!24604 rename keyword argument from 'acc_level' to 'boost_level' in class Model.__init__

Merge pull request !24604 from zhouneng/fix_issue_acc_level_rename_r1.4

mindspore/train/model.py

@@ -123,7 +123,7 @@ class Model:
     """
 
     def __init__(self, network, loss_fn=None, optimizer=None, metrics=None, eval_network=None,
-                 eval_indexes=None, amp_level="O0", acc_level="O0", **kwargs):
+                 eval_indexes=None, amp_level="O0", boost_level="O0", **kwargs):
         self._network = network
         self._loss_fn = loss_fn
         self._optimizer = optimizer
@@ -132,7 +132,7 @@ class Model:
         self._keep_bn_fp32 = True
         self._check_kwargs(kwargs)
         self._amp_level = amp_level
-        self._acc_level = acc_level
+        self._boost_level = boost_level
         self._eval_network = eval_network
         self._process_amp_args(kwargs)
         self._parallel_mode = _get_parallel_mode()
@@ -187,7 +187,7 @@ class Model:
 
     def _build_acc_network(self, kwargs):
         """Build the acc network."""
-        processor = acc.AutoAcc(self._acc_level, kwargs)
+        processor = acc.AutoAcc(self._boost_level, kwargs)
         if processor.level not in ["O1", "O2"]:
             return
         if self._optimizer is None:

model_zoo/official/cv/resnet/config/resnet101_imagenet2012_config.yaml

@@ -50,7 +50,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 all_reduce_fusion_config:

model_zoo/official/cv/resnet/config/resnet18_cifar10_config.yaml

@@ -50,7 +50,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 

model_zoo/official/cv/resnet/config/resnet18_cifar10_config_gpu.yaml

@@ -50,7 +50,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 

model_zoo/official/cv/resnet/config/resnet18_imagenet2012_config.yaml

@@ -52,7 +52,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 

model_zoo/official/cv/resnet/config/resnet18_imagenet2012_config_gpu.yaml

@@ -52,7 +52,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 

model_zoo/official/cv/resnet/config/resnet34_imagenet2012_config.yaml

@@ -52,7 +52,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 

model_zoo/official/cv/resnet/config/resnet50_cifar10_config.yaml

@@ -50,7 +50,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 all_reduce_fusion_config:

model_zoo/official/cv/resnet/config/resnet50_imagenet2012_Acc_config.yaml

@@ -52,7 +52,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O1"
+boost_mode: "O1"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 all_reduce_fusion_config:

model_zoo/official/cv/resnet/config/resnet50_imagenet2012_Ascend_Thor_config.yaml

@@ -53,7 +53,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 all_reduce_fusion_config:

model_zoo/official/cv/resnet/config/resnet50_imagenet2012_GPU_Thor_config.yaml

@@ -53,7 +53,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 all_reduce_fusion_config:

model_zoo/official/cv/resnet/config/resnet50_imagenet2012_config.yaml

@@ -52,7 +52,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 all_reduce_fusion_config:

model_zoo/official/cv/resnet/config/resnet_benchmark_GPU.yaml

@@ -25,7 +25,7 @@ eval: False
 save_ckpt: False
 mode_name: "GRAPH"
 dtype: "fp16"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 

model_zoo/official/cv/resnet/config/se-resnet50_imagenet2012_config.yaml

@@ -53,7 +53,7 @@ eval_interval: 1
 enable_cache: False
 cache_session_id: ""
 mode_name: "GRAPH"
-acc_mode: "O0"
+boost_mode: "O0"
 conv_init: "XavierUniform"
 dense_init: "TruncatedNormal"
 all_reduce_fusion_config:

model_zoo/official/cv/resnet/train.py

@@ -107,7 +107,7 @@ def set_parameter():
                                               gradients_mean=True)
             set_algo_parameters(elementwise_op_strategy_follow=True)
             if config.net_name == "resnet50" or config.net_name == "se-resnet50":
-                if config.acc_mode not in ["O1", "O2"]:
+                if config.boost_mode not in ["O1", "O2"]:
                     context.set_auto_parallel_context(all_reduce_fusion_config=config.all_reduce_fusion_config)
             elif config.net_name == "resnet101":
                 context.set_auto_parallel_context(all_reduce_fusion_config=config.all_reduce_fusion_config)
@@ -252,7 +252,7 @@ def train_net():
         model = Model(net, loss_fn=loss, optimizer=opt, metrics=metrics, eval_network=dist_eval_network)
     else:
         model = Model(net, loss_fn=loss, optimizer=opt, loss_scale_manager=loss_scale, metrics=metrics,
-                      amp_level="O2", acc_level=config.acc_mode, keep_batchnorm_fp32=False,
+                      amp_level="O2", boost_level=config.boost_mode, keep_batchnorm_fp32=False,
                       eval_network=dist_eval_network)
 
     if config.optimizer == "Thor" and config.dataset == "imagenet2012":