!4714 bug fix for ME

Merge pull request !4714 from chenzhongming/new_master

mindspore/nn/layer/conv.py

@@ -51,6 +51,8 @@ class _Conv(Cell):
         self.kernel_size = kernel_size
         self.stride = stride
         self.pad_mode = pad_mode
+        self.weight_init = weight_init
+        self.bias_init = bias_init
         if isinstance(padding, int):
             Validator.check_integer('padding', padding, 0, Rel.GE, self.cls_name)
             self.padding = padding
@@ -85,12 +87,12 @@ class _Conv(Cell):
             shape = [in_channels, out_channels // group, *kernel_size]
         else:
             shape = [out_channels, in_channels // group, *kernel_size]
-        self.weight = Parameter(initializer(weight_init, shape), name='weight')
+        self.weight = Parameter(initializer(self.weight_init, shape), name='weight')
 
         if check_bool(has_bias):
-            self.bias = Parameter(initializer(bias_init, [out_channels]), name='bias')
+            self.bias = Parameter(initializer(self.bias_init, [out_channels]), name='bias')
         else:
-            if bias_init != 'zeros':
+            if self.bias_init != 'zeros':
                 logger.warning("Value of 'has_bias' is False, value of 'bias_init' will be ignored.")
             self.bias = None
 
@@ -249,11 +251,8 @@ class Conv2d(_Conv):
                 self.dilation,
                 self.group,
                 self.has_bias,
-                self.weight,
-                self.bias)
-
-        if self.has_bias:
-            s += ', bias={}'.format(self.bias)
+                self.weight_init,
+                self.bias_init)
         return s
 
 
@@ -431,11 +430,8 @@ class Conv1d(_Conv):
                 self.dilation,
                 self.group,
                 self.has_bias,
-                self.weight,
-                self.bias)
-
-        if self.has_bias:
-            s += ', bias={}'.format(self.bias)
+                self.weight_init,
+                self.bias_init)
         return s
 
 
@@ -605,8 +601,8 @@ class Conv2dTranspose(_Conv):
                                                   self.dilation,
                                                   self.group,
                                                   self.has_bias,
-                                                  self.weight,
-                                                  self.bias)
+                                                  self.weight_init,
+                                                  self.bias_init)
         return s
 
 
@@ -788,8 +784,8 @@ class Conv1dTranspose(_Conv):
                                                   self.dilation,
                                                   self.group,
                                                   self.has_bias,
-                                                  self.weight,
-                                                  self.bias)
+                                                  self.weight_init,
+                                                  self.bias_init)
         return s
 
 

model_zoo/official/cv/mobilenetv2/eval.py

@@ -30,7 +30,7 @@ from src.mobilenetV2 import mobilenet_v2
 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_targe', type=str, default=None, help='run device_targe')
+parser.add_argument('--device_target', type=str, default=None, help='run device_target')
 args_opt = parser.parse_args()
 
 

model_zoo/official/cv/mobilenetv2/scripts/run_train.sh

@@ -73,6 +73,7 @@ run_gpu()
     mpirun -n $2 --allow-run-as-root \
     python ${BASEPATH}/../train.py \
         --dataset_path=$4 \
+        --pre_trained=$5 \
         --device_target=$1 \
         &> ../train.log &  # dataset train folder
 }
@@ -81,7 +82,7 @@ if [ $# -gt 6 ] || [ $# -lt 4 ]
 then
     echo "Usage:\n \
           Ascend: sh run_train.sh Ascend [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [RANK_TABLE_FILE] [DATASET_PATH] [CKPT_PATH]\n \
-          GPU: sh run_train.sh GPU [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH]\n \
+          GPU: sh run_train.sh GPU [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] [CKPT_PATH]\n \
           "
 exit 1
 fi

model_zoo/official/cv/mobilenetv2/train.py

@@ -49,10 +49,10 @@ de.config.set_seed(1)
 parser = argparse.ArgumentParser(description='Image classification')
 parser.add_argument('--dataset_path', type=str, default=None, help='Dataset path')
 parser.add_argument('--pre_trained', type=str, default=None, help='Pretrained checkpoint path')
-parser.add_argument('--device_targe', type=str, default=None, help='run device_targe')
+parser.add_argument('--device_target', type=str, default=None, help='run device_target')
 args_opt = parser.parse_args()
 
-if args_opt.device_targe == "Ascend":
+if args_opt.device_target == "Ascend":
     device_id = int(os.getenv('DEVICE_ID'))
     rank_id = int(os.getenv('RANK_ID'))
     rank_size = int(os.getenv('RANK_SIZE'))
@@ -61,7 +61,7 @@ if args_opt.device_targe == "Ascend":
     context.set_context(mode=context.GRAPH_MODE,
                         device_target="Ascend",
                         device_id=device_id, save_graphs=False)
-elif args_opt.device_targe == "GPU":
+elif args_opt.device_target == "GPU":
     context.set_context(mode=context.GRAPH_MODE,
                         device_target="GPU",
                         save_graphs=False)
@@ -161,13 +161,13 @@ class Monitor(Callback):
 
 
 if __name__ == '__main__':
-    if args_opt.device_targe == "GPU":
+    if args_opt.device_target == "GPU":
         # train on gpu
         print("train args: ", args_opt)
         print("cfg: ", config_gpu)
 
