modify redundant code

mindspore/_check_deps_version.py

@@ -34,6 +34,7 @@ def parse_args():
     args = parser.parse_args()
     return args
 
+
 def check_deps_version(mindspore_version, supported_version):
     """
        check te/hccl/topi version
@@ -62,17 +63,18 @@ def check_deps_version(mindspore_version, supported_version):
             print(f"MindSpore version {mindspore_version} and \"topi\" wheel package version {v} does not "
                   "match, reference to the match info on: https://www.mindspore.cn/install")
 
-    # pylint: disable=broad-except
     except Exception as e:
         print("CheckFailed: ", e.args)
         print("Minspore relies on the 3 whl packages of \"te\", \"topi\" and \"hccl\" in the \"fwkacllib\" "
               "folder of the Ascend 910 AI software package, please check whether they are installed "
               "correctly or not, reference to the match info on: https://www.mindspore.cn/install")
 
+
 def main():
     args = parse_args()
     check_deps_version(args.mindspore_version, args.supported_version)
 
+
 if __name__ == "__main__":
     sys.path = sys.path[1:] # avoid the impact of relative path env, only affect this process
     main()

mindspore/_check_version.py

@@ -292,9 +292,7 @@ class AscendEnvChecker(EnvChecker):
             return
 
         try:
-            # pylint: disable=unused-import
             import te
-        # pylint: disable=broad-except
         except Exception:
             if Path(self.tbe_path).is_dir():
                 if os.getenv('LD_LIBRARY_PATH'):
@@ -373,6 +371,7 @@ class AscendEnvChecker(EnvChecker):
                     return self.v
         return self.v
 
+
 def check_version_and_env_config():
     """check version and env config"""
     if __package_name__.lower() == "mindspore-ascend":
@@ -384,7 +383,6 @@ def check_version_and_env_config():
         return
 
     try:
-        # pylint: disable=unused-import
         from . import _c_expression
         # check version of ascend site or cuda
         env_checker.check_version()

mindspore/common/parameter.py

@@ -350,7 +350,6 @@ class Parameter(Tensor_):
             Parameter, a new parameter.
         """
         x = copy(self)
-        # pylint: disable=protected-access
         x.param_info = self.param_info.clone()
         x.is_init = False
         x.init = self.init
@@ -426,11 +425,9 @@ class Parameter(Tensor_):
     def _update_tensor_data(self, data):
         "Update the parameter by a Tensor."
         if isinstance(self, Tensor):
-            # for Tensor same shape:
             self.init_flag = False
             self.init = None
             return self.assign_value(data)
-        # create a new tensor
         new_param = Parameter(data, self.name, self.requires_grad)
         new_param.param_info = self.param_info
         return new_param

mindspore/context.py

@@ -238,7 +238,6 @@ class _Context:
         graph_memory_max_size = _DEVICE_APP_MEMORY_SIZE - int(variable_memory_max_size[:-2])
         graph_memory_max_size_ = str(graph_memory_max_size) + " * 1024 * 1024 * 1024"
         self.set_param(ms_ctx_param.variable_memory_max_size, variable_memory_max_size_)
-        # pylint: disable=protected-access
         self.set_param(ms_ctx_param._graph_memory_max_size, graph_memory_max_size_)
 
     def set_max_device_memory(self, max_device_memory):

mindspore/core/ops/adam.cc

@@ -43,7 +43,6 @@ abstract::AbstractBasePtr AdamInfer(const PrimitivePtr &primitive, const std::ve
   auto infer_m_type = CheckAndConvertUtils::CheckTensorTypeValid("m_type", m_type, common_valid_types, prim_name);
   auto infer_v_type = CheckAndConvertUtils::CheckTensorTypeValid("v_type", v_type, common_valid_types, prim_name);
   (void)CheckAndConvertUtils::CheckTensorTypeValid("grad_type", grad_type, common_valid_types, prim_name);
-  // auto infer_grad_type = grad_type->cast<TensorTypePtr>()->element();
   auto output0 = std::make_shared<abstract::AbstractTensor>(infer_var_type, var_shape);
   auto output1 = std::make_shared<abstract::AbstractTensor>(infer_m_type, m_shape);
   auto output2 = std::make_shared<abstract::AbstractTensor>(infer_v_type, v_shape);

mindspore/core/ops/assert.cc

@@ -52,7 +52,6 @@ AbstractBasePtr AssertInfer(const abstract::AnalysisEnginePtr &, const Primitive
     if (condition_shape[0] == 1) {
       auto condition_value = reinterpret_cast<bool *>(input_args[0]->BuildValue()->cast<tensor::TensorPtr>()->data_c());
       MS_EXCEPTION_IF_NULL(condition_value);
-      //      auto condition_value = GetValue<bool>(input_args[0]->BuildValue());
       CheckAndConvertUtils::CheckInteger("condition[0]", *condition_value, kEqual, 1, op_name);
     }
     condition = input_args[0]->BuildType();

mindspore/nn/layer/thor_layer.py

@@ -184,10 +184,9 @@ class Dense_Thor(Cell):
         s = 'input_channels={}, output_channels={}'.format(self.in_channels, self.out_channels)
         if self.has_bias:
             s += ', has_bias={}'.format(self.has_bias)
-        # if self.activation_flag:
-        #     s += ', activation={}'.format(self.activation)
         return s
 
+
 class _Conv(Cell):
     """
     Applies a N-D convolution over an input signal composed of several input planes.
@@ -212,7 +211,6 @@ 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_non_negative_int(padding, 'padding', self.cls_name)