From d46a542fae26009eee16204a81903862cb4dba73 Mon Sep 17 00:00:00 2001
From: aky15 <ankeyu.aky@11.17.44.249>
Date: 星期一, 10 四月 2023 16:02:41 +0800
Subject: [PATCH] Merge branch 'main' into dev_aky

---
 funasr/export/export_model.py |   64 ++++++++++++++++++++++++-------
 1 files changed, 49 insertions(+), 15 deletions(-)

diff --git a/funasr/export/export_model.py b/funasr/export/export_model.py
index f6ba616..b69eeee 100644
--- a/funasr/export/export_model.py
+++ b/funasr/export/export_model.py
@@ -14,11 +14,12 @@
 # torch_version = float(".".join(torch.__version__.split(".")[:2]))
 # assert torch_version > 1.9
 
-class ASRModelExportParaformer:
+class ModelExport:
     def __init__(
         self,
         cache_dir: Union[Path, str] = None,
         onnx: bool = True,
+        device: str = "cpu",
         quant: bool = True,
         fallback_num: int = 0,
         audio_in: str = None,
@@ -36,6 +37,7 @@
         )
         print("output dir: {}".format(self.cache_dir))
         self.onnx = onnx
+        self.device = device
         self.quant = quant
         self.fallback_num = fallback_num
         self.frontend = None
@@ -112,6 +114,10 @@
         else:
             dummy_input = model.get_dummy_inputs()
 
+        if self.device == 'cuda':
+            model = model.cuda()
+            dummy_input = tuple([i.cuda() for i in dummy_input])
+
         # 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'))
@@ -161,31 +167,57 @@
     
     def export(self,
                tag_name: str = 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
-               mode: str = 'paraformer',
+               mode: str = None,
                ):
         
         model_dir = tag_name
-        if model_dir.startswith('damo/'):
+        if model_dir.startswith('damo'):
             from modelscope.hub.snapshot_download import snapshot_download
             model_dir = snapshot_download(model_dir, cache_dir=self.cache_dir)
-        asr_train_config = os.path.join(model_dir, 'config.yaml')
-        asr_model_file = os.path.join(model_dir, 'model.pb')
-        cmvn_file = os.path.join(model_dir, 'am.mvn')
-        json_file = os.path.join(model_dir, 'configuration.json')
+
         if mode is None:
             import json
+            json_file = os.path.join(model_dir, 'configuration.json')
             with open(json_file, 'r') as f:
                 config_data = json.load(f)
-                mode = config_data['model']['model_config']['mode']
+                if config_data['task'] == "punctuation":
+                    mode = config_data['model']['punc_model_config']['mode']
+                else:
+                    mode = config_data['model']['model_config']['mode']
         if mode.startswith('paraformer'):
             from funasr.tasks.asr import ASRTaskParaformer as ASRTask
-        elif mode.startswith('uniasr'):
-            from funasr.tasks.asr import ASRTaskUniASR as ASRTask
+            config = os.path.join(model_dir, 'config.yaml')
+            model_file = os.path.join(model_dir, 'model.pb')
+            cmvn_file = os.path.join(model_dir, 'am.mvn')
+            model, asr_train_args = ASRTask.build_model_from_file(
+                config, model_file, cmvn_file, 'cpu'
+            )
+            self.frontend = model.frontend
+        elif mode.startswith('offline'):
+            from funasr.tasks.vad import VADTask
+            config = os.path.join(model_dir, 'vad.yaml')
+            model_file = os.path.join(model_dir, 'vad.pb')
+            cmvn_file = os.path.join(model_dir, 'vad.mvn')
             
-        model, asr_train_args = ASRTask.build_model_from_file(
-            asr_train_config, asr_model_file, cmvn_file, 'cpu'
-        )
-        self.frontend = model.frontend
+            model, vad_infer_args = VADTask.build_model_from_file(
+                config, model_file, cmvn_file=cmvn_file, device='cpu'
+            )
+            self.export_config["feats_dim"] = 400
+            self.frontend = model.frontend
+        elif mode.startswith('punc'):
+            from funasr.tasks.punctuation import PunctuationTask as PUNCTask
+            punc_train_config = os.path.join(model_dir, 'config.yaml')
+            punc_model_file = os.path.join(model_dir, 'punc.pb')
+            model, punc_train_args = PUNCTask.build_model_from_file(
+                punc_train_config, punc_model_file, 'cpu'
+            )
+        elif mode.startswith('punc_VadRealtime'):
+            from funasr.tasks.punctuation import PunctuationTask as PUNCTask
+            punc_train_config = os.path.join(model_dir, 'config.yaml')
+            punc_model_file = os.path.join(model_dir, 'punc.pb')
+            model, punc_train_args = PUNCTask.build_model_from_file(
+                punc_train_config, punc_model_file, 'cpu'
+            )
         self._export(model, tag_name)
             
 
@@ -234,15 +266,17 @@
     parser.add_argument('--model-name', type=str, required=True)
     parser.add_argument('--export-dir', type=str, required=True)
     parser.add_argument('--type', type=str, default='onnx', help='["onnx", "torch"]')
+    parser.add_argument('--device', type=str, default='cpu', help='["cpu", "cuda"]')
     parser.add_argument('--quantize', type=str2bool, default=False, help='export quantized model')
     parser.add_argument('--fallback-num', type=int, default=0, help='amp fallback number')
     parser.add_argument('--audio_in', type=str, default=None, help='["wav", "wav.scp"]')
     parser.add_argument('--calib_num', type=int, default=200, help='calib max num')
     args = parser.parse_args()
 
-    export_model = ASRModelExportParaformer(
+    export_model = ModelExport(
         cache_dir=args.export_dir,
         onnx=args.type == 'onnx',
+        device=args.device,
         quant=args.quantize,
         fallback_num=args.fallback_num,
         audio_in=args.audio_in,

--
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