export model

funasr/export/README.md

@@ -0,0 +1,21 @@
+
+environment: ubuntu20.04-py37-torch1.11.0-tf1.15.5-1.2.0
+
+Export onnx files from modelscope
+```python
+from funasr.export.export_model import ASRModelExportParaformer
+
+output_dir = "../export"
+export_model = ASRModelExportParaformer(cache_dir=output_dir, onnx=True)
+export_model.export_from_modelscope('damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
+```
+
+
+Export onnx files from local path
+```python
+from funasr.export.export_model import ASRModelExportParaformer
+
+output_dir = "../export"
+export_model = ASRModelExportParaformer(cache_dir=output_dir, onnx=True)
+export_model.export_from_local('/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
+```

funasr/export/export_model.py

@@ -41,12 +41,25 @@ class ASRModelExportParaformer:
             model,
             self.export_config,
         )
-        if self.onnx:
-            self._export_onnx(model, verbose, export_dir)
+        self._export_onnx(model, verbose, export_dir)
+        # if self.onnx:
+        #     self._export_onnx(model, verbose, export_dir)
+        # else:
+        #     self._export_torchscripts(model, verbose, export_dir)
 
         logging.info("output dir: {}".format(export_dir))
 
 
+    def _export_torchscripts(self, model, verbose, path, enc_size=None):
+        if enc_size:
+            dummy_input = model.get_dummy_inputs(enc_size)
+        else:
+            dummy_input = model.get_dummy_inputs()
+
+        # model_script = torch.jit.script(model)
+        model_script = torch.jit.trace(model, dummy_input)
+        model_script.save(os.path.join(path, f'{model.model_name}.torchscripts'))
+
     def export_from_modelscope(
         self,
         tag_name: str = 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',