HB9uLZ.stage_config.json from original name : data/scene_datasets/mp3d/zsNo4HB9uLZ/zsNo4HB9uLZ.glb | This file does not exist.
E0823 22:32:05.268834 21439 StageAttributesManager.cpp:90] StageAttributesManager::registerObjectFinalize : Render asset template handle : data/scene_datasets/mp3d/zsNo4HB9uLZ/zsNo4HB9uLZ.glb specified in stage template with handle : data/scene_datasets/mp3d/zsNo4HB9uLZ/zsNo4HB9uLZ.glb does not correspond to any existing file or primitive render asset. Aborting.
I0823 22:32:05.268836 21439 AbstractObjectAttributesManagerBase.h:181] AbstractObjectAttributesManager<T>::createObject (Stage) : Done making attributes with handle : data/scene_datasets/mp3d/zsNo4HB9uLZ/zsNo4HB9uLZ.glb
进程已结束,退出代码为 139 (interrupted by signal 11:SIGSEGV)
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