20240131在WIN10下配置whisper

news2024/11/13 14:27:44

20240131在WIN10下配置whisper
2024/1/31 18:25


首先你要有一张NVIDIA的显卡,比如我用的PDD拼多多的二手GTX1080显卡。【并且极其可能是矿卡!】800¥
2、请正确安装好NVIDIA最新的545版本的驱动程序和CUDA。
2、安装Torch
3、配置whisper


https://blog.csdn.net/m0_52156129/article/details/129263703
如何在你的电脑上完成whisper的简单部署

【根据你的位置或者网速,你下载的速度可能会很慢或者中断,重来即可!^_】
https://pytorch.org/get-started/locally/
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121

pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu118
pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu121


START LOCALLY
Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, builds that are generated nightly. Please ensure that you have met the prerequisites below (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies. You can also install previous versions of PyTorch. Note that LibTorch is only available for C++.

NOTE: Latest PyTorch requires Python 3.8 or later. For more details, see Python section below.


C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2023 NVIDIA Corporation
Built on Tue_Jun_13_19:42:34_Pacific_Daylight_Time_2023
Cuda compilation tools, release 12.2, V12.2.91
Build cuda_12.2.r12.2/compiler.32965470_0

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu121
C:\Users\wb491>pip install -U openai-whisper
C:\Users\wb491>whisper -h
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>whisper Utopia.AU.S01E04.Onwards.and.Upwards.1080p.WEB-DL.AAC2.0.H.264-ABH.mkv --model small --language Chinese


LOG:

Microsoft Windows [版本 10.0.19045.3930]
(c) Microsoft Corporation。保留所有权利。

C:\Users\wb491>pip install -U openai-whisper
Collecting openai-whisper
  Downloading openai-whisper-20231117.tar.gz (798 kB)
     ---------------------------------------- 798.6/798.6 kB 2.2 MB/s eta 0:00:00
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Preparing metadata (pyproject.toml) ... done
Collecting numba (from openai-whisper)
  Downloading numba-0.58.1-cp38-cp38-win_amd64.whl.metadata (2.8 kB)
Requirement already satisfied: numpy in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from openai-whisper) (1.24.4)
Requirement already satisfied: torch in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from openai-whisper) (1.8.1)
Collecting tqdm (from openai-whisper)
  Downloading tqdm-4.66.1-py3-none-any.whl.metadata (57 kB)
     ---------------------------------------- 57.6/57.6 kB ? eta 0:00:00
Collecting more-itertools (from openai-whisper)
  Downloading more_itertools-10.2.0-py3-none-any.whl.metadata (34 kB)
Collecting tiktoken (from openai-whisper)
  Downloading tiktoken-0.5.2-cp38-cp38-win_amd64.whl.metadata (6.8 kB)
Collecting llvmlite<0.42,>=0.41.0dev0 (from numba->openai-whisper)
  Downloading llvmlite-0.41.1-cp38-cp38-win_amd64.whl.metadata (4.9 kB)
Collecting importlib-metadata (from numba->openai-whisper)
  Downloading importlib_metadata-7.0.1-py3-none-any.whl.metadata (4.9 kB)
Collecting regex>=2022.1.18 (from tiktoken->openai-whisper)
  Downloading regex-2023.12.25-cp38-cp38-win_amd64.whl.metadata (41 kB)
     ---------------------------------------- 42.0/42.0 kB ? eta 0:00:00
Collecting requests>=2.26.0 (from tiktoken->openai-whisper)
  Downloading requests-2.31.0-py3-none-any.whl.metadata (4.6 kB)
Requirement already satisfied: typing-extensions in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torch->openai-whisper) (4.9.0)
Collecting colorama (from tqdm->openai-whisper)
  Downloading colorama-0.4.6-py2.py3-none-any.whl (25 kB)
Collecting charset-normalizer<4,>=2 (from requests>=2.26.0->tiktoken->openai-whisper)
  Downloading charset_normalizer-3.3.2-cp38-cp38-win_amd64.whl.metadata (34 kB)
Collecting idna<4,>=2.5 (from requests>=2.26.0->tiktoken->openai-whisper)
  Downloading idna-3.6-py3-none-any.whl.metadata (9.9 kB)
Collecting urllib3<3,>=1.21.1 (from requests>=2.26.0->tiktoken->openai-whisper)
  Downloading urllib3-2.2.0-py3-none-any.whl.metadata (6.4 kB)
Collecting certifi>=2017.4.17 (from requests>=2.26.0->tiktoken->openai-whisper)
  Downloading certifi-2023.11.17-py3-none-any.whl.metadata (2.2 kB)
Collecting zipp>=0.5 (from importlib-metadata->numba->openai-whisper)
  Downloading zipp-3.17.0-py3-none-any.whl.metadata (3.7 kB)
Downloading more_itertools-10.2.0-py3-none-any.whl (57 kB)
   ---------------------------------------- 57.0/57.0 kB 2.9 MB/s eta 0:00:00
Downloading numba-0.58.1-cp38-cp38-win_amd64.whl (2.6 MB)
   ---------------------------------------- 2.6/2.6 MB 15.2 MB/s eta 0:00:00
Downloading tiktoken-0.5.2-cp38-cp38-win_amd64.whl (786 kB)
   ---------------------------------------- 786.4/786.4 kB 48.5 MB/s eta 0:00:00
Downloading tqdm-4.66.1-py3-none-any.whl (78 kB)
   ---------------------------------------- 78.3/78.3 kB 4.3 MB/s eta 0:00:00
Downloading llvmlite-0.41.1-cp38-cp38-win_amd64.whl (28.1 MB)
   ---------------------------------------- 28.1/28.1 MB 40.9 MB/s eta 0:00:00
Downloading regex-2023.12.25-cp38-cp38-win_amd64.whl (269 kB)
   ---------------------------------------- 269.5/269.5 kB 16.2 MB/s eta 0:00:00
Downloading requests-2.31.0-py3-none-any.whl (62 kB)
   ---------------------------------------- 62.6/62.6 kB ? eta 0:00:00
Downloading importlib_metadata-7.0.1-py3-none-any.whl (23 kB)
Downloading certifi-2023.11.17-py3-none-any.whl (162 kB)
   ---------------------------------------- 162.5/162.5 kB 10.2 MB/s eta 0:00:00
Downloading charset_normalizer-3.3.2-cp38-cp38-win_amd64.whl (99 kB)
   ---------------------------------------- 99.6/99.6 kB ? eta 0:00:00
Downloading idna-3.6-py3-none-any.whl (61 kB)
   ---------------------------------------- 61.6/61.6 kB 3.2 MB/s eta 0:00:00
Downloading urllib3-2.2.0-py3-none-any.whl (120 kB)
   ---------------------------------------- 120.9/120.9 kB 7.4 MB/s eta 0:00:00
Downloading zipp-3.17.0-py3-none-any.whl (7.4 kB)
Building wheels for collected packages: openai-whisper
  Building wheel for openai-whisper (pyproject.toml) ... done
  Created wheel for openai-whisper: filename=openai_whisper-20231117-py3-none-any.whl size=801375 sha256=0b59001c7b0cf9b553836246ea71e0c10b01936089a7a2ee3e5c031eba9277df
  Stored in directory: c:\users\wb491\appdata\local\pip\cache\wheels\d2\33\5e\ab7fe45178ca9489707f18a89fd9a22611b656edf804b3cf53
Successfully built openai-whisper
Installing collected packages: zipp, urllib3, regex, more-itertools, llvmlite, idna, colorama, charset-normalizer, certifi, tqdm, requests, importlib-metadata, tiktoken, numba, openai-whisper
Successfully installed certifi-2023.11.17 charset-normalizer-3.3.2 colorama-0.4.6 idna-3.6 importlib-metadata-7.0.1 llvmlite-0.41.1 more-itertools-10.2.0 numba-0.58.1 openai-whisper-20231117 regex-2023.12.25 requests-2.31.0 tiktoken-0.5.2 tqdm-4.66.1 urllib3-2.2.0 zipp-3.17.0

