Get home dir from system instead hard-coding it

data.py

@@ -1,10 +1,14 @@
+from pathlib import Path
+
 import numpy as np
-import torch
-import torch.nn.functional as F
 from PIL import Image
 from torch.utils.data.dataset import Dataset
 from torchvision import transforms
 
+KAGGLE_PATH = Path.home() / '.kaggle/competitions/digit-recognizer/'
+KAGGLE_TEST_PATH = KAGGLE_PATH / 'test.csv'
+KAGGLE_TRAIN_PATH = KAGGLE_PATH / 'train.csv'
+
 
 class DigitRecognizerDataset(Dataset):
     def __init__(self, X, Y, pretransform=False):
@@ -33,7 +37,8 @@ def __len__(self):
         return self.len
 
 
-def train_validation_split(csv_file, max_rows=None, validation_num=None, pretransform=False):
+def train_validation_split(csv_file, max_rows=None, validation_num=None,
+                           pretransform=False):
     if max_rows:
         data = np.genfromtxt(csv_file, delimiter=',',
                              skip_header=1, max_rows=max_rows)

dtc.py

@@ -1,15 +1,17 @@
 import numpy as np
 from sklearn import tree
 
-data = np.genfromtxt('/home/arccha/.kaggle/competitions/digit-recognizer/train.csv',
+from data import KAGGLE_TRAIN_PATH, KAGGLE_TEST_PATH
+
+data = np.genfromtxt(KAGGLE_TRAIN_PATH,
                      delimiter=',', skip_header=1)
 
 Y, X = np.split(data, [1], axis=1)
 
 dtc = tree.DecisionTreeClassifier()
 dtc = dtc.fit(X, Y)
 
-X = np.genfromtxt('/home/arccha/.kaggle/competitions/digit-recognizer/test.csv',
+X = np.genfromtxt(KAGGLE_TEST_PATH,
                   delimiter=',', skip_header=1)
 
 Y = dtc.predict(X)

predict.py

@@ -1,20 +1,16 @@
-from pathlib import Path
+from torch.utils.data import DataLoader
+from tqdm import tqdm
 
-import numpy as np
-import torch
 from cuda import *
 from data import *
 from net import *
-from torch.utils.data import DataLoader
-from tqdm import tqdm
 
-test_path = Path('/home/arccha/.kaggle/competitions/digit-recognizer/test.csv')
-if not test_path.exists():
-    test_path = '../test.csv'
+if not KAGGLE_TEST_PATH.exists():
+    KAGGLE_TEST_PATH = '../test.csv'
 else:
-    test_path = str(test_path)
+    KAGGLE_TEST_PATH = str(KAGGLE_TEST_PATH)
 
-test_dataset = get_test_dataset(test_path)
+test_dataset = get_test_dataset(KAGGLE_TEST_PATH)
 test_loader = DataLoader(dataset=test_dataset, batch_size=32,
                          shuffle=False, num_workers=1, pin_memory=True)