diff --git a/utils.py b/utils.py
index 8d8e5ba3..c63bae62 100644
--- a/utils.py
+++ b/utils.py
@@ -16,7 +16,7 @@
 import tensorflow.contrib.slim as slim
 
 def load_mnist(dataset_name):
-    data_dir = os.path.join("./data", dataset_name)
+    data_dir = os.path.join("data", dataset_name)
 
     def extract_data(filename, num_data, head_size, data_size):
         with gzip.open(filename) as bytestream:
@@ -25,16 +25,16 @@ def extract_data(filename, num_data, head_size, data_size):
             data = np.frombuffer(buf, dtype=np.uint8).astype(np.float)
         return data
 
-    data = extract_data(data_dir + '/train-images-idx3-ubyte.gz', 60000, 16, 28 * 28)
+    data = extract_data(os.path.join(data_dir, 'train-images-idx3-ubyte.gz'), 60000, 16, 28 * 28)
     trX = data.reshape((60000, 28, 28, 1))
 
-    data = extract_data(data_dir + '/train-labels-idx1-ubyte.gz', 60000, 8, 1)
+    data = extract_data(os.path.join(data_dir, 'train-labels-idx1-ubyte.gz'), 60000, 8, 1)
     trY = data.reshape((60000))
 
-    data = extract_data(data_dir + '/t10k-images-idx3-ubyte.gz', 10000, 16, 28 * 28)
+    data = extract_data(os.path.join(data_dir, 't10k-images-idx3-ubyte.gz'), 10000, 16, 28 * 28)
     teX = data.reshape((10000, 28, 28, 1))
 
-    data = extract_data(data_dir + '/t10k-labels-idx1-ubyte.gz', 10000, 8, 1)
+    data = extract_data(os.path.join(data_dir, 't10k-labels-idx1-ubyte.gz'), 10000, 8, 1)
     teY = data.reshape((10000))
 
     trY = np.asarray(trY)
@@ -146,4 +146,4 @@ def discrete_cmap(N, base_cmap=None):
     base = plt.cm.get_cmap(base_cmap)
     color_list = base(np.linspace(0, 1, N))
     cmap_name = base.name + str(N)
-    return base.from_list(cmap_name, color_list, N)
\ No newline at end of file
+    return base.from_list(cmap_name, color_list, N)