From 1cdb3cc28d4d89a576cc06e5cd8eb80da1f3a3aa Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期五, 26 四月 2024 11:27:39 +0800
Subject: [PATCH] Dev gzf exp (#1665)

---
 runtime/python/libtorch/funasr_torch/utils/utils.py |   30 ++++++++++++++----------------
 1 files changed, 14 insertions(+), 16 deletions(-)

diff --git a/runtime/python/libtorch/funasr_torch/utils/utils.py b/runtime/python/libtorch/funasr_torch/utils/utils.py
index 913ddc1..f85d4e9 100644
--- a/runtime/python/libtorch/funasr_torch/utils/utils.py
+++ b/runtime/python/libtorch/funasr_torch/utils/utils.py
@@ -17,24 +17,23 @@
 logger_initialized = {}
 
 
-class TokenIDConverter():
-    def __init__(self, token_list: Union[List, str],
-                 ):
+class TokenIDConverter:
+    def __init__(
+        self,
+        token_list: Union[List, str],
+    ):
 
         self.token_list = token_list
         self.unk_symbol = token_list[-1]
         self.token2id = {v: i for i, v in enumerate(self.token_list)}
         self.unk_id = self.token2id[self.unk_symbol]
 
-
     def get_num_vocabulary_size(self) -> int:
         return len(self.token_list)
 
-    def ids2tokens(self,
-                   integers: Union[np.ndarray, Iterable[int]]) -> List[str]:
+    def ids2tokens(self, integers: Union[np.ndarray, Iterable[int]]) -> List[str]:
         if isinstance(integers, np.ndarray) and integers.ndim != 1:
-            raise TokenIDConverterError(
-                f"Must be 1 dim ndarray, but got {integers.ndim}")
+            raise TokenIDConverterError(f"Must be 1 dim ndarray, but got {integers.ndim}")
         return [self.token_list[i] for i in integers]
 
     def tokens2ids(self, tokens: Iterable[str]) -> List[int]:
@@ -42,7 +41,7 @@
         return [self.token2id.get(i, self.unk_id) for i in tokens]
 
 
-class CharTokenizer():
+class CharTokenizer:
     def __init__(
         self,
         symbol_value: Union[Path, str, Iterable[str]] = None,
@@ -77,7 +76,7 @@
                 if line.startswith(w):
                     if not self.remove_non_linguistic_symbols:
                         tokens.append(line[: len(w)])
-                    line = line[len(w):]
+                    line = line[len(w) :]
                     break
             else:
                 t = line[0]
@@ -100,7 +99,6 @@
         )
 
 
-
 class Hypothesis(NamedTuple):
     """Hypothesis data type."""
 
@@ -120,15 +118,15 @@
 
 def read_yaml(yaml_path: Union[str, Path]) -> Dict:
     if not Path(yaml_path).exists():
-        raise FileExistsError(f'The {yaml_path} does not exist.')
+        raise FileExistsError(f"The {yaml_path} does not exist.")
 
-    with open(str(yaml_path), 'rb') as f:
+    with open(str(yaml_path), "rb") as f:
         data = yaml.load(f, Loader=yaml.Loader)
     return data
 
 
 @functools.lru_cache()
-def get_logger(name='funasr_torch'):
+def get_logger(name="funasr_torch"):
     """Initialize and get a logger by name.
     If the logger has not been initialized, this method will initialize the
     logger by adding one or two handlers, otherwise the initialized logger will
@@ -148,8 +146,8 @@
             return logger
 
     formatter = logging.Formatter(
-        '[%(asctime)s] %(name)s %(levelname)s: %(message)s',
-        datefmt="%Y/%m/%d %H:%M:%S")
+        "[%(asctime)s] %(name)s %(levelname)s: %(message)s", datefmt="%Y/%m/%d %H:%M:%S"
+    )
 
     sh = logging.StreamHandler()
     sh.setFormatter(formatter)

--
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