make Image2Image support windows (fix #1412)

tensorpack · Mar 26, 2020 · f1a8acf · f1a8acf
1 parent e50423d
commit f1a8acf
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Showing 3 changed files with 7 additions and 5 deletions.
diff --git a/examples/GAN/Image2Image.py b/examples/GAN/Image2Image.py
@@ -146,11 +146,12 @@ def optimizer(self):
         return tf.train.AdamOptimizer(lr, beta1=0.5, epsilon=1e-3)
 
 
-def split_input(img):
+def split_input(dp):
     """
-    img: an RGB image of shape (s, 2s, 3).
+    dp: the datapoint. first component is an RGB image of shape (s, 2s, 3).
     :return: [input, output]
     """
+    img = dp[0]
     # split the image into left + right pairs
     s = img.shape[0]
     assert img.shape[1] == 2 * s
@@ -169,7 +170,7 @@ def get_data():
     imgs = glob.glob(os.path.join(datadir, '*.jpg'))
     ds = ImageFromFile(imgs, channel=3, shuffle=True)
 
-    ds = MapData(ds, lambda dp: split_input(dp[0]))
+    ds = MapData(ds, split_input)
     augs = [imgaug.Resize(286), imgaug.RandomCrop(256)]
     ds = AugmentImageComponents(ds, augs, (0, 1))
     ds = BatchData(ds, BATCH)
@@ -186,7 +187,7 @@ def sample(datadir, model_path):
 
     imgs = glob.glob(os.path.join(datadir, '*.jpg'))
     ds = ImageFromFile(imgs, channel=3, shuffle=True)
-    ds = MapData(ds, lambda dp: split_input(dp[0]))
+    ds = MapData(ds, split_input)
     ds = AugmentImageComponents(ds, [imgaug.Resize(256)], (0, 1))
     ds = BatchData(ds, 6)
 

diff --git a/tensorpack/models/batch_norm.py b/tensorpack/models/batch_norm.py
@@ -1,3 +1,4 @@
+# Copyright (c) Tensorpack Contributors. All Rights Reserved
 # -*- coding: utf-8 -*-
 # File: batch_norm.py
 

diff --git a/tensorpack/tfutils/common.py b/tensorpack/tfutils/common.py
@@ -201,7 +201,7 @@ def collect_env_info():
         # List devices with NVML
         data.append(
             ("CUDA_VISIBLE_DEVICES",
-             os.environ.get("CUDA_VISIBLE_DEVICES", str(None))))
+             os.environ.get("CUDA_VISIBLE_DEVICES", "Unspecified")))
         try:
             devs = defaultdict(list)
             with NVMLContext() as ctx: