优化了cnn路径

src/python/getting-started/digit-recognizer/cnn_keras-python3.6.py

@@ -17,13 +17,16 @@ from keras.models import Sequential
 from keras.optimizers import RMSprop
 from keras.preprocessing.image import ImageDataGenerator
 from keras.utils.np_utils import to_categorical  # convert to one-hot-encoding
+import os
 
 np.random.seed(2)
 
+# 数据路径
+data_dir = '/media/wsw/B634091A3408DF6D/data/kaggle/datasets/getting-started/digit-recognizer/'
+
 # Load the data
-train = pd.read_csv(
-    r'datasets/getting-started/digit-recognizer/input/train.csv')
-test = pd.read_csv(r'datasets/getting-started/digit-recognizer/input/test.csv')
+train = pd.read_csv(os.path.join(data_dir, 'input/train.csv'))
+test = pd.read_csv(os.path.join(data_dir, 'input/test.csv'))
 
 X_train = train.values[:, 1:]
 Y_train = train.values[:, 0]
@@ -129,6 +132,5 @@ submission = pd.concat(
     [pd.Series(
         range(1, 28001), name="ImageId"), results], axis=1)
 
-submission.to_csv(
-    "datasets/getting-started/digit-recognizer/ouput/Result_keras_CNN.csv",
-    index=False)
+submission.to_csv(os.path.join(data_dir, "output/Result_keras_CNN.csv",index=False))
+print('finished')

src/python/getting-started/digit-recognizer/cnn_pytorch-python3.6.py

@@ -17,14 +17,17 @@ import torch
 import torch.nn as nn
 from torch.autograd import Variable
 from torch.utils.data import Dataset, DataLoader
+import os.path
 
+# 数据路径
+data_dir = '/media/wsw/B634091A3408DF6D/data/kaggle/datasets/getting-started/digit-recognizer/'
 
 class CustomedDataSet(Dataset):
     def __init__(self, train=True):
         self.train = train
         if self.train:
             trainX = pd.read_csv(
-                '/opt/data/kaggle/getting-started/digit-recognizer/input/train.csv'
+                os.path.join(data_dir, 'input/train.csv')
                 # names=["ImageId", "Label"]
             )
             trainY = trainX.label.as_matrix().tolist()
@@ -34,7 +37,7 @@ class CustomedDataSet(Dataset):
             self.labellist = trainY
         else:
             testX = pd.read_csv(
-                '/opt/data/kaggle/getting-started/digit-recognizer/input/test.csv'
+                os.path.join(data_dir, 'input/test.csv')
             )
             self.testID = testX.index
             testX = testX.as_matrix().reshape(testX.shape[0], 1, 28, 28)
@@ -178,6 +181,6 @@ submission_df = pd.DataFrame(
           'Label': testLabel})
 # print(submission_df.head(10))
 submission_df.to_csv(
-    '/opt/data/kaggle/getting-started/digit-recognizer/output/Result_pytorch_CNN.csv',
+    os.path.join(data_dir, 'output/Result_pytorch_CNN.csv'),
     columns=["ImageId", "Label"],
     index=False)