add the call in infer.py

paddlespeech/cli/executor.py

@@ -14,6 +14,7 @@
 import os
 from abc import ABC
 from abc import abstractmethod
+from typing import List
 from typing import Union
 
 import paddle
@@ -64,3 +65,17 @@ class BaseExecutor(ABC):
             Output postprocess and return human-readable results such as texts and audio files.
         """
         pass
+
+    @abstractmethod
+    def execute(self, argv: List[str]) -> bool:
+        """
+            Command line entry.
+        """
+        pass
+
+    @abstractmethod
+    def __call__(self, *arg, **kwargs):
+        """
+            Python API to call an executor.
+        """
+        pass

paddlespeech/cli/s2t/infer.py

@@ -18,13 +18,14 @@ from typing import List
 from typing import Optional
 from typing import Union
 
-import soundfile
 import paddle
-from paddlespeech.cli.executor import BaseExecutor
+import soundfile
-from paddlespeech.cli.utils import cli_register
+
-from paddlespeech.cli.utils import download_and_decompress
+from ..executor import BaseExecutor
-from paddlespeech.cli.utils import logger
+from ..utils import cli_register
-from paddlespeech.cli.utils import MODEL_HOME
+from ..utils import download_and_decompress
+from ..utils import logger
+from ..utils import MODEL_HOME
 from paddlespeech.s2t.exps.u2.config import get_cfg_defaults
 from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer
 from paddlespeech.s2t.io.collator import SpeechCollator
@@ -55,29 +56,6 @@ model_alias = {
     "wenetspeech": "paddlespeech.s2t.models.u2:U2Model",
 }
 
-pretrain_model_alias = {
-    "ds2_online_zn": [
-        "https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/aishell_ds2_online_cer8.00_release.tar.gz",
-        "", ""
-    ],
-    "ds2_offline_zn": [
-        "https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/ds2.model.tar.gz",
-        "", ""
-    ],
-    "transformer_zn": [
-        "https://paddlespeech.bj.bcebos.com/s2t/aishell/asr1/transformer.model.tar.gz",
-        "", ""
-    ],
-    "conformer_zn": [
-        "https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/conformer.model.tar.gz",
-        "", ""
-    ],
-    "wenetspeech_zn": [
-        "https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/conformer.model.tar.gz",
-        "conf/conformer.yaml", "exp/conformer/checkpoints/wenetspeech"
-    ],
-}
-
 
 @cli_register(
     name='paddlespeech.s2t', description='Speech to text infer command.')
@@ -107,7 +85,6 @@ class S2TExecutor(BaseExecutor):
         self.parser.add_argument(
             '--input',
             type=str,
-            default="../Downloads/asr-demo-1.wav",
             help='Audio file to recognize.')
         self.parser.add_argument(
             '--device',
@@ -155,7 +132,9 @@ class S2TExecutor(BaseExecutor):
             res_path = os.path.dirname(
                 os.path.dirname(os.path.abspath(self.cfg_path)))
 
+        # Enter the path of model root
         os.chdir(res_path)
+
         #Init body.
         parser_args = self.parser_args
         paddle.set_device(parser_args.device)
@@ -206,7 +185,7 @@ class S2TExecutor(BaseExecutor):
         config = self.config
         audio_file = input
         #print("audio_file", audio_file)
-        logger.info("audio_file"+ audio_file)
+        logger.info("audio_file" + audio_file)
 
         self.sr = config.collator.target_sample_rate
 
@@ -307,7 +286,11 @@ class S2TExecutor(BaseExecutor):
         return self.result_transcripts
 
     def execute(self, argv: List[str]) -> bool:
+        """
+            Command line entry.
+        """
         self.parser_args = self.parser.parse_args(argv)
+        print(self.parser_args)
 
         model = self.parser_args.model
         lang = self.parser_args.lang
@@ -317,17 +300,20 @@ class S2TExecutor(BaseExecutor):
         device = self.parser_args.device
 
         try:
-            self._init_from_path(model, lang, config, ckpt_path)
+            res = self(model, lang, config, ckpt_path, audio_file, device)
-            self.preprocess(audio_file)
+            print(res)
-            self.infer()
-            res = self.postprocess()  # Retrieve result of s2t.
-            logger.info(res)
             return True
         except Exception as e:
             print(e)
             return False
 
+    def __call__(self, model, lang, config, ckpt_path, audio_file, device):
+        """
+            Python API to call an executor.
+        """
+        self._init_from_path(model, lang, config, ckpt_path)
+        self.preprocess(audio_file)
+        self.infer()
+        res = self.postprocess()  # Retrieve result of s2t.
 
-if __name__ == "__main__":
+        return res
-    exe = S2TExecutor()
-    exe.execute('')