C:\Users\wb491>
C:\Users\wb491>
C:\Users\wb491>whisper -h
usage: whisper [-h] [--model MODEL] [--model_dir MODEL_DIR] [--device DEVICE] [--output_dir OUTPUT_DIR] [--output_format {txt,vtt,srt,tsv,json,all}] [--verbose VERBOSE] [--task {transcribe,translate}]
               [--language {af,am,ar,as,az,ba,be,bg,bn,bo,br,bs,ca,cs,cy,da,de,el,en,es,et,eu,fa,fi,fo,fr,gl,gu,ha,haw,he,hi,hr,ht,hu,hy,id,is,it,ja,jw,ka,kk,km,kn,ko,la,lb,ln,lo,lt,lv,mg,mi,mk,ml,mn,mr,ms,mt,my,ne,nl,nn,no,oc,pa,pl,ps,pt,ro,ru,sa,sd,si,sk,sl,sn,so,sq,sr,su,sv,sw,ta,te,tg,th,tk,tl,tr,tt,uk,ur,uz,vi,yi,yo,yue,zh,Afrikaans,Albanian,Amharic,Arabic,Armenian,Assamese,Azerbaijani,Bashkir,Basque,Belarusian,Bengali,Bosnian,Breton,Bulgarian,Burmese,Cantonese,Castilian,Catalan,Chinese,Croatian,Czech,Danish,Dutch,English,Estonian,Faroese,Finnish,Flemish,French,Galician,Georgian,German,Greek,Gujarati,Haitian,Haitian Creole,Hausa,Hawaiian,Hebrew,Hindi,Hungarian,Icelandic,Indonesian,Italian,Japanese,Javanese,Kannada,Kazakh,Khmer,Korean,Lao,Latin,Latvian,Letzeburgesch,Lingala,Lithuanian,Luxembourgish,Macedonian,Malagasy,Malay,Malayalam,Maltese,Mandarin,Maori,Marathi,Moldavian,Moldovan,Mongolian,Myanmar,Nepali,Norwegian,Nynorsk,Occitan,Panjabi,Pashto,Persian,Polish,Portuguese,Punjabi,Pushto,Romanian,Russian,Sanskrit,Serbian,Shona,Sindhi,Sinhala,Sinhalese,Slovak,Slovenian,Somali,Spanish,Sundanese,Swahili,Swedish,Tagalog,Tajik,Tamil,Tatar,Telugu,Thai,Tibetan,Turkish,Turkmen,Ukrainian,Urdu,Uzbek,Valencian,Vietnamese,Welsh,Yiddish,Yoruba}]
               [--temperature TEMPERATURE] [--best_of BEST_OF] [--beam_size BEAM_SIZE] [--patience PATIENCE] [--length_penalty LENGTH_PENALTY] [--suppress_tokens SUPPRESS_TOKENS] [--initial_prompt INITIAL_PROMPT]
               [--condition_on_previous_text CONDITION_ON_PREVIOUS_TEXT] [--fp16 FP16] [--temperature_increment_on_fallback TEMPERATURE_INCREMENT_ON_FALLBACK] [--compression_ratio_threshold COMPRESSION_RATIO_THRESHOLD]
               [--logprob_threshold LOGPROB_THRESHOLD] [--no_speech_threshold NO_SPEECH_THRESHOLD] [--word_timestamps WORD_TIMESTAMPS] [--prepend_punctuations PREPEND_PUNCTUATIONS] [--append_punctuations APPEND_PUNCTUATIONS]
               [--highlight_words HIGHLIGHT_WORDS] [--max_line_width MAX_LINE_WIDTH] [--max_line_count MAX_LINE_COUNT] [--max_words_per_line MAX_WORDS_PER_LINE] [--threads THREADS]
               audio [audio ...]

