Accept 'auto' in num_ffmpeg_threads

src/torchcodec/decoders/_video_decoder.py

@@ -43,11 +43,11 @@ class VideoDecoder:
                 cheap no-copy operation that allows these frames to be
                 transformed using the `torchvision transforms
                 <https://pytorch.org/vision/stable/transforms.html>`_.
-        num_ffmpeg_threads (int or None, optional): The number of threads to use for decoding.
+        num_ffmpeg_threads (int or str, optional): The number of threads to use for decoding.
             Use 1 for single-threaded decoding which may be best if you are running multiple
             instances of ``VideoDecoder`` in parallel. Use a higher number for multi-threaded
             decoding which is best if you are running a single instance of ``VideoDecoder``.
-            ``None`` is equivalent to passing 0 and lets FFmpeg automatically decide.
+            "auto" is equivalent to passing 0 and lets FFmpeg automatically decide.
             Default: 1.
         device (str or torch.device, optional): The device to use for decoding. Default: "cpu".
 
@@ -65,7 +65,7 @@ def __init__(
         *,
         stream_index: Optional[int] = None,
         dimension_order: Literal["NCHW", "NHWC"] = "NCHW",
-        num_ffmpeg_threads: Optional[int] = 1,
+        num_ffmpeg_threads: Union[int, str] = 1,
         device: Optional[Union[str, device]] = "cpu",
     ):
         if isinstance(source, str):
@@ -89,6 +89,14 @@ def __init__(
                 f"Supported values are {', '.join(allowed_dimension_orders)}."
             )
 
+        if isinstance(num_ffmpeg_threads, str):
+            if num_ffmpeg_threads != "auto":
+                raise ValueError(
+                    "num_ffmpeg_threads should be 'auto' when it's a string. "
+                    f"Got {num_ffmpeg_threads}"
+                )
+            num_ffmpeg_threads = 0
+
         core.scan_all_streams_to_update_metadata(self._decoder)
         core.add_video_stream(
             self._decoder,