parameter.py

FOLDER_NAME = 'HDPlanner_navigation'
model_path = f'model/{FOLDER_NAME}'
train_path = f'train/{FOLDER_NAME}'
gifs_path = f'gifs/{FOLDER_NAME}'
SUMMARY_WINDOW = 50
LOAD_MODEL = False  # do you want to load the model trained before
SAVE_IMG_GAP = 1000

CELL_SIZE = 0.4  # meter
NODE_RESOLUTION = 4.0  # meter
DOWNSAMPLE_SIZE = NODE_RESOLUTION // CELL_SIZE
SENSOR_RANGE = 20  # meter
UTILITY_RANGE = 0.2 * SENSOR_RANGE

LOCAL_MAP_SIZE = 60  # meter
EXTENDED_LOCAL_MAP_SIZE = 6 * SENSOR_RANGE * 1.05 #126?

MAX_EPISODE_STEP = 128
REPLAY_SIZE = 10000
MINIMUM_BUFFER_SIZE = 5000
BATCH_SIZE = 64
LR = 1e-5
GAMMA = 1

LOCAL_NODE_INPUT_DIM = 7
INPUT_DIM = 7
EMBEDDING_DIM = 128

LOCAL_K_SIZE = 25  # the number of neighboring nodes
LOCAL_NODE_PADDING_SIZE = 360  # the number of nodes will be padded to this value

USE_GPU = False  # do you want to collect training data using GPUs
USE_GPU_GLOBAL = True  # do you want to train the network using GPUs
NUM_GPU = 1
NUM_META_AGENT = 16
MIN_CENTERS_BEFORE_SPARSIFY = 2
SPARSIFICATION_CENTERS_KNN_RAD = 20
CENTER_SIZE = 25
MIN_UTILITY  = 2