Cherry pick 1.1.1 (#332)

* fix conflict

* fix windows CPU envs (#315)

* change scipy.misc.imread() to imageio.imread() (#324)

* adapt PY2 PY3 (#326)

demo/slimfacenet/dataloader/casia.py

@@ -13,7 +13,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import numpy as np
-import scipy.misc
+import six
+if six.PY2:
+    import scipy.misc as imgreader
+else:
+    import imageio as imgreader
 import os
 import paddle
 from paddle import fluid
@@ -54,7 +58,7 @@ class CASIA_Face(object):
             target = self.label_list[index]
 
             try:
-                img = scipy.misc.imread(img_path)
+                img = imgreader.imread(img_path)
             except:
                 continue
 

demo/slimfacenet/dataloader/lfw.py

@@ -13,8 +13,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import numpy as np
-import scipy.misc
-
+import six
+if six.PY2:
+    import scipy.misc as imgreader
+else:
+    import imageio as imgreader
 import paddle
 from paddle import fluid
 
@@ -33,10 +36,10 @@ class LFW(object):
                 return
             index = self.shuffle_idx.pop(0)
 
-            imgl = scipy.misc.imread(self.imgl_list[index])
+            imgl = imgreader.imread(self.imgl_list[index])
             if len(imgl.shape) == 2:
                 imgl = np.stack([imgl] * 3, 2)
-            imgr = scipy.misc.imread(self.imgr_list[index])
+            imgr = imgreader.imread(self.imgr_list[index])
             if len(imgr.shape) == 2:
                 imgr = np.stack([imgr] * 3, 2)
 

demo/slimfacenet/train_eval.py

@@ -150,7 +150,10 @@ def train(exe, train_program, train_out, test_program, test_out, args):
 
 
 def build_program(program, startup, args, is_train=True):
-    num_trainers = len(os.getenv('CUDA_VISIBLE_DEVICES').split(','))
+    if args.use_gpu:
+        num_trainers = fluid.core.get_cuda_device_count()
+    else:
+        num_trainers = int(os.environ.get('CPU_NUM', 1))
     places = fluid.cuda_places() if args.use_gpu else fluid.CPUPlace()
 
     train_dataset = CASIA_Face(root=args.train_data_dir)
@@ -166,7 +169,7 @@ def build_program(program, startup, args, is_train=True):
                 image = fluid.data(
                     name='image', shape=[-1, 3, 112, 96], dtype='float32')
                 label = fluid.data(name='label', shape=[-1, 1], dtype='int64')
-                train_reader = paddle.batch(
+                train_reader = fluid.io.batch(
                     train_dataset.reader,
                     batch_size=args.train_batchsize // num_trainers,
                     drop_last=False)
@@ -187,7 +190,7 @@ def build_program(program, startup, args, is_train=True):
             else:
                 nl, nr, flods, flags = parse_filelist(args.test_data_dir)
                 test_dataset = LFW(nl, nr)
-                test_reader = paddle.batch(
+                test_reader = fluid.io.batch(
                     test_dataset.reader,
                     batch_size=args.test_batchsize,
                     drop_last=False)
@@ -231,7 +234,7 @@ def build_program(program, startup, args, is_train=True):
 def quant_val_reader_batch():
     nl, nr, flods, flags = parse_filelist(args.test_data_dir)
     test_dataset = LFW(nl, nr)
-    test_reader = paddle.batch(
+    test_reader = fluid.io.batch(
         test_dataset.reader, batch_size=1, drop_last=False)
     shuffle_reader = fluid.io.shuffle(test_reader, 3)
 
@@ -298,14 +301,16 @@ def main():
         help='The path of the extract features save, must be .mat file')
     args = parser.parse_args()
 
-    num_trainers = len(os.getenv('CUDA_VISIBLE_DEVICES').split(','))
+    if args.use_gpu:
+        num_trainers = fluid.core.get_cuda_device_count()
+    else:
+        num_trainers = int(os.environ.get('CPU_NUM', 1))
     print(args)
     print('num_trainers: {}'.format(num_trainers))
     if args.save_ckpt == None:
         args.save_ckpt = 'output'
-    if not os.path.exists(args.save_ckpt):
-        subprocess.call(['mkdir', '-p', args.save_ckpt])
-
+    if not os.path.isdir(args.save_ckpt):
+        os.makedirs(args.save_ckpt)
     with open(os.path.join(args.save_ckpt, 'log.txt'), 'w+') as f:
         f.writelines(str(args) + '\n')
         f.writelines('num_trainers: {}'.format(num_trainers) + '\n')
@@ -346,7 +351,7 @@ def main():
              executor=exe)
         nl, nr, flods, flags = parse_filelist(args.test_data_dir)
         test_dataset = LFW(nl, nr)
-        test_reader = paddle.batch(
+        test_reader = fluid.io.batch(
             test_dataset.reader,
             batch_size=args.test_batchsize,
             drop_last=False)