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config_vipc.py
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config_vipc.py
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from easydict import EasyDict as edict
__C = edict()
cfg = __C
#
# Dataset Config
#
__C.DATASETS = edict()
__C.DATASETS.SHAPENET = edict()
__C.DATASETS.SHAPENET.N_POINTS = 2048
__C.DATASETS.SHAPENET.VIPC_PATH = '/data/ShapeNetViPC-Dataset'#path to dataset
#
# Constants
#
__C.CONST = edict()
__C.CONST.NUM_WORKERS = 8
__C.CONST.DATA_perfetch = 8
#
# Directories
#
__C.DIR = edict()
__C.DIR.OUT_PATH = '/project/EGIInet/project_logs'#path to save checkpoints and logs
__C.CONST.DEVICE = '0,1'
#
# Network
#
__C.NETWORK = edict()
__C.NETWORK.EGIInet = edict()
__C.NETWORK.EGIInet.embed_dim = 192
__C.NETWORK.EGIInet.depth = 6
__C.NETWORK.EGIInet.img_patch_size = 14
__C.NETWORK.EGIInet.pc_sample_rate = 0.125
__C.NETWORK.EGIInet.pc_sample_scale = 2
__C.NETWORK.EGIInet.fuse_layer_num = 2
__C.NETWORK.shared_encoder = edict()
__C.NETWORK.shared_encoder.block_head = 12
__C.NETWORK.shared_encoder.pc_h_hidden_dim = 192
#
# Train
#
__C.TRAIN = edict()
__C.TRAIN.BATCH_SIZE = 128
__C.TRAIN.N_EPOCHS = 160
__C.TRAIN.SAVE_FREQ = 40
__C.TRAIN.LEARNING_RATE = 0.001
__C.TRAIN.LR_MILESTONES = [16,32,48,64,80,96,112,128,144]
__C.TRAIN.LR_DECAY_STEP = [16,32,48,64,80,96,112,128,144]
__C.TRAIN.WARMUP_STEPS = 1
__C.TRAIN.GAMMA = 0.7
__C.TRAIN.BETAS = (.9, .999)
__C.TRAIN.WEIGHT_DECAY = 0
__C.TRAIN.CATE = 'plane'
__C.TRAIN.d_size = 1
#
# Test
#
__C.TEST = edict()
__C.TEST.METRIC_NAME = 'ChamferDistance'
__C.TEST.CATE = 'plane'
__C.TEST.BATCH_SIZE = 64
#__C.CONST.WEIGHTS = r"/project/EGIInet/checkpoints/plane-ckpt-best.pth" #path to pre-trained checkpoints