@@ -62,7 +62,12 @@ def write_video(
6262    audio_options : Optional [Dict [str , Any ]] =  None ,
6363) ->  None :
6464    """ 
65-     Writes a 4d tensor in [T, H, W, C] format in a video file 
65+     Writes a 4d tensor in [T, H, W, C] format in a video file. 
66+ 
67+     This function relies on PyAV (therefore, ultimately FFmpeg) to encode 
68+     videos, you can get more fine-grained control by referring to the other 
69+     options at your disposal within `the FFMpeg wiki 
70+     <http://trac.ffmpeg.org/wiki#Encoding>`_. 
6671
6772    .. warning:: 
6873
@@ -78,12 +83,25 @@ def write_video(
7883            as a uint8 tensor in [T, H, W, C] format 
7984        fps (Number): video frames per second 
8085        video_codec (str): the name of the video codec, i.e. "libx264", "h264", etc. 
81-         options (Dict): dictionary containing options to be passed into the PyAV video stream 
86+         options (Dict): dictionary containing options to be passed into the PyAV video stream. 
87+             The list of options is codec-dependent and can all 
88+             be found from `the FFMpeg wiki <http://trac.ffmpeg.org/wiki#Encoding>`_. 
8289        audio_array (Tensor[C, N]): tensor containing the audio, where C is the number of channels 
8390            and N is the number of samples 
8491        audio_fps (Number): audio sample rate, typically 44100 or 48000 
8592        audio_codec (str): the name of the audio codec, i.e. "mp3", "aac", etc. 
86-         audio_options (Dict): dictionary containing options to be passed into the PyAV audio stream 
93+         audio_options (Dict): dictionary containing options to be passed into the PyAV audio stream. 
94+             The list of options is codec-dependent and can all 
95+             be found from `the FFMpeg wiki <http://trac.ffmpeg.org/wiki#Encoding>`_. 
96+ 
97+     Examples:: 
98+         >>> # Creating libx264 video with CRF 17, for visually lossless footage: 
99+         >>> 
100+         >>> from torchvision.io import write_video 
101+         >>> # 1000 frames of 100x100, 3-channel image. 
102+         >>> vid = torch.randn(1000, 100, 100, 3, dtype = torch.uint8) 
103+         >>> write_video("video.mp4", options = {"crf": "17"}) 
104+ 
87105    """ 
88106    if  not  torch .jit .is_scripting () and  not  torch .jit .is_tracing ():
89107        _log_api_usage_once (write_video )
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