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configs.py
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from yacs.config import CfgNode as CN
_C = CN()
# -----------------------------------------------------------------------------
# EXPERIMENT
# -----------------------------------------------------------------------------
_C.EXP = CN()
_C.EXP.EXP_ID = ""
_C.EXP.SEED = 0
_C.EXP.TASK = 'cls'
_C.EXP.DATASET = 'modelnet40'
_C.EXP.MODEL_NAME = 'mv'
_C.EXP.LOSS_NAME = 'cross_entropy'
_C.EXP.OPTIMIZER = 'vanilla'
_C.EXP.METRIC = 'acc'
_C.EXP.RANK = False
_C.EXP.random_init = False
#------------------------------------------------------------------------------
# Extra Experiment Parameters
#------------------------------------------------------------------------------
_C.EXP_EXTRA = CN()
_C.EXP_EXTRA.no_val = True
_C.EXP_EXTRA.no_test = False
_C.EXP_EXTRA.val_eval_freq = 1
_C.EXP_EXTRA.test_eval_freq = 1
_C.EXP_EXTRA.save_ckp = 25
# -----------------------------------------------------------------------------
# DATALOADER (contains things common across the datasets)
# -----------------------------------------------------------------------------
_C.DATALOADER = CN()
_C.DATALOADER.batch_size = 60
_C.DATALOADER.num_workers = 0
# -----------------------------------------------------------------------------
# TRAINING DETAILS (contains things common across the training)
# -----------------------------------------------------------------------------
_C.TRAIN = CN()
_C.TRAIN.num_epochs = 300
_C.TRAIN.learning_rate = 1e-3
_C.TRAIN.lr_decay_factor = 0.5
_C.TRAIN.lr_reduce_patience = 10
_C.TRAIN.l2 = 0.0
_C.TRAIN.early_stop = 300
_C.TRAIN.lr_clip = 0.00001
#-----------------------------------------------------------------------------
# MODELNET40_RSCNN
#-----------------------------------------------------------------------------
_C.DATALOADER.MODELNET40_RSCNN = CN()
_C.DATALOADER.MODELNET40_RSCNN.data_path = './data/'
_C.DATALOADER.MODELNET40_RSCNN.train_data_path = 'train_files.txt'
_C.DATALOADER.MODELNET40_RSCNN.valid_data_path = 'train_files.txt'
_C.DATALOADER.MODELNET40_RSCNN.test_data_path = 'test_files.txt'
_C.DATALOADER.MODELNET40_RSCNN.num_points = 1024
#-----------------------------------------------------------------------------
# MODELNET40_PN2
#-----------------------------------------------------------------------------
_C.DATALOADER.MODELNET40_PN2 = CN()
_C.DATALOADER.MODELNET40_PN2.train_data_path = './data/modelnet40_ply_hdf5_2048/train_files.txt'
_C.DATALOADER.MODELNET40_PN2.valid_data_path = './data/modelnet40_ply_hdf5_2048/train_files.txt'
_C.DATALOADER.MODELNET40_PN2.test_data_path = './data/modelnet40_ply_hdf5_2048/test_files.txt'
_C.DATALOADER.MODELNET40_PN2.num_points = 1024
#-----------------------------------------------------------------------------
# MODELNET40_DGCNN
#-----------------------------------------------------------------------------
_C.DATALOADER.MODELNET40_DGCNN = CN()
_C.DATALOADER.MODELNET40_DGCNN.train_data_path = './data/modelnet40_ply_hdf5_2048/train_files.txt'
_C.DATALOADER.MODELNET40_DGCNN.valid_data_path = './data/modelnet40_ply_hdf5_2048/train_files.txt'
_C.DATALOADER.MODELNET40_DGCNN.test_data_path = './data/modelnet40_ply_hdf5_2048/test_files.txt'
_C.DATALOADER.MODELNET40_DGCNN.num_points = 1024
#-----------------------------------------------------------------------------
# MODELNET40_C
#-----------------------------------------------------------------------------
_C.DATALOADER.MODELNET40_C = CN()
_C.DATALOADER.MODELNET40_C.test_data_path = './data/modelnet40_c_f1/'
_C.DATALOADER.MODELNET40_C.corruption = 'uniform'
_C.DATALOADER.MODELNET40_C.severity = 1
# ----------------------------------------------------------------------------
# MODEL
# -----------------------------------------------------------------------------
_C.MODEL = CN()
# -----------------------------------------------------------------------------
# MV MODEL
# -----------------------------------------------------------------------------
_C.MODEL.MV = CN()
_C.MODEL.MV.backbone = 'resnet18'
_C.MODEL.MV.feat_size = 16
# -----------------------------------------------------------------------------
# RSCNN MODEL
# -----------------------------------------------------------------------------
_C.MODEL.RSCNN = CN()
_C.MODEL.RSCNN.ssn_or_msn = True
# -----------------------------------------------------------------------------
# PN2 MODEL
# -----------------------------------------------------------------------------
_C.MODEL.PN2 = CN()
_C.MODEL.PN2.version_cls = 1.0
# -----------------------------------------------------------------------------
# PCTE MODEL
# -----------------------------------------------------------------------------
_C.MODEL.PCTE = CN()
_C.MODEL.PCTE.pe_param = [0.9,256]
# -----------------------------------------------------------------------------
# PCTES MODEL
# -----------------------------------------------------------------------------
_C.MODEL.PCTES = CN()
_C.MODEL.PCTES.pe_param = [0.9,64]
# -----------------------------------------------------------------------------
# PEMax MODEL
# -----------------------------------------------------------------------------
_C.MODEL.PEMax = CN()
_C.MODEL.PEMax.pe_param = [0.09,1024]
# -----------------------------------------------------------------------------
# PEMean MODEL
# -----------------------------------------------------------------------------
_C.MODEL.PEMean = CN()
_C.MODEL.PEMean.pe_param = [0.9,1024]
# -----------------------------------------------------------------------------
# PEMedian MODEL
# -----------------------------------------------------------------------------
_C.MODEL.PEMedian = CN()
_C.MODEL.PEMedian.pe_param = [0.9,1024]
# -----------------------------------------------------------------------------
# PEHist MODEL
# -----------------------------------------------------------------------------
_C.MODEL.PEHist = CN()
_C.MODEL.PEHist.pe_param = [0.9,1024]
_C.MODEL.PEHist.pool_param = 50
# -----------------------------------------------------------------------------
# PERansac MODEL
# -----------------------------------------------------------------------------
_C.MODEL.PERansac = CN()
_C.MODEL.PERansac.pe_param = [0.9,1024]
_C.MODEL.PERansac.pe_param = 50
_C.AUG = CN()
_C.AUG.NAME = 'none'
_C.AUG.BETA = 1.
_C.AUG.PROB = 0.5
_C.AUG.MIXUPRATE = 0.4
_C.ADAPT = CN()
_C.ADAPT.METHOD = 'none'
_C.ADAPT.ITER = 1
def get_cfg_defaults():
"""Get a yacs CfgNode object with default values for my_project."""
# Return a clone so that the defaults will not be altered
# This is for the "local variable" use pattern
return _C.clone()