rm bool arg of script

model_zoo/official/cv/lenet_quant/eval_quant.py

@@ -38,8 +38,6 @@ parser.add_argument('--data_path', type=str, default="./MNIST_Data",
                     help='path where the dataset is saved')
 parser.add_argument('--ckpt_path', type=str, default="",
                     help='if mode is test, must provide path where the trained ckpt file')
-parser.add_argument('--dataset_sink_mode', type=bool, default=True,
-                    help='dataset_sink_mode is False or True')
 args = parser.parse_args()
 
 if __name__ == "__main__":
@@ -67,5 +65,5 @@ if __name__ == "__main__":
         raise ValueError("Load param into net fail!")
 
     print("============== Starting Testing ==============")
-    acc = model.eval(ds_eval, dataset_sink_mode=args.dataset_sink_mode)
+    acc = model.eval(ds_eval, dataset_sink_mode=True)
     print("============== {} ==============".format(acc))

model_zoo/official/cv/lenet_quant/export.py

@@ -36,8 +36,6 @@ parser.add_argument('--data_path', type=str, default="./MNIST_Data",
                     help='path where the dataset is saved')
 parser.add_argument('--ckpt_path', type=str, default="",
                     help='if mode is test, must provide path where the trained ckpt file')
-parser.add_argument('--dataset_sink_mode', type=bool, default=True,
-                    help='dataset_sink_mode is False or True')
 args = parser.parse_args()
 
 if __name__ == "__main__":

model_zoo/official/cv/lenet_quant/train_quant.py

@@ -41,8 +41,6 @@ parser.add_argument('--data_path', type=str, default="./MNIST_Data",
                     help='path where the dataset is saved')
 parser.add_argument('--ckpt_path', type=str, default="",
                     help='if mode is test, must provide path where the trained ckpt file')
-parser.add_argument('--dataset_sink_mode', type=bool, default=True,
-                    help='dataset_sink_mode is False or True')
 args = parser.parse_args()
 
 if __name__ == "__main__":
@@ -76,5 +74,5 @@ if __name__ == "__main__":
 
     print("============== Starting Training ==============")
     model.train(cfg['epoch_size'], ds_train, callbacks=[ckpt_callback, LossMonitor()],
-                dataset_sink_mode=args.dataset_sink_mode)
+                dataset_sink_mode=True)
     print("============== End Training ==============")

model_zoo/official/cv/mobilenetv2_quant/eval.py

@@ -32,7 +32,6 @@ parser = argparse.ArgumentParser(description='Image classification')
 parser.add_argument('--checkpoint_path', type=str, default=None, help='Checkpoint file path')
 parser.add_argument('--dataset_path', type=str, default=None, help='Dataset path')
 parser.add_argument('--device_target', type=str, default=None, help='Run device target')
-parser.add_argument('--quantization_aware', type=bool, default=False, help='Use quantization aware training')
 args_opt = parser.parse_args()
 
 if __name__ == '__main__':
@@ -51,9 +50,8 @@ if __name__ == '__main__':
 
     # define fusion network
     network = mobilenetV2(num_classes=config_device_target.num_classes)
-    if args_opt.quantization_aware:
-        # convert fusion network to quantization aware network
-        network = quant.convert_quant_network(network, bn_fold=True, per_channel=[True, False], symmetric=[True, False])
+    # convert fusion network to quantization aware network
+    network = quant.convert_quant_network(network, bn_fold=True, per_channel=[True, False], symmetric=[True, False])
     # define network loss
     loss = nn.SoftmaxCrossEntropyWithLogits(is_grad=False, sparse=True, reduction='mean')
 

model_zoo/official/cv/mobilenetv2_quant/scripts/run_infer_quant.sh

@@ -50,5 +50,4 @@ python ${BASEPATH}/../eval.py \
         --device_target=$1 \
         --dataset_path=$2 \
         --checkpoint_path=$3 \
-        --quantization_aware=True \
         &> infer.log &  # dataset val folder path