positional arguments:
  audio                 audio file(s) to transcribe

optional arguments:
  -h, --help            show this help message and exit
  --model MODEL         name of the Whisper model to use (default: small)
  --model_dir MODEL_DIR
                        the path to save model files; uses ~/.cache/whisper by default (default: None)
  --device DEVICE       device to use for PyTorch inference (default: cpu)
  --output_dir OUTPUT_DIR, -o OUTPUT_DIR
                        directory to save the outputs (default: .)
  --output_format {txt,vtt,srt,tsv,json,all}, -f {txt,vtt,srt,tsv,json,all}
                        format of the output file; if not specified, all available formats will be produced (default: all)
  --verbose VERBOSE     whether to print out the progress and debug messages (default: True)
  --task {transcribe,translate}
                        whether to perform X->X speech recognition ('transcribe') or X->English translation ('translate') (default: transcribe)
  --language {af,am,ar,as,az,ba,be,bg,bn,bo,br,bs,ca,cs,cy,da,de,el,en,es,et,eu,fa,fi,fo,fr,gl,gu,ha,haw,he,hi,hr,ht,hu,hy,id,is,it,ja,jw,ka,kk,km,kn,ko,la,lb,ln,lo,lt,lv,mg,mi,mk,ml,mn,mr,ms,mt,my,ne,nl,nn,no,oc,pa,pl,ps,pt,ro,ru,sa,sd,si,sk,sl,sn,so,sq,sr,su,sv,sw,ta,te,tg,th,tk,tl,tr,tt,uk,ur,uz,vi,yi,yo,yue,zh,Afrikaans,Albanian,Amharic,Arabic,Armenian,Assamese,Azerbaijani,Bashkir,Basque,Belarusian,Bengali,Bosnian,Breton,Bulgarian,Burmese,Cantonese,Castilian,Catalan,Chinese,Croatian,Czech,Danish,Dutch,English,Estonian,Faroese,Finnish,Flemish,French,Galician,Georgian,German,Greek,Gujarati,Haitian,Haitian Creole,Hausa,Hawaiian,Hebrew,Hindi,Hungarian,Icelandic,Indonesian,Italian,Japanese,Javanese,Kannada,Kazakh,Khmer,Korean,Lao,Latin,Latvian,Letzeburgesch,Lingala,Lithuanian,Luxembourgish,Macedonian,Malagasy,Malay,Malayalam,Maltese,Mandarin,Maori,Marathi,Moldavian,Moldovan,Mongolian,Myanmar,Nepali,Norwegian,Nynorsk,Occitan,Panjabi,Pashto,Persian,Polish,Portuguese,Punjabi,Pushto,Romanian,Russian,Sanskrit,Serbian,Shona,Sindhi,Sinhala,Sinhalese,Slovak,Slovenian,Somali,Spanish,Sundanese,Swahili,Swedish,Tagalog,Tajik,Tamil,Tatar,Telugu,Thai,Tibetan,Turkish,Turkmen,Ukrainian,Urdu,Uzbek,Valencian,Vietnamese,Welsh,Yiddish,Yoruba}
                        language spoken in the audio, specify None to perform language detection (default: None)
  --temperature TEMPERATURE
                        temperature to use for sampling (default: 0)
  --best_of BEST_OF     number of candidates when sampling with non-zero temperature (default: 5)
  --beam_size BEAM_SIZE
                        number of beams in beam search, only applicable when temperature is zero (default: 5)
  --patience PATIENCE   optional patience value to use in beam decoding, as in https://arxiv.org/abs/2204.05424, the default (1.0) is equivalent to conventional beam search (default: None)
  --length_penalty LENGTH_PENALTY
                        optional token length penalty coefficient (alpha) as in https://arxiv.org/abs/1609.08144, uses simple length normalization by default (default: None)
  --suppress_tokens SUPPRESS_TOKENS
                        comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations (default: -1)
  --initial_prompt INITIAL_PROMPT
                        optional text to provide as a prompt for the first window. (default: None)
  --condition_on_previous_text CONDITION_ON_PREVIOUS_TEXT
                        if True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop
                        (default: True)
  --fp16 FP16           whether to perform inference in fp16; True by default (default: True)
  --temperature_increment_on_fallback TEMPERATURE_INCREMENT_ON_FALLBACK
                        temperature to increase when falling back when the decoding fails to meet either of the thresholds below (default: 0.2)
  --compression_ratio_threshold COMPRESSION_RATIO_THRESHOLD
                        if the gzip compression ratio is higher than this value, treat the decoding as failed (default: 2.4)
  --logprob_threshold LOGPROB_THRESHOLD
                        if the average log probability is lower than this value, treat the decoding as failed (default: -1.0)
  --no_speech_threshold NO_SPEECH_THRESHOLD
                        if the probability of the <|nospeech|> token is higher than this value AND the decoding has failed due to `logprob_threshold`, consider the segment as silence (default: 0.6)
  --word_timestamps WORD_TIMESTAMPS
                        (experimental) extract word-level timestamps and refine the results based on them (default: False)
  --prepend_punctuations PREPEND_PUNCTUATIONS
                        if word_timestamps is True, merge these punctuation symbols with the next word (default: "'“¿([{-)
  --append_punctuations APPEND_PUNCTUATIONS
                        if word_timestamps is True, merge these punctuation symbols with the previous word (default: "'.。,,!!??::”)]}、)
  --highlight_words HIGHLIGHT_WORDS
                        (requires --word_timestamps True) underline each word as it is spoken in srt and vtt (default: False)
  --max_line_width MAX_LINE_WIDTH
                        (requires --word_timestamps True) the maximum number of characters in a line before breaking the line (default: None)
  --max_line_count MAX_LINE_COUNT
                        (requires --word_timestamps True) the maximum number of lines in a segment (default: None)
  --max_words_per_line MAX_WORDS_PER_LINE
                        (requires --word_timestamps True, no effect with --max_line_width) the maximum number of words in a segment (default: None)
  --threads THREADS     number of threads used by torch for CPU inference; supercedes MKL_NUM_THREADS/OMP_NUM_THREADS (default: 0)

C:\Users\wb491>cd C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>dir
 驱动器 C 中的卷是 WIN10
 卷的序列号是 9273-D6A8

 C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB 的目录

2024/01/31  00:02    <DIR>          .
2024/01/31  00:02    <DIR>          ..
2024/01/30  22:50           111,189 04.srt
2024/01/30  22:50           113,309 05.srt
2024/01/30  22:51           107,750 06.srt
2024/01/30  22:51           101,014 07.srt
2024/01/30  22:51           111,620 08.srt
2024/01/30  19:28           124,714 161426695262720.7z
2024/01/30  21:12           447,089 2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB 2.7z
2024/01/30  22:45           287,154 4[内置字幕]字幕1+台湾.ssa
2024/01/30  22:46           281,620 5[内置字幕]字幕1+台湾.ssa
2024/01/30  22:46           276,722 6[内置字幕]字幕1 (1)+台湾.ssa
2024/01/30  22:47           255,284 7[内置字幕]字幕1 (2)+台湾.ssa
2024/01/30  22:48           293,888 8[内置字幕]字幕1 (3)+台湾.ssa
2024/01/30  18:43                31 RARBG.txt
2024/01/30  18:43     1,082,562,938 Utopia.AU.S01E04.Onwards.and.Upwards.1080p.WEB-DL.AAC2.0.H.264-ABH.mkv
2024/01/30  18:43     1,068,829,082 Utopia.AU.S01E05.Arts.and.Minds.1080p.WEB-DL.AAC2.0.H.264-ABH.mkv
2024/01/30  18:43     1,065,442,786 Utopia.AU.S01E06.Then.We.Can.Build.It.1080p.WEB-DL.AAC2.0.H.264-ABH.mkv
2024/01/30  18:43     1,041,821,540 Utopia.AU.S01E07.The.First.Project.1080p.WEB-DL.AAC2.0.H.264-ABH.mkv
2024/01/30  18:43     1,065,084,003 Utopia.AU.S01E08.The.Whole.Enchilada.1080p.WEB-DL.AAC2.0.H.264-ABH.mkv
              18 个文件  5,326,251,733 字节
               2 个目录 260,072,566,784 可用字节

