# LICENSE file in the root directory of this source tree. from typing import List, Optional, Union import numpy as np from habitat import get_config as get_task_config from habitat.config import Config as CN DEFAULT_CONFIG_DIR = "configs/" CONFIG_FILE_SEPARATOR = "," # ----------------------------------------------------------------------------- # EXPERIMENT CONFIG # ----------------------------------------------------------------------------- _C = CN() _C.BASE_TASK_CONFIG_PATH = "configs/tasks/pointnav.yaml" _C.TASK_CONFIG = CN() # task_config will be stored as a config node _C.CMD_TRAILING_OPTS = [] # store command line options as list of strings _C.TRAINER_NAME = "ppo" _C.ENV_NAME = "NavRLEnv" _C.SIMULATOR_GPU_ID = 0 _C.TORCH_GPU_ID = 0 _C.VIDEO_OPTION = ["disk", "tensorboard"] _C.TENSORBOARD_DIR = "tb" _C.VIDEO_DIR = "video_dir" _C.TEST_EPISODE_COUNT = 2 _C.EVAL_CKPT_PATH_DIR = "data/checkpoints" # path to ckpt or path to ckpts dir _C.NUM_PROCESSES = 16 _C.SENSORS = ["RGB_SENSOR", "DEPTH_SENSOR"] _C.CHECKPOINT_FOLDER = "data/checkpoints" _C.NUM_UPDATES = 10000
# LICENSE file in the root directory of this source tree. from typing import List, Optional, Union import numpy as np from habitat import get_config as get_task_config from habitat.config import Config as CN DEFAULT_CONFIG_DIR = "configs/" CONFIG_FILE_SEPARATOR = "," # ----------------------------------------------------------------------------- # EXPERIMENT CONFIG # ----------------------------------------------------------------------------- _C = CN() _C.BASE_TASK_CONFIG_PATH = "configs/tasks/vln_r2r.yaml" _C.BERT_CONFIG = "/home/erick/Research/vln/libs/habitat/habitat-api/habitat_baselines/vln/config/bert_base_6layer_6connect.json" _C.BERT_GPU = 2 _C.BERT_PRE_TRAINED_MODEL = "bert-base-uncased" _C.MAX_TOKEN_LENGTH = 128 _C.TOKENIZER = "BertTokenizer" _C.DETECTRON2_GPU = 1 _C.DETECTRON2_MODEL = 'BUA_R_101_C4_MAX' #"IS_R_101_C4_3x" _C.TASK_CONFIG = CN() # task_config will be stored as a config node _C.CMD_TRAILING_OPTS = [] # store command line options as list of strings _C.TRAINER_NAME = "vln" _C.ENV_NAME = "VLNRLEnv" _C.SIMULATOR_GPU_ID = 3 _C.TORCH_GPU_ID = 4 _C.VIDEO_OPTION = ["disk", "tensorboard"] _C.TENSORBOARD_DIR = "tb"
from typing import List, Optional, Union import math import numpy as np from habitat_extensions import get_extended_config as get_task_config from habitat.config import Config as CN DEFAULT_CONFIG_DIR = "configs/" CONFIG_FILE_SEPARATOR = "," # ----------------------------------------------------------------------------- # EXPERIMENT CONFIG # ----------------------------------------------------------------------------- _C = CN() _C.PYT_RANDOM_SEED = 123 _C.BASE_TASK_CONFIG_PATH = "habitat_extensions/config/exploration_gibson.yaml" _C.TASK_CONFIG = CN() # task_config will be stored as a config node _C.CMD_TRAILING_OPTS = [] # store command line options as list of strings _C.TRAINER_NAME = "occant_exp" _C.ENV_NAME = "ExpRLEnv" _C.SIMULATOR_GPU_ID = 0 _C.SIMULATOR_GPU_IDS = [] # Assign specific GPUs to simulator _C.TORCH_GPU_ID = 0 _C.VIDEO_OPTION = ["disk", "tensorboard"] _C.TENSORBOARD_DIR = "tb" _C.VIDEO_DIR = "video_dir" _C.TEST_EPISODE_COUNT = -1 _C.EVAL_CKPT_PATH_DIR = "data/checkpoints" # path to ckpt or path to ckpts dir _C.EVAL_PREV_CKPT_ID = -1 # The evaluation starts at (this value + 1)th ckpt _C.NUM_PROCESSES = 36 _C.SENSORS = ["RGB_SENSOR", "DEPTH_SENSOR"]
from typing import List, Optional, Union import numpy as np from habitat import get_config as get_task_config from habitat.config import Config as CN DEFAULT_CONFIG_DIR = "configs/" CONFIG_FILE_SEPARATOR = "," # ----------------------------------------------------------------------------- # EXPERIMENT CONFIG # ----------------------------------------------------------------------------- _C = CN() _C.MULTIPLY_SCENES = False _C.BASE_TASK_CONFIG_PATH = "configs/tasks/explore_replica.yaml" _C.TASK_CONFIG = CN() # task_config will be stored as a config node _C.SHARED_DATA = [] # HACKY share stuff _C.SHARED_SIZES = [] # HACKY share stuff _C.CMD_TRAILING_OPTS = [] # store command line options as list of strings _C.TRAINER_NAME = "ppo" _C.ENV_NAME = "NavRLEnv" _C.SIMULATOR_GPU_ID = 0 _C.TORCH_GPU_ID = 0 _C.VIDEO_OPTION = ["disk", "tensorboard"] _C.VIDEO_OPTION_INTERVAL = 10 _C.TENSORBOARD_DIR = "tb" _C.VIDEO_DIR = "video_dir" _C.TEST_EPISODE_COUNT = 36 _C.EVAL_CKPT_PATH_DIR = "data/checkpoints" # path to ckpt or path to ckpts dir _C.NUM_PROCESSES = 12