Add typing to constructor and transcribe method

faster_whisper/transcribe.py

@@ -1,6 +1,8 @@
 import collections
 import zlib
 
+from typing import BinaryIO, List, Optional, Tuple, Union
+
 import ctranslate2
 import numpy as np
 import tokenizers
@@ -44,12 +46,12 @@ class TranscriptionOptions(
 class WhisperModel:
     def __init__(
         self,
-        model_path,
-        device="auto",
-        device_index=0,
-        compute_type="default",
-        cpu_threads=0,
-        num_workers=1,
+        model_path: str,
+        device: str = "auto",
+        device_index: int = 0,
+        compute_type: str = "default",
+        cpu_threads: int = 0,
+        num_workers: int = 1,
     ):
         """Initializes the Whisper model.
 
@@ -90,20 +92,27 @@ class WhisperModel:
 
     def transcribe(
         self,
-        input_file,
-        language=None,
-        task="transcribe",
-        beam_size=5,
-        best_of=5,
-        patience=1,
-        length_penalty=1,
-        temperature=[0.0, 0.2, 0.4, 0.6, 0.8, 1.0],
-        compression_ratio_threshold=2.4,
-        log_prob_threshold=-1.0,
-        no_speech_threshold=0.6,
-        condition_on_previous_text=True,
-        initial_prompt=None,
-        without_timestamps=False,
+        input_file: Union[str, BinaryIO],
+        language: Optional[str] = None,
+        task: str = "transcribe",
+        beam_size: int = 5,
+        best_of: int = 5,
+        patience: float = 1,
+        length_penalty: float = 1,
+        temperature: Union[float, List[float], Tuple[float, ...]] = [
+            0.0,
+            0.2,
+            0.4,
+            0.6,
+            0.8,
+            1.0,
+        ],
+        compression_ratio_threshold: float = 2.4,
+        log_prob_threshold: float = -1.0,
+        no_speech_threshold: float = 0.6,
+        condition_on_previous_text: bool = True,
+        initial_prompt: Optional[str] = None,
+        without_timestamps: bool = False,
     ):
         """Transcribes an input file.