Update examples to use candle_lib.

Author: jmohdyusof

examples/ADRP/adrp.py

@@ -1,7 +1,6 @@
 from __future__ import print_function
 
 import os
-import sys
 import logging
 
 import pandas as pd
@@ -12,10 +11,6 @@
 from sklearn.preprocessing import StandardScaler
 
 file_path = os.path.dirname(os.path.realpath(__file__))
-# lib_path = os.path.abspath(os.path.join(file_path, '..'))
-# sys.path.append(lib_path)
-lib_path2 = os.path.abspath(os.path.join(file_path, "..", "..", "common"))
-sys.path.append(lib_path2)
 
 import candle
 

examples/ADRP/reg_go2.py

@@ -1,7 +1,6 @@
 import pandas as pd
 import numpy as np
 import os
-import sys
 import argparse
 
 import math
@@ -19,13 +18,10 @@
 
 from tensorflow.keras.callbacks import ModelCheckpoint, CSVLogger, ReduceLROnPlateau, EarlyStopping
 
-
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import StandardScaler
 
 file_path = os.path.dirname(os.path.realpath(__file__))
-lib_path = os.path.abspath(os.path.join(file_path, '..', '..', 'common'))
-sys.path.append(lib_path)
 
 psr = argparse.ArgumentParser(description='input csv file')
 psr.add_argument('--in', default='in_file')

examples/M16/M16_test.py

@@ -1,13 +1,10 @@
 import os
-import sys
 import pandas as pd
 import numpy as np
 import warnings
 warnings.filterwarnings("ignore")
 
 file_path = os.path.dirname(os.path.realpath(__file__))
-lib_path2 = os.path.abspath(os.path.join(file_path, "..", "..", "common"))
-sys.path.append(lib_path2)
 
 import candle
 

examples/histogen/extract_code_baseline_pytorch.py

@@ -13,11 +13,6 @@
 from vqvae import VQVAE
 
 file_path = os.path.dirname(os.path.realpath(__file__))
-lib_path = os.path.abspath(os.path.join(file_path, '..'))
-sys.path.append(lib_path)
-lib_path2 = os.path.abspath(os.path.join(file_path, '..', '..', 'common'))
-sys.path.append(lib_path2)
-
 
 import candle
 

examples/histogen/sample_baseline_pytorch.py

@@ -1,5 +1,4 @@
 import os
-import sys
 
 import torch
 from torchvision.utils import save_image
@@ -9,11 +8,6 @@
 from pixelsnail import PixelSNAIL
 
 file_path = os.path.dirname(os.path.realpath(__file__))
-lib_path = os.path.abspath(os.path.join(file_path, '..'))
-sys.path.append(lib_path)
-lib_path2 = os.path.abspath(os.path.join(file_path, '..', '..', 'common'))
-sys.path.append(lib_path2)
-
 
 import candle
 

examples/histogen/train_pixelsnail_baseline_pytorch.py

@@ -19,11 +19,6 @@
 from scheduler import CycleScheduler
 
 file_path = os.path.dirname(os.path.realpath(__file__))
-lib_path = os.path.abspath(os.path.join(file_path, '..'))
-sys.path.append(lib_path)
-lib_path2 = os.path.abspath(os.path.join(file_path, '..', '..', 'common'))
-sys.path.append(lib_path2)
-
 
 import candle
 

examples/histogen/train_vqvae_baseline_pytorch.py

@@ -16,10 +16,6 @@
 
 
 file_path = os.path.dirname(os.path.realpath(__file__))
-lib_path = os.path.abspath(os.path.join(file_path, '..'))
-sys.path.append(lib_path)
-lib_path2 = os.path.abspath(os.path.join(file_path, '..', '..', 'common'))
-sys.path.append(lib_path2)
 
 port = (2 ** 15 + 2 ** 14 + hash(os.getuid()
         if sys.platform != "win32" else 1) % 2 ** 14)

examples/image-vae/image_vae_baseline_pytorch.py

@@ -13,11 +13,8 @@
 from model import GeneralVae, PictureDecoder, PictureEncoder, customLoss
 from utils import AverageMeter
 import os
-import sys
 
 file_path = os.path.dirname(os.path.realpath(__file__))
-lib_path = os.path.abspath(os.path.join(file_path, '..', '..', 'common'))
-sys.path.append(lib_path)
 
 import candle
 

examples/image-vae/sample_baseline_pytorch.py

@@ -1,6 +1,5 @@
 import logging
 import os
-import sys
 
 import numpy as np
 import torch
@@ -13,8 +12,6 @@
 logger.setLevel(logging.CRITICAL)
 
 file_path = os.path.dirname(os.path.realpath(__file__))
-lib_path = os.path.abspath(os.path.join(file_path, '..', '..', 'common'))
-sys.path.append(lib_path)
 
 import candle
 

examples/mnist/mnist.py

@@ -1,8 +1,5 @@
 import os
-import sys
 file_path = os.path.dirname(os.path.realpath(__file__))
-lib_path = os.path.abspath(os.path.join(file_path, '..', '..', 'common'))
-sys.path.append(lib_path)
 
 from tensorflow.keras import backend as K
 import candle