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>whisper Utopia.AU.S01E04.Onwards.and.Upwards.1080p.WEB-DL.AAC2.0.H.264-ABH.mkv --model small --language Chinese
100%|███████████████████████████████████████| 461M/461M [00:41<00:00, 11.5MiB/s]
c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\transcribe.py:115: UserWarning: FP16 is not supported on CPU; using FP32 instead
  warnings.warn("FP16 is not supported on CPU; using FP32 instead")
Traceback (most recent call last):
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\runpy.py", line 192, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "C:\Users\wb491\AppData\Local\Programs\Python\Python38\Scripts\whisper.exe\__main__.py", line 7, in <module>
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\transcribe.py", line 478, in cli
    result = transcribe(model, audio_path, temperature=temperature, **args)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\transcribe.py", line 240, in transcribe
    result: DecodingResult = decode_with_fallback(mel_segment)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\transcribe.py", line 170, in decode_with_fallback
    decode_result = model.decode(segment, options)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\decoding.py", line 824, in decode
    result = DecodingTask(model, options).run(mel)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\decoding.py", line 737, in run
    tokens, sum_logprobs, no_speech_probs = self._main_loop(audio_features, tokens)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\decoding.py", line 687, in _main_loop
    logits = self.inference.logits(tokens, audio_features)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\decoding.py", line 163, in logits
    return self.model.decoder(tokens, audio_features, kv_cache=self.kv_cache)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\model.py", line 211, in forward
    x = block(x, xa, mask=self.mask, kv_cache=kv_cache)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\model.py", line 138, in forward
    x = x + self.cross_attn(self.cross_attn_ln(x), xa, kv_cache=kv_cache)[0]
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\model.py", line 90, in forward
    wv, qk = self.qkv_attention(q, k, v, mask)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\model.py", line 108, in qkv_attention
    return (w @ v).permute(0, 2, 1, 3).flatten(start_dim=2), qk.detach()
KeyboardInterrupt

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>nvcc --versuib
nvcc fatal   : Unknown option '--versuib'

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2023 NVIDIA Corporation
Built on Tue_Jun_13_19:42:34_Pacific_Daylight_Time_2023
Cuda compilation tools, release 12.2, V12.2.91
Build cuda_12.2.r12.2/compiler.32965470_0

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu121
Looking in indexes: https://download.pytorch.org/whl/nightly/cu121
Requirement already satisfied: torch in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (1.8.1)
Collecting torchvision
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240130%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
     ---------------------------------------- 5.8/5.8 MB 10.3 MB/s eta 0:00:00
Collecting torchaudio
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240130%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
     ---------------------------------------- 4.1/4.1 MB 43.2 MB/s eta 0:00:00
Requirement already satisfied: typing-extensions in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torch) (4.9.0)
Requirement already satisfied: numpy in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torch) (1.24.4)
Requirement already satisfied: requests in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torchvision) (2.31.0)
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240130%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
     ---------------------------------------- 2.4/2.4 GB 2.9 MB/s eta 0:00:00
Collecting pillow!=8.3.*,>=5.3.0 (from torchvision)
  Downloading https://download.pytorch.org/whl/nightly/Pillow-9.3.0-cp38-cp38-win_amd64.whl (2.5 MB)
     ---------------------------------------- 2.5/2.5 MB 437.3 kB/s eta 0:00:00
Collecting filelock (from torch)
  Downloading https://download.pytorch.org/whl/nightly/filelock-3.9.0-py3-none-any.whl (9.7 kB)
Collecting sympy (from torch)
  Downloading https://download.pytorch.org/whl/nightly/sympy-1.11.1-py3-none-any.whl (6.5 MB)
     ---------------------------------------- 6.5/6.5 MB 51.7 MB/s eta 0:00:00
Collecting networkx (from torch)
  Downloading https://download.pytorch.org/whl/nightly/networkx-3.0rc1-py3-none-any.whl (2.0 MB)
     ---------------------------------------- 2.0/2.0 MB 43.7 MB/s eta 0:00:00
Collecting jinja2 (from torch)
  Downloading https://download.pytorch.org/whl/nightly/Jinja2-3.1.2-py3-none-any.whl (133 kB)
     ---------------------------------------- 133.1/133.1 kB 8.2 MB/s eta 0:00:00
Collecting fsspec (from torch)
  Downloading https://download.pytorch.org/whl/nightly/fsspec-2023.4.0-py3-none-any.whl (153 kB)
     ---------------------------------------- 154.0/154.0 kB ? eta 0:00:00
INFO: pip is looking at multiple versions of torch to determine which version is compatible with other requirements. This could take a while.
Collecting torchvision
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240129%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
     ---------------------------------------- 5.8/5.8 MB 4.3 MB/s eta 0:00:00
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240129%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
     ---------------------------------------- 2.4/2.4 GB 2.7 MB/s eta 0:00:00
Collecting torchvision
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240128%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
     ---------------------------------------- 5.8/5.8 MB 531.9 kB/s eta 0:00:00
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240128%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
     ---------------------------------------- 2.4/2.4 GB 2.8 MB/s eta 0:00:00
Collecting torchvision
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240127%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
     ---------------------------------------- 5.8/5.8 MB 4.2 MB/s eta 0:00:00
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240127%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
     --------- ------------------------------ 0.6/2.4 GB 459.1 kB/s eta 1:06:27
ERROR: Exception:
Traceback (most recent call last):
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 438, in _error_catcher
    yield
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 561, in read
    data = self._fp_read(amt) if not fp_closed else b""
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 527, in _fp_read
    return self._fp.read(amt) if amt is not None else self._fp.read()
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\cachecontrol\filewrapper.py", line 98, in read
    data: bytes = self.__fp.read(amt)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\http\client.py", line 454, in read
    n = self.readinto(b)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\http\client.py", line 498, in readinto
    n = self.fp.readinto(b)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\socket.py", line 669, in readinto
    return self._sock.recv_into(b)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\ssl.py", line 1241, in recv_into
    return self.read(nbytes, buffer)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\ssl.py", line 1099, in read
    return self._sslobj.read(len, buffer)
socket.timeout: The read operation timed out

