add export file name check

mindspore/_checkparam.py

@@ -427,6 +427,16 @@ class Validator:
                 target, prim_name, reg, flag))
         return True
 
+    @staticmethod
+    def check_file_name_by_regular(target, reg=None, flag=re.ASCII, prim_name=None):
+        if reg is None:
+            reg = r"^[0-9a-zA-Z\_\.\/\\]*$"
+        if re.match(reg, target, flag) is None:
+            prim_name = f'in `{prim_name}`' if prim_name else ""
+            raise ValueError("'{}' {} is illegal, it should be match regular'{}' by flags'{}'".format(
+                target, prim_name, reg, flag))
+        return True
+
     @staticmethod
     def check_pad_value_by_mode(pad_mode, padding, prim_name):
         """Validates value of padding according to pad_mode"""

mindspore/train/serialization.py

@@ -530,6 +530,7 @@ def export(net, *inputs, file_name, file_format='AIR', **kwargs):
     if not isinstance(file_name, str):
         raise ValueError("Args file_name {} must be string, please check it".format(file_name))
 
+    Validator.check_file_name_by_regular(file_name)
     net = _quant_export(net, *inputs, file_format=file_format, **kwargs)
     _export(net, file_name, file_format, *inputs)
 
@@ -552,14 +553,14 @@ def _export(net, file_name, file_format, *inputs):
     is_dump_onnx_in_training = net.training and file_format == 'ONNX'
     if is_dump_onnx_in_training:
         net.set_train(mode=False)
-    # export model
+
     net.init_parameters_data()
     if file_format == 'AIR':
         phase_name = 'export.air'
         graph_id, _ = _executor.compile(net, *inputs, phase=phase_name)
         file_name += ".air"
         _executor.export(file_name, graph_id)
-    elif file_format == 'ONNX':  # file_format is 'ONNX'
+    elif file_format == 'ONNX':
         phase_name = 'export.onnx'
         graph_id, _ = _executor.compile(net, *inputs, phase=phase_name, do_convert=False)
         onnx_stream = _executor._get_func_graph_proto(net, graph_id)
@@ -567,7 +568,7 @@ def _export(net, file_name, file_format, *inputs):
         with open(file_name, 'wb') as f:
             os.chmod(file_name, stat.S_IWUSR | stat.S_IRUSR)
             f.write(onnx_stream)
-    elif file_format == 'MINDIR':  # file_format is 'MINDIR'
+    elif file_format == 'MINDIR':
         phase_name = 'export.mindir'
         graph_id, _ = _executor.compile(net, *inputs, phase=phase_name, do_convert=False)
         onnx_stream = _executor._get_func_graph_proto(net, graph_id, 'mind_ir')
@@ -575,7 +576,7 @@ def _export(net, file_name, file_format, *inputs):
         with open(file_name, 'wb') as f:
             os.chmod(file_name, stat.S_IWUSR | stat.S_IRUSR)
             f.write(onnx_stream)
-    # restore network training mode
+
     if is_dump_onnx_in_training:
         net.set_train(mode=True)