diff --git a/mindspore/python/mindspore/common/api.py b/mindspore/python/mindspore/common/api.py
index e7da63f5668..f9e4c8746e1 100644
--- a/mindspore/python/mindspore/common/api.py
+++ b/mindspore/python/mindspore/common/api.py
@@ -148,7 +148,7 @@ def __get_compile_cache_dep_files(file_path, compile_cache_dep_files, pkg):
                 whole_module = n.name
             else:
                 whole_module = module_name
-                if not n.name is None:
+                if n.name is not None:
                     whole_module += "." + n.name
             try:
                 module_spec = importlib.util.find_spec(whole_module, pkg)
@@ -163,7 +163,7 @@ def __get_compile_cache_dep_files(file_path, compile_cache_dep_files, pkg):
             else:
                 continue
             # Exclude the installed modules.
-            if not _in_sys_path(dep_file_path) and not dep_file_path in compile_cache_dep_files:
+            if not _in_sys_path(dep_file_path) and dep_file_path not in compile_cache_dep_files:
                 logger.debug(f"dependent file path: {dep_file_path}")
                 compile_cache_dep_files.append(dep_file_path)
                 __get_compile_cache_dep_files(dep_file_path, compile_cache_dep_files, module.__package__)
@@ -184,8 +184,8 @@ def _get_compile_cache_dep_files():
 def _restore_mutable_attr(args_list, compile_args):
     """Restore the mutable attr for every arg."""
     new_compile_args = ()
-    for idx in range(len(args_list)):
-        if hasattr(args_list[idx], "__ms_mutable__") and getattr(args_list[idx], "__ms_mutable__"):
+    for idx, arg in enumerate(args_list):
+        if hasattr(arg, "__ms_mutable__") and getattr(arg, "__ms_mutable__"):
             new_compile_args += (mutable(compile_args[idx]),)
         else:
             new_compile_args += (compile_args[idx],)
diff --git a/mindspore/python/mindspore/common/dtype.py b/mindspore/python/mindspore/common/dtype.py
index 180ae8b3435..6fde2ee0103 100644
--- a/mindspore/python/mindspore/common/dtype.py
+++ b/mindspore/python/mindspore/common/dtype.py
@@ -190,7 +190,7 @@ def pytype_to_dtype(obj):
     if not isinstance(obj, type):
         raise TypeError("For 'pytype_to_dtype', the argument 'obj' must be a python type object,"
                         "such as int, float, str, etc. But got type {}.".format(type(obj)))
-    elif obj in _simple_types:
+    if obj in _simple_types:
         return _simple_types[obj]
     raise NotImplementedError(f"The python type {obj} cannot be converted to MindSpore type.")
 
diff --git a/mindspore/python/mindspore/common/tensor.py b/mindspore/python/mindspore/common/tensor.py
index 0b8ee6cd42d..e31ba3dd691 100644
--- a/mindspore/python/mindspore/common/tensor.py
+++ b/mindspore/python/mindspore/common/tensor.py
@@ -3346,7 +3346,7 @@ class Tensor(Tensor_):
         res = tensor_operator_registry.get('reduce_sum')(prod.astype(mstype.float32), -1)
 
         begin = ()
-        for i in range(ndim - 2):
+        for _ in range(ndim - 2):
             begin += (0,)
         last_dim_begin = max(0, -offset)
         begin += (last_dim_begin,)
diff --git a/mindspore/python/mindspore/train/serialization.py b/mindspore/python/mindspore/train/serialization.py
index 4fd3acaa917..3e00a855c2e 100644
--- a/mindspore/python/mindspore/train/serialization.py
+++ b/mindspore/python/mindspore/train/serialization.py
@@ -1449,9 +1449,9 @@ def _merge_param_with_strategy(sliced_data, parameter_name, strategy, is_even):
             tensor_slices_new_inner = []
             for j in range(ele_count):
                 new_tensor = tensor_slices_new[j * tensor_strategy[dim_len - 1 - i]]
-                for l in range(j * tensor_strategy[dim_len - 1 - i] + 1,
+                for k in range(j * tensor_strategy[dim_len - 1 - i] + 1,
                                (j + 1) * tensor_strategy[dim_len - 1 - i]):
-                    new_tensor = np.concatenate((new_tensor, tensor_slices_new[l]), axis=dim_len - 1 - i)
+                    new_tensor = np.concatenate((new_tensor, tensor_slices_new[k]), axis=dim_len - 1 - i)
                 tensor_slices_new_inner.insert(len(tensor_slices_new_inner), np.array(new_tensor))
             tensor_slices_new = tensor_slices_new_inner
         merged_tensor = Tensor(tensor_slices_new[0])