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\cli\base_command.py", line 180, in exc_logging_wrapper
    status = run_func(*args)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\cli\req_command.py", line 245, in wrapper
    return func(self, options, args)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\commands\install.py", line 377, in run
    requirement_set = resolver.resolve(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\resolver.py", line 95, in resolve
    result = self._result = resolver.resolve(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 546, in resolve
    state = resolution.resolve(requirements, max_rounds=max_rounds)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 427, in resolve
    failure_causes = self._attempt_to_pin_criterion(name)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 239, in _attempt_to_pin_criterion
    criteria = self._get_updated_criteria(candidate)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 230, in _get_updated_criteria
    self._add_to_criteria(criteria, requirement, parent=candidate)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 173, in _add_to_criteria
    if not criterion.candidates:
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\structs.py", line 156, in __bool__
    return bool(self._sequence)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\found_candidates.py", line 155, in __bool__
    return any(self)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\found_candidates.py", line 143, in <genexpr>
    return (c for c in iterator if id(c) not in self._incompatible_ids)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\found_candidates.py", line 47, in _iter_built
    candidate = func()
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\factory.py", line 182, in _make_candidate_from_link
    base: Optional[BaseCandidate] = self._make_base_candidate_from_link(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\factory.py", line 228, in _make_base_candidate_from_link
    self._link_candidate_cache[link] = LinkCandidate(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\candidates.py", line 293, in __init__
    super().__init__(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\candidates.py", line 156, in __init__
    self.dist = self._prepare()
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\candidates.py", line 225, in _prepare
    dist = self._prepare_distribution()
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\candidates.py", line 304, in _prepare_distribution
    return preparer.prepare_linked_requirement(self._ireq, parallel_builds=True)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\operations\prepare.py", line 525, in prepare_linked_requirement
    return self._prepare_linked_requirement(req, parallel_builds)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\operations\prepare.py", line 596, in _prepare_linked_requirement
    local_file = unpack_url(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\operations\prepare.py", line 168, in unpack_url
    file = get_http_url(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\operations\prepare.py", line 109, in get_http_url
    from_path, content_type = download(link, temp_dir.path)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\network\download.py", line 147, in __call__
    for chunk in chunks:
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\cli\progress_bars.py", line 53, in _rich_progress_bar
    for chunk in iterable:
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\network\utils.py", line 63, in response_chunks
    for chunk in response.raw.stream(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 622, in stream
    data = self.read(amt=amt, decode_content=decode_content)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 587, in read
    raise IncompleteRead(self._fp_bytes_read, self.length_remaining)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\contextlib.py", line 131, in __exit__
    self.gen.throw(type, value, traceback)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 443, in _error_catcher
    raise ReadTimeoutError(self._pool, None, "Read timed out.")
pip._vendor.urllib3.exceptions.ReadTimeoutError: HTTPSConnectionPool(host='download.pytorch.org', port=443): Read timed out.

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu121
Looking in indexes: https://download.pytorch.org/whl/nightly/cu121
Requirement already satisfied: torch in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (1.8.1)
Collecting torchvision
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240130%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
Collecting torchaudio
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240130%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
Requirement already satisfied: typing-extensions in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torch) (4.9.0)
Requirement already satisfied: numpy in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torch) (1.24.4)
Requirement already satisfied: requests in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torchvision) (2.31.0)
Collecting torch
  Using cached https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240130%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
Collecting pillow!=8.3.*,>=5.3.0 (from torchvision)
  Using cached https://download.pytorch.org/whl/nightly/Pillow-9.3.0-cp38-cp38-win_amd64.whl (2.5 MB)
Collecting filelock (from torch)
  Using cached https://download.pytorch.org/whl/nightly/filelock-3.9.0-py3-none-any.whl (9.7 kB)
Collecting sympy (from torch)
  Using cached https://download.pytorch.org/whl/nightly/sympy-1.11.1-py3-none-any.whl (6.5 MB)
Collecting networkx (from torch)
  Using cached https://download.pytorch.org/whl/nightly/networkx-3.0rc1-py3-none-any.whl (2.0 MB)
Collecting jinja2 (from torch)
  Using cached https://download.pytorch.org/whl/nightly/Jinja2-3.1.2-py3-none-any.whl (133 kB)
Collecting fsspec (from torch)
  Using cached https://download.pytorch.org/whl/nightly/fsspec-2023.4.0-py3-none-any.whl (153 kB)
INFO: pip is looking at multiple versions of torch to determine which version is compatible with other requirements. This could take a while.
Collecting torchvision
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240129%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
Collecting torch
  Using cached https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240129%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
Collecting torchvision
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240128%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
Collecting torch
  Using cached https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240128%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
Collecting torchvision
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240127%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240127%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
     ---------------- ----------------------- 1.0/2.4 GB 56.0 kB/s eta 6:55:44
ERROR: Exception:
Traceback (most recent call last):
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 438, in _error_catcher
    yield
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 561, in read
    data = self._fp_read(amt) if not fp_closed else b""
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 527, in _fp_read
    return self._fp.read(amt) if amt is not None else self._fp.read()
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\cachecontrol\filewrapper.py", line 98, in read
    data: bytes = self.__fp.read(amt)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\http\client.py", line 454, in read
    n = self.readinto(b)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\http\client.py", line 498, in readinto
    n = self.fp.readinto(b)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\socket.py", line 669, in readinto
    return self._sock.recv_into(b)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\ssl.py", line 1241, in recv_into
    return self.read(nbytes, buffer)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\ssl.py", line 1099, in read
    return self._sslobj.read(len, buffer)
socket.timeout: The read operation timed out

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\cli\base_command.py", line 180, in exc_logging_wrapper
    status = run_func(*args)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\cli\req_command.py", line 245, in wrapper
    return func(self, options, args)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\commands\install.py", line 377, in run
    requirement_set = resolver.resolve(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\resolver.py", line 95, in resolve
    result = self._result = resolver.resolve(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 546, in resolve
    state = resolution.resolve(requirements, max_rounds=max_rounds)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 427, in resolve
    failure_causes = self._attempt_to_pin_criterion(name)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 239, in _attempt_to_pin_criterion
    criteria = self._get_updated_criteria(candidate)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 230, in _get_updated_criteria
    self._add_to_criteria(criteria, requirement, parent=candidate)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\resolvers.py", line 173, in _add_to_criteria
    if not criterion.candidates:
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\resolvelib\structs.py", line 156, in __bool__
    return bool(self._sequence)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\found_candidates.py", line 155, in __bool__
    return any(self)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\found_candidates.py", line 143, in <genexpr>
    return (c for c in iterator if id(c) not in self._incompatible_ids)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\found_candidates.py", line 47, in _iter_built
    candidate = func()
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\factory.py", line 182, in _make_candidate_from_link
    base: Optional[BaseCandidate] = self._make_base_candidate_from_link(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\factory.py", line 228, in _make_base_candidate_from_link
    self._link_candidate_cache[link] = LinkCandidate(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\candidates.py", line 293, in __init__
    super().__init__(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\candidates.py", line 156, in __init__
    self.dist = self._prepare()
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\candidates.py", line 225, in _prepare
    dist = self._prepare_distribution()
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\resolution\resolvelib\candidates.py", line 304, in _prepare_distribution
    return preparer.prepare_linked_requirement(self._ireq, parallel_builds=True)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\operations\prepare.py", line 525, in prepare_linked_requirement
    return self._prepare_linked_requirement(req, parallel_builds)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\operations\prepare.py", line 596, in _prepare_linked_requirement
    local_file = unpack_url(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\operations\prepare.py", line 168, in unpack_url
    file = get_http_url(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\operations\prepare.py", line 109, in get_http_url
    from_path, content_type = download(link, temp_dir.path)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\network\download.py", line 147, in __call__
    for chunk in chunks:
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\cli\progress_bars.py", line 53, in _rich_progress_bar
    for chunk in iterable:
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_internal\network\utils.py", line 63, in response_chunks
    for chunk in response.raw.stream(
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 622, in stream
    data = self.read(amt=amt, decode_content=decode_content)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 587, in read
    raise IncompleteRead(self._fp_bytes_read, self.length_remaining)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\contextlib.py", line 131, in __exit__
    self.gen.throw(type, value, traceback)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\pip\_vendor\urllib3\response.py", line 443, in _error_catcher
    raise ReadTimeoutError(self._pool, None, "Read timed out.")
pip._vendor.urllib3.exceptions.ReadTimeoutError: HTTPSConnectionPool(host='download.pytorch.org', port=443): Read timed out.

