From 6c1e6e7876c393cf4718edb0653484976eab629f Mon Sep 17 00:00:00 2001
From: KP <109694228@qq.com>
Date: Wed, 8 Dec 2021 15:53:57 +0800
Subject: [PATCH] Update recommended model to cnn14 and argument name in
 __call__.

---
 paddlespeech/cli/cls/infer.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/paddlespeech/cli/cls/infer.py b/paddlespeech/cli/cls/infer.py
index dc976cb4..0b4982d1 100644
--- a/paddlespeech/cli/cls/infer.py
+++ b/paddlespeech/cli/cls/infer.py
@@ -80,7 +80,7 @@ class CLSExecutor(BaseExecutor):
         self.parser.add_argument(
             '--model',
             type=str,
-            default='panns_cnn10',
+            default='panns_cnn14',
             help='Choose model type of cls task.')
         self.parser.add_argument(
             '--config',
@@ -127,8 +127,8 @@ class CLSExecutor(BaseExecutor):
     def _init_from_path(self,
                         model_type: str='panns_cnn14',
                         cfg_path: Optional[os.PathLike]=None,
-                        label_file: Optional[os.PathLike]=None,
-                        ckpt_path: Optional[os.PathLike]=None):
+                        ckpt_path: Optional[os.PathLike]=None,
+                        label_file: Optional[os.PathLike]=None):
         """
             Init model and other resources from a specific path.
         """
@@ -244,15 +244,15 @@ class CLSExecutor(BaseExecutor):
             logger.exception(e)
             return False
 
-    def __call__(self, model_type, cfg_path, label_file, ckpt_path, audio_file,
-                 topk, device):
+    def __call__(self, model, config, ckpt_path, label_file, audio_file, topk,
+                 device):
         """
             Python API to call an executor.
         """
         audio_file = os.path.abspath(audio_file)
         # self._check(audio_file, sample_rate)
         paddle.set_device(device)
-        self._init_from_path(model_type, cfg_path, label_file, ckpt_path)
+        self._init_from_path(model, config, ckpt_path, label_file)
         self.preprocess(audio_file)
         self.infer()
         res = self.postprocess(topk)  # Retrieve result of cls.