shorten int8-quantized naming (#149)

Author: fengyuentau

models/face_detection_yunet/face_detection_yunet_2022mar-act_int8-wt_int8-quantized.onnx renamed to models/face_detection_yunet/face_detection_yunet_2022mar_int8.onnx

@@ -59,29 +59,30 @@ def __init__(self, model_path, calibration_image_dir, transforms=Compose(), per_
         # data reader
         self.dr = DataReader(self.model_path, self.calibration_image_dir, self.transforms, data_dim)
 
-    def check_opset(self, convert=True):
+    def check_opset(self):
         model = onnx.load(self.model_path)
         if model.opset_import[0].version != 13:
             print('\tmodel opset version: {}. Converting to opset 13'.format(model.opset_import[0].version))
             # convert opset version to 13
             model_opset13 = version_converter.convert_version(model, 13)
             # save converted model
-            output_name = '{}-opset.onnx'.format(self.model_path[:-5])
+            output_name = '{}-opset13.onnx'.format(self.model_path[:-5])
             onnx.save_model(model_opset13, output_name)
             # update model_path for quantization
-            self.model_path = output_name
+            return output_name
+        return self.model_path
 
     def run(self):
         print('Quantizing {}: act_type {}, wt_type {}'.format(self.model_path, self.act_type, self.wt_type))
-        self.check_opset()
-        output_name = '{}-act_{}-wt_{}-quantized.onnx'.format(self.model_path[:-5], self.act_type, self.wt_type)
-        quantize_static(self.model_path, output_name, self.dr,
+        new_model_path = self.check_opset()
+        output_name = '{}_{}.onnx'.format(self.model_path[:-5], self.wt_type)
+        quantize_static(new_model_path, output_name, self.dr,
                         quant_format=QuantFormat.QOperator, # start from onnxruntime==1.11.0, quant_format is set to QuantFormat.QDQ by default, which performs fake quantization
                         per_channel=self.per_channel,
                         weight_type=self.type_dict[self.wt_type],
                         activation_type=self.type_dict[self.act_type])
-        os.remove('augmented_model.onnx')
-        os.remove('{}-opt.onnx'.format(self.model_path[:-5]))
+        if new_model_path != self.model_path:
+            os.remove(new_model_path)
         print('\tQuantized model saved to {}'.format(output_name))
 
 models=dict(
@@ -132,4 +133,3 @@ def run(self):
     for selected_model_name in selected_models:
         q = models[selected_model_name]
         q.run()
-