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu121
Looking in indexes: https://download.pytorch.org/whl/nightly/cu121
Requirement already satisfied: torch in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (1.8.1)
Collecting torchvision
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240130%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
Collecting torchaudio
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240130%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
Requirement already satisfied: typing-extensions in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torch) (4.9.0)
Requirement already satisfied: numpy in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torch) (1.24.4)
Requirement already satisfied: requests in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from torchvision) (2.31.0)
Collecting torch
  Using cached https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240130%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
Collecting pillow!=8.3.*,>=5.3.0 (from torchvision)
  Using cached https://download.pytorch.org/whl/nightly/Pillow-9.3.0-cp38-cp38-win_amd64.whl (2.5 MB)
Collecting filelock (from torch)
  Using cached https://download.pytorch.org/whl/nightly/filelock-3.9.0-py3-none-any.whl (9.7 kB)
Collecting sympy (from torch)
  Using cached https://download.pytorch.org/whl/nightly/sympy-1.11.1-py3-none-any.whl (6.5 MB)
Collecting networkx (from torch)
  Using cached https://download.pytorch.org/whl/nightly/networkx-3.0rc1-py3-none-any.whl (2.0 MB)
Collecting jinja2 (from torch)
  Using cached https://download.pytorch.org/whl/nightly/Jinja2-3.1.2-py3-none-any.whl (133 kB)
Collecting fsspec (from torch)
  Using cached https://download.pytorch.org/whl/nightly/fsspec-2023.4.0-py3-none-any.whl (153 kB)
INFO: pip is looking at multiple versions of torch to determine which version is compatible with other requirements. This could take a while.
Collecting torchvision
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240129%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
Collecting torch
  Using cached https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240129%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
Collecting torchvision
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240128%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
Collecting torch
  Using cached https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240128%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
Collecting torchvision
  Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240127%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240127%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
     ---------------------------------------- 2.4/2.4 GB 2.4 MB/s eta 0:00:00
Collecting torchvision
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240126%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
     ---------------------------------------- 5.8/5.8 MB 4.2 MB/s eta 0:00:00
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240126%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
     ---------------------------------------- 2.4/2.4 GB 2.5 MB/s eta 0:00:00
Collecting torchvision
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240125%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
     ---------------------------------------- 5.8/5.8 MB 4.3 MB/s eta 0:00:00
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240125%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
     ---------------------------------------- 2.4/2.4 GB 3.0 MB/s eta 0:00:00
Collecting torchvision
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240124%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
     ---------------------------------------- 5.8/5.8 MB 1.1 MB/s eta 0:00:00
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240124%2Bcu121-cp38-cp38-win_amd64.whl (2413.5 MB)
     ---------------------------------------- 2.4/2.4 GB 2.9 MB/s eta 0:00:00
Collecting torchvision
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchvision-0.18.0.dev20240123%2Bcu121-cp38-cp38-win_amd64.whl (5.8 MB)
     ---------------------------------------- 5.8/5.8 MB 4.3 MB/s eta 0:00:00
Collecting torch
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.3.0.dev20240122%2Bcu121-cp38-cp38-win_amd64.whl (2465.0 MB)
     ---------------------------------------- 2.5/2.5 GB 2.7 MB/s eta 0:00:00
INFO: pip is looking at multiple versions of torchaudio to determine which version is compatible with other requirements. This could take a while.
Collecting torchaudio
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240129%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
     ---------------------------------------- 4.1/4.1 MB 3.2 MB/s eta 0:00:00
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240128%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
     ---------------------------------------- 4.1/4.1 MB 647.8 kB/s eta 0:00:00
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240127%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
     ---------------------------------------- 4.1/4.1 MB 1.4 MB/s eta 0:00:00
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240126%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
     ---------------------------------------- 4.1/4.1 MB 3.1 MB/s eta 0:00:00
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240125%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
     ---------------------------------------- 4.1/4.1 MB 3.2 MB/s eta 0:00:00
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240124%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
     ---------------------------------------- 4.1/4.1 MB 3.3 MB/s eta 0:00:00
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.2.0.dev20240123%2Bcu121-cp38-cp38-win_amd64.whl (4.1 MB)
     ---------------------------------------- 4.1/4.1 MB 3.0 MB/s eta 0:00:00
Collecting MarkupSafe>=2.0 (from jinja2->torch)
  Downloading https://download.pytorch.org/whl/nightly/MarkupSafe-2.1.3-cp38-cp38-win_amd64.whl (17 kB)
Requirement already satisfied: charset-normalizer<4,>=2 in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from requests->torchvision) (3.3.2)
Requirement already satisfied: idna<4,>=2.5 in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from requests->torchvision) (3.6)
Requirement already satisfied: urllib3<3,>=1.21.1 in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from requests->torchvision) (2.2.0)
Requirement already satisfied: certifi>=2017.4.17 in c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages (from requests->torchvision) (2023.11.17)
Collecting mpmath>=0.19 (from sympy->torch)
  Downloading https://download.pytorch.org/whl/nightly/mpmath-1.2.1-py3-none-any.whl (532 kB)
     ---------------------------------------- 532.6/532.6 kB 8.4 MB/s eta 0:00:00
Installing collected packages: mpmath, sympy, pillow, networkx, MarkupSafe, fsspec, filelock, jinja2, torch, torchvision, torchaudio
  Attempting uninstall: torch
    Found existing installation: torch 1.8.1
    Uninstalling torch-1.8.1:
      Successfully uninstalled torch-1.8.1
Successfully installed MarkupSafe-2.1.3 filelock-3.9.0 fsspec-2023.4.0 jinja2-3.1.2 mpmath-1.2.1 networkx-3.0rc1 pillow-9.3.0 sympy-1.11.1 torch-2.3.0.dev20240122+cu121 torchaudio-2.2.0.dev20240123+cu121 torchvision-0.18.0.dev20240123+cu121

