modify wrong args

model_zoo/official/cv/mobilenetv2/src/config.py

@@ -26,8 +26,9 @@ def set_config(args):
         "batch_size": 150,
         "epoch_size": 15,
         "warmup_epochs": 0,
-        "lr_max": 0.03,
+        "lr_init": .0,
         "lr_end": 0.03,
+        "lr_max": 0.03,
         "momentum": 0.9,
         "weight_decay": 4e-5,
         "label_smooth": 0.1,
@@ -45,9 +46,9 @@ def set_config(args):
         "batch_size": 150,
         "epoch_size": 200,
         "warmup_epochs": 0,
-        "lr": 0.8,
-        "lr_max": 0.03,
-        "lr_end": 0.03,
+        "lr_init": .0,
+        "lr_end": .0,
+        "lr_max": 0.8,
         "momentum": 0.9,
         "weight_decay": 4e-5,
         "label_smooth": 0.1,
@@ -66,9 +67,9 @@ def set_config(args):
         "batch_size": 256,
         "epoch_size": 200,
         "warmup_epochs": 4,
-        "lr": 0.4,
-        "lr_max": 0.03,
-        "lr_end": 0.03,
+        "lr_init": 0.00,
+        "lr_end": 0.00,
+        "lr_max": 0.4,
         "momentum": 0.9,
         "weight_decay": 4e-5,
         "label_smooth": 0.1,

model_zoo/official/cv/mobilenetv2/src/utils.py

@@ -17,7 +17,6 @@ from mindspore import context
 from mindspore import nn
 from mindspore.common import dtype as mstype
 from mindspore.train.model import ParallelMode
-from mindspore.parallel._auto_parallel_context import auto_parallel_context
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig
 from mindspore.communication.management import get_rank, init, get_group_size
 
@@ -63,7 +62,7 @@ def set_context(config):
                             device_id=config.device_id, save_graphs=False)
     elif config.platform == "GPU":
         context.set_context(mode=context.GRAPH_MODE,
-                            device_target=args_opt.platform, save_graphs=False)
+                            device_target=config.platform, save_graphs=False)
 
 def config_ckpoint(config, lr, step_size):
     cb = None

model_zoo/official/cv/mobilenetv2/train.py

@@ -77,7 +77,7 @@ if __name__ == '__main__':
 
     # get learning rate
     lr = Tensor(get_lr(global_step=0,
-                       lr_init=0,
+                       lr_init=config.lr_init,
                        lr_end=config.lr_end,
                        lr_max=config.lr_max,
                        warmup_epochs=config.warmup_epochs,