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config_55.py
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config_55.py
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from easydict import EasyDict as edict
__C = edict()
cfg = __C
#
# Dataset Config
#
__C.DATASETS = edict()
__C.DATASETS.SHAPENET55 = edict()
__C.DATASETS.SHAPENET55.CATEGORY_FILE_PATH = 'datasets/ShapeNet55'
__C.DATASETS.SHAPENET55.N_POINTS = 2048
__C.DATASETS.SHAPENET55.COMPLETE_POINTS_PATH = './shapenet_pc/%s'
#
# Dataset
#
__C.DATASET = edict()
__C.DATASET.TRAIN_DATASET = 'ShapeNet55'
__C.DATASET.TEST_DATASET = 'ShapeNet55'
#
# Constants
#
__C.CONST = edict()
__C.CONST.NUM_WORKERS = 4
__C.CONST.N_INPUT_POINTS = 2048
__C.CONST.mode = 'easy'
#suo
# Directories
#
__C.DIR = edict()
__C.DIR.OUT_PATH = 'SVDFormer_55'
__C.CONST.DEVICE = '0,1'
# __C.CONST.WEIGHTS = ''
# Memcached
#
__C.MEMCACHED = edict()
__C.MEMCACHED.ENABLED = False
__C.MEMCACHED.LIBRARY_PATH = '/mnt/lustre/share/pymc/py3'
__C.MEMCACHED.SERVER_CONFIG = '/mnt/lustre/share/memcached_client/server_list.conf'
__C.MEMCACHED.CLIENT_CONFIG = '/mnt/lustre/share/memcached_client/client.conf'
#
# Network
#
__C.NETWORK = edict()
__C.NETWORK.step1 = 2
__C.NETWORK.step2 = 4
__C.NETWORK.merge_points = 1024
__C.NETWORK.local_points = 1024
__C.NETWORK.view_distance = 1.5
#
# Train
#
__C.TRAIN = edict()
__C.TRAIN.BATCH_SIZE = 16
__C.TRAIN.N_EPOCHS = 300
__C.TRAIN.SAVE_FREQ = 5
__C.TRAIN.LEARNING_RATE = 0.0001
__C.TRAIN.LR_MILESTONES = [50, 100, 150, 200, 250]
__C.TRAIN.LR_DECAY_STEP = 2
__C.TRAIN.WARMUP_STEPS = 300
__C.TRAIN.GAMMA = .98
__C.TRAIN.BETAS = (.9, .999)
__C.TRAIN.WEIGHT_DECAY = 0
#
# Test
#
__C.TEST = edict()
__C.TEST.METRIC_NAME = 'ChamferDistance'