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>python
Python 3.8.0 (tags/v3.8.0:fa919fd, Oct 14 2019, 19:37:50) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>>
>>> import torch
>>> print(torch.__version__)
2.3.0.dev20240122+cu121
>>> print(torch.cuda.is_available())
True
>>>
>>> exit()

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2023 NVIDIA Corporation
Built on Tue_Jun_13_19:42:34_Pacific_Daylight_Time_2023
Cuda compilation tools, release 12.2, V12.2.91
Build cuda_12.2.r12.2/compiler.32965470_0

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>
C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>whisper Utopia.AU.S01E04.Onwards.and.Upwards.1080p.WEB-DL.AAC2.0.H.264-ABH.mkv --model small --language Chinese
[00:30.000 --> 00:31.000] Katey
[00:32.000 --> 00:33.000] 我找不到咖啡
[00:33.000 --> 00:34.000] 我們找到了
[00:34.000 --> 00:35.000] 為什麼
[00:35.000 --> 00:36.000] 健康的選擇
[00:36.000 --> 00:37.000] 只有一個月而已
[00:37.000 --> 00:38.000] 我們在做工作
[00:38.000 --> 00:41.000] 免費咖啡、糖、醬汁
[00:41.000 --> 00:43.000] 那是四個基本食物群嗎
[00:44.000 --> 00:45.000] 不
[00:46.000 --> 00:47.000] 我會喝一杯
[00:47.000 --> 00:48.000] 有CAMMANMile和Ginger
[00:49.000 --> 00:50.000] 那是誰
[00:50.000 --> 00:51.000] Toni
[00:51.000 --> 00:52.000] 那是Lauren
[00:52.000 --> 00:53.000] 她是一名記者
[00:53.000 --> 00:54.000] 我們在調查
[00:54.000 --> 00:55.000] 不,是一名記者
[00:55.000 --> 00:56.000] 是一名記者
[00:56.000 --> 00:57.000] 是一名記者
[00:57.000 --> 00:58.000] 她是一名記者
[00:58.000 --> 00:59.000] 我們在調查
[00:59.000 --> 01:00.000] 不,是一名記者
[01:00.000 --> 01:01.000] 25年代澳洲人
[01:01.000 --> 01:02.000] 誰在調查我們的未來
[01:02.000 --> 01:03.000] 她在調查我們的未來
[01:03.000 --> 01:04.000] 她在調查我們的未來
[01:04.000 --> 01:05.000] 他答應了
[01:05.000 --> 01:06.000] Ronda在他的旁邊
[01:06.000 --> 01:07.000] 要停止
[01:07.000 --> 01:08.000] 小政治的立場
[01:08.000 --> 01:09.000] 要不然
[01:09.000 --> 01:10.000] 要不然
[01:10.000 --> 01:11.000] 對
[01:11.000 --> 01:12.000] 對不起,我還不確定
[01:12.000 --> 01:13.000] 那是甚麼
[01:13.000 --> 01:14.000] 是Rose Hep
[01:14.000 --> 01:15.000] 是嗎
[01:15.000 --> 01:16.000] 是
[01:16.000 --> 01:17.000] 那些小小的
[01:17.000 --> 01:18.000] 所以
[01:18.000 --> 01:20.000] 這些項目都已經完成了
[01:20.000 --> 01:21.000] 已經完成了
[01:21.000 --> 01:22.000] 還沒結束
[01:22.000 --> 01:23.000] 沒有,他們…
[01:23.000 --> 01:25.000] 他們在各種程度
[01:25.000 --> 01:26.000] 他們是一種技術
[01:26.000 --> 01:27.000] 技術技術
[01:27.000 --> 01:28.000] 還有一種長 term vision
[01:28.000 --> 01:29.000] 對
[01:29.000 --> 01:30.000] 步步步步步步步步
[01:30.000 --> 01:31.000] 很棒,很棒
[01:31.000 --> 01:32.000] 謝謝
[01:32.000 --> 01:33.000] 對不起,我…
[01:33.000 --> 01:34.000] 對不起
[01:34.000 --> 01:35.000] 我看你很熱心
[01:35.000 --> 01:36.000] 我們在討論長 term vision
[01:36.000 --> 01:38.000] 我希望我們可以給你一點點
[01:40.000 --> 01:41.000] Katy
[01:41.000 --> 01:42.000] 你用了甚麼手機
[01:42.000 --> 01:43.000] 我用了
[01:43.000 --> 01:44.000] 為甚麼
[01:44.000 --> 01:45.000] 健康的選擇
[01:45.000 --> 01:46.000] 但所有的食物都在
[01:46.000 --> 01:47.000] 對
[01:47.000 --> 01:48.000] 那是甚麼選擇
[01:48.000 --> 01:49.000] 你可以用雞肉
[01:49.000 --> 01:50.000] 或雞肉
[01:50.000 --> 01:52.000] 這是甚麼選擇
[01:52.000 --> 01:53.000] 這裡
[01:53.000 --> 01:54.000] 你好,Jim
[01:54.000 --> 01:55.000] 你現在在做甚麼
[01:55.000 --> 01:56.000] 我正在做巧克力
[01:56.000 --> 01:57.000] 你現在在做甚麼
[01:57.000 --> 01:58.000] 做甚麼
[01:58.000 --> 02:00.000] 我正在做NHP
[02:00.000 --> 02:01.000] NHP
[02:01.000 --> 02:03.000] National Highways Program
[02:03.000 --> 02:04.000] Connecting Australia
[02:04.000 --> 02:05.000] 27 Billion Dollar
[02:05.000 --> 02:06.000] Kate Zabrano
[02:06.000 --> 02:07.000] 在發展
[02:07.000 --> 02:08.000] 對
[02:08.000 --> 02:09.000] 對
[02:09.000 --> 02:10.000] 對
[02:10.000 --> 02:11.000] 對
[02:11.000 --> 02:12.000] 我可能會把那一個
[02:12.000 --> 02:14.000] 放在背後
[02:14.000 --> 02:15.000] 你對Clerk Priority
[02:15.000 --> 02:16.000] 第一
[02:16.000 --> 02:17.000] 對,國際戰鬥
[02:17.000 --> 02:18.000] 我們可能要把
[02:18.000 --> 02:19.000] 一半的氣勢
[02:19.000 --> 02:20.000] 滑倒了
[02:20.000 --> 02:21.000] 我只是半小時
[02:21.000 --> 02:22.000] 告訴你一件事
[02:22.000 --> 02:24.000] 我們在討論長 term project
[02:24.000 --> 02:25.000] 那聲音很棒
[02:25.000 --> 02:26.000] 我意思是
[02:26.000 --> 02:27.000] 你不要放在自己身上
[02:27.000 --> 02:28.000] 我不是放在自己身上
[02:28.000 --> 02:29.000] 我是放在你身上
[02:31.000 --> 02:32.000] 他不願意喝咖啡
[02:32.000 --> 02:34.000] 不願意
[02:35.000 --> 02:37.000] 那些大男人在討論你
[02:37.000 --> 02:38.000] 那些大男人
[02:38.000 --> 02:39.000] 他曾經在樓下工作
[02:39.000 --> 02:40.000] 但他移動了
[02:40.000 --> 02:41.000] 在這裡
[02:41.000 --> 02:42.000] 他在哪裡
[02:42.000 --> 02:43.000] 在那邊
[02:43.000 --> 02:44.000] 旁邊
[02:44.000 --> 02:45.000] 是否安全
[02:45.000 --> 02:46.000] 當然
[02:49.000 --> 02:50.000] 沒有人在
[02:50.000 --> 02:51.000] 他在附近
[02:51.000 --> 02:52.000] 那為什麼我們在說
[02:52.000 --> 02:53.000] 我不知道
[02:54.000 --> 02:55.000] 他在問我們
[02:55.000 --> 02:56.000] 他在問我們
[02:56.000 --> 02:57.000] 他的表演表演
[02:57.000 --> 02:58.000] 什麼
[02:58.000 --> 02:59.000] 我不知道
[02:59.000 --> 03:00.000] 他在前面
[03:00.000 --> 03:01.000] 他在前面
[03:01.000 --> 03:02.000] 所以希望你能做到
[03:02.000 --> 03:03.000] 他在這裡
[03:03.000 --> 03:04.000] 我怎麼應該
[03:04.000 --> 03:05.000] 在表演表演
[03:05.000 --> 03:06.000] 在我前面
[03:06.000 --> 03:07.000] 我認為我們必須
[03:07.000 --> 03:08.000] 為什麼
[03:08.000 --> 03:09.000] 這是一件事
[03:09.000 --> 03:10.000] 你的表演
[03:10.000 --> 03:11.000] 好
[03:11.000 --> 03:12.000] 你給我一個 Summary
[03:12.000 --> 03:13.000] 我看他做什麼
[03:13.000 --> 03:14.000] 我不知道
[03:14.000 --> 03:15.000] 你找到嗎
[03:15.000 --> 03:16.000] 我問他
[03:16.000 --> 03:17.000] 你不要問他
[03:17.000 --> 03:18.000] 為什麼我們在說
[03:18.000 --> 03:19.000] 他在討論
[03:19.000 --> 03:20.000] 他會在討論
[03:20.000 --> 03:21.000] 當然
[03:21.000 --> 03:22.000] 你怎麼會這樣
[03:22.000 --> 03:23.000] 你喜歡他
Traceback (most recent call last):
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\runpy.py", line 192, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "C:\Users\wb491\AppData\Local\Programs\Python\Python38\Scripts\whisper.exe\__main__.py", line 7, in <module>
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\transcribe.py", line 478, in cli
    result = transcribe(model, audio_path, temperature=temperature, **args)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\transcribe.py", line 240, in transcribe
    result: DecodingResult = decode_with_fallback(mel_segment)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\transcribe.py", line 170, in decode_with_fallback
    decode_result = model.decode(segment, options)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\decoding.py", line 824, in decode
    result = DecodingTask(model, options).run(mel)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\decoding.py", line 737, in run
    tokens, sum_logprobs, no_speech_probs = self._main_loop(audio_features, tokens)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\decoding.py", line 687, in _main_loop
    logits = self.inference.logits(tokens, audio_features)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\decoding.py", line 163, in logits
    return self.model.decoder(tokens, audio_features, kv_cache=self.kv_cache)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
    return forward_call(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\model.py", line 211, in forward
    x = block(x, xa, mask=self.mask, kv_cache=kv_cache)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
    return forward_call(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\model.py", line 136, in forward
    x = x + self.attn(self.attn_ln(x), mask=mask, kv_cache=kv_cache)[0]
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
    return forward_call(*args, **kwargs)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\model.py", line 90, in forward
    wv, qk = self.qkv_attention(q, k, v, mask)
  File "c:\users\wb491\appdata\local\programs\python\python38\lib\site-packages\whisper\model.py", line 108, in qkv_attention
    return (w @ v).permute(0, 2, 1, 3).flatten(start_dim=2), qk.detach()
KeyboardInterrupt