         # define network
-        net = mobilenet_v2(num_classes=config_gpu.num_classes, device_targe="GPU")
+        net = mobilenet_v2(num_classes=config_gpu.num_classes, device_target="GPU")
         # define loss
         if config_gpu.label_smooth > 0:
             loss = CrossEntropyWithLabelSmooth(smooth_factor=config_gpu.label_smooth,
@@ -179,7 +179,7 @@ if __name__ == '__main__':
         dataset = create_dataset(dataset_path=args_opt.dataset_path,
                                  do_train=True,
                                  config=config_gpu,
-                                 device_targe=args_opt.device_targe,
+                                 device_target=args_opt.device_target,
                                  repeat_num=1,
                                  batch_size=config_gpu.batch_size)
         step_size = dataset.get_dataset_size()
@@ -216,7 +216,7 @@ if __name__ == '__main__':
         # begin train
         model.train(epoch_size, dataset, callbacks=cb)
         print("============== End Training ==============")
-    elif args_opt.device_targe == "Ascend":
+    elif args_opt.device_target == "Ascend":
         # train on ascend
         print("train args: ", args_opt, "\ncfg: ", config_ascend,
               "\nparallel args: rank_id {}, device_id {}, rank_size {}".format(rank_id, device_id, rank_size))
@@ -228,7 +228,7 @@ if __name__ == '__main__':
             init()
 
         epoch_size = config_ascend.epoch_size
-        net = mobilenet_v2(num_classes=config_ascend.num_classes, device_targe="Ascend")
+        net = mobilenet_v2(num_classes=config_ascend.num_classes, device_target="Ascend")
         net.to_float(mstype.float16)
         for _, cell in net.cells_and_names():
             if isinstance(cell, nn.Dense):
@@ -242,7 +242,7 @@ if __name__ == '__main__':
         dataset = create_dataset(dataset_path=args_opt.dataset_path,
                                  do_train=True,
                                  config=config_ascend,
-                                 device_targe=args_opt.device_targe,
+                                 device_target=args_opt.device_target,
                                  repeat_num=1,
                                  batch_size=config_ascend.batch_size)
         step_size = dataset.get_dataset_size()
@@ -276,4 +276,4 @@ if __name__ == '__main__':
                 cb += [ckpt_cb]
         model.train(epoch_size, dataset, callbacks=cb)
     else:
-        raise ValueError("Unsupported device_targe.")
+        raise ValueError("Unsupported device_target.")

model_zoo/official/cv/mobilenetv3/Readme.md

@@ -27,8 +27,8 @@ Dataset used: [imagenet](http://www.image-net.org/)
 
 # Environment Requirements
 
-- Hardware（Ascend/GPU）
-  - Prepare hardware environment with Ascend or GPU processor. If you want to try Ascend  , please send the [application form](https://obs-9be7.obs.cn-east-2.myhuaweicloud.com/file/other/Ascend%20Model%20Zoo%E4%BD%93%E9%AA%8C%E8%B5%84%E6%BA%90%E7%94%B3%E8%AF%B7%E8%A1%A8.docx) to ascend@huawei.com. Once approved, you can get the resources. 
+- Hardware（GPU）
+  - Prepare hardware environment with GPU processor.
 - Framework
   - [MindSpore](http://10.90.67.50/mindspore/archive/20200506/OpenSource/me_vm_x86/)
 - For more information, please check the resources below：
@@ -60,14 +60,12 @@ Dataset used: [imagenet](http://www.image-net.org/)
 
 ### Usage
 
-- Ascend: sh run_train.sh Ascend [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH]
 - GPU: sh run_trian.sh GPU [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH]
 
 ### Launch
 
 ``` 
 # training example
-  Ascend: sh run_train.sh Ascend 8 192.168.0.1 0,1,2,3,4,5,6,7 ~/imagenet/train/
   GPU: sh run_train.sh GPU 8 0,1,2,3,4,5,6,7 ~/imagenet/train/
 ```
 
@@ -86,14 +84,12 @@ epoch time: 138331.250, per step time: 221.330, avg loss: 3.917
 
 ### Usage
 
-- Ascend: sh run_infer.sh Ascend [DATASET_PATH] [CHECKPOINT_PATH]
 - GPU: sh run_infer.sh GPU [DATASET_PATH] [CHECKPOINT_PATH]
 
 ### Launch
 
 ``` 
 # infer example
-    Ascend: sh run_infer.sh Ascend ~/imagenet/val/ ~/train/mobilenet-200_625.ckpt
     GPU: sh run_infer.sh GPU ~/imagenet/val/ ~/train/mobilenet-200_625.ckpt
 ```