modify functions with new api >> global_function

Classification/cnns/of_cnn_inference.py

@@ -7,6 +7,7 @@ import numpy as np
 from PIL import Image
 
 import config as configs
+
 parser = configs.get_parser()
 args = parser.parse_args()
 configs.print_args(args)
@@ -38,9 +39,9 @@ def load_image(image_path='test_img/ILSVRC2012_val_00020287.JPEG'):
     return np.ascontiguousarray(im, 'float32')
 
 
-@flow.global_function(flow.function_config())
-def InferenceNet(images:tp.Numpy.Placeholder((1, 3, 224, 224), dtype=flow.float)):
-    logits = model_dict[args.model](images,training=False)
+@flow.global_function("predict", flow.function_config())
+def InferenceNet(images: tp.Numpy.Placeholder((1, 3, 224, 224), dtype=flow.float)) -> tp.Numpy:
+    logits = model_dict[args.model](images, training=False)
     predictions = flow.nn.softmax(logits)
     return predictions
 
@@ -52,9 +53,9 @@ def main():
     check_point.load(args.model_load_dir)
 
     image = load_image(args.image_path)
-    predictions = InferenceNet(image).get()
-    clsidx = predictions.numpy().argmax()
-    print(predictions.numpy().max(), clsidx_2_labels[clsidx])
+    predictions = InferenceNet(image)
+    clsidx = predictions.argmax()
+    print(predictions.max(), clsidx_2_labels[clsidx])
 
 
 if __name__ == "__main__":

Classification/cnns/of_cnn_train_val.py

@@ -43,7 +43,7 @@ def label_smoothing(labels, classes, eta, dtype):
                         on_value=1 - eta + eta / classes, off_value=eta/classes)
 
 
-@flow.global_function(get_train_config(args))
+@flow.global_function("train", get_train_config(args))
 def TrainNet():
     if args.train_data_dir:
         assert os.path.exists(args.train_data_dir)
@@ -68,7 +68,7 @@ def TrainNet():
     return outputs
 
 
-@flow.global_function(get_val_config(args))
+@flow.global_function("predict", get_val_config(args))
 def InferenceNet():
     if args.val_data_dir:
         assert os.path.exists(args.val_data_dir)