update package structure

abducer/abducer_base.py → abl/abducer/abducer_base.py

@@ -10,16 +10,17 @@
 #
 # ================================================================#
 
-import sys
+# import sys
 
-sys.path.append(".")
-sys.path.append("..")
+# sys.path.append(".")
+# sys.path.append("..")
 
 import abc
-from abducer.kb import *
+# TODO 尽量别用import *
+from .kb import *
 import numpy as np
 from zoopt import Dimension, Objective, Parameter, Opt
-from utils.utils import confidence_dist, flatten, hamming_dist
+from ..utils.utils import confidence_dist, flatten, hamming_dist
 
 import math
 import time

abducer/kb.py → abl/abducer/kb.py

@@ -21,7 +21,7 @@ sys.path.append("..")
 
 from collections import defaultdict
 from itertools import product, combinations
-from utils.utils import flatten, reform_idx, hamming_dist, check_equal
+from ..utils.utils import flatten, reform_idx, hamming_dist, check_equal
 
 from multiprocessing import Pool
 
@@ -299,7 +299,7 @@ class add_prolog_KB(prolog_KB):
 class HED_prolog_KB(prolog_KB):
     def __init__(self, pseudo_label_list=[0, 1, '+', '=']):
         super().__init__(pseudo_label_list)
-        self.prolog.consult('./datasets/hed/learn_add.pl')
+        self.prolog.consult('../examples/datasets/hed/learn_add.pl')
 
     # corresponding to `con_sol is not None` in `consistent_score_mapped` within `learn_add.py`
     def logic_forward(self, exs):

framework.py → abl/framework.py

@@ -14,7 +14,7 @@ import pickle as pk
 
 import numpy as np
 
-from utils.plog import INFO, DEBUG, clocker
+from .utils.plog import INFO, DEBUG, clocker
 
 def block_sample(X, Z, Y, sample_num, epoch_idx):
     part_num = (len(X) // sample_num)

framework_hed.py → abl/framework_hed.py

@@ -16,12 +16,15 @@ import torch.nn as nn
 import numpy as np
 import os
 
-from utils.plog import INFO, DEBUG, clocker
-from utils.utils import flatten, reform_idx, block_sample, gen_mappings, mapping_res, remapping_res
+from .utils.plog import INFO, DEBUG, clocker
+from .utils.utils import flatten, reform_idx, block_sample, gen_mappings, mapping_res, remapping_res
 
-from models.nn import MLP, SymbolNetAutoencoder
-from models.basic_model import BasicModel, BasicDataset
-from datasets.hed.get_hed import get_pretrain_data
+from .models.nn import MLP, SymbolNetAutoencoder
+from .models.basic_model import BasicModel, BasicDataset
+
+import sys
+sys.path.append("..")
+from examples.datasets.hed.get_hed import get_pretrain_data
 
 def result_statistics(pred_Z, Z, Y, logic_forward, char_acc_flag):
     result = {}

models/nn.py → abl/models/nn.py

@@ -10,9 +10,6 @@
 #
 # ================================================================#
 
-import sys
-
-sys.path.append("..")
 
 import torchvision
 
@@ -23,8 +20,6 @@ from torch.autograd import Variable
 import torchvision.transforms as transforms
 import numpy as np
 
-from models.basic_model import BasicModel
-import utils.plog as plog
 
 
 class LeNet5(nn.Module):

models/wabl_models.py → abl/models/wabl_models.py

@@ -21,7 +21,6 @@ from sklearn.preprocessing import StandardScaler
 from sklearn.svm import SVC
 from sklearn.gaussian_process import GaussianProcessClassifier
 from sklearn.gaussian_process.kernels import RBF
-from models.basic_model import BasicModel
 
 import pickle as pk
 import random

utils/utils.py → abl/utils/utils.py

@@ -1,5 +1,5 @@
 import numpy as np
-from utils.plog import INFO
+from .plog import INFO
 from collections import OrderedDict
 
 # for multiple predictions, modify from `learn_add.py`