C:\2014[乌托邦(澳洲版) 第一季]Utopia.AU.S01.1080p.WEB-DL.AAC2.0.H.264-ABH[rartv]-7.83GB>

本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如若转载,请注明出处:http://www.coloradmin.cn/o/1424294.html

如若内容造成侵权/违法违规/事实不符,请联系多彩编程网进行投诉反馈,一经查实,立即删除!

相关文章

【简便方法和积累】pytest 单元测试框架中便捷安装插件和执行问题

又来进步一点点~~~ 背景&#xff1a;之前写了两篇关于pytest单元测试框架的文章&#xff0c;本篇内容对之前的做一个补充 一、pytest插件&#xff1a; pytest 有非常多的插件&#xff0c;很方便&#xff0c;以下为插件举例&#xff1a; pytest&#xff0c;pytest-html&#x…

leetcode刷题(剑指offer) 19.删除链表的倒数第N个节点

19.删除链表的倒数第N个节点 给你一个链表&#xff0c;删除链表的倒数第 n 个结点&#xff0c;并且返回链表的头结点。 示例 1&#xff1a; 输入&#xff1a;head [1,2,3,4,5], n 2 输出&#xff1a;[1,2,3,5]示例 2&#xff1a; 输入&#xff1a;head [1], n 1 输出&am…

双异步系列完结撒花,如何解決异步事务问题?

目录 一、前情提要原始需求&#xff1a;读取一个10万行的Excel优化1&#xff1a;[**使用双异步后&#xff0c;从 191s 优化到 2s**](https://blog.csdn.net/guorui_java/article/details/135143234)优化2&#xff1a;[**使用双异步后&#xff0c;如何保证数据一致性&#xff1f…

ClickHouse为什么这么快(二)SSE指令优化

上一篇 ClickHouse为什么这么快&#xff08;一&#xff09;减少数据扫描范围 我们说到了ClickHouse中使用列存储&#xff0c;每个列都单独存储为一个文件&#xff0c;每个文件都是由一个或多个数据块组成&#xff0c;也就是说&#xff1a;每个文件由一个或多个数组组成&#xf…

Python限定符

在正则表达式中&#xff0c;限定符用于指定模式的匹配次数或匹配范围。在Python中&#xff0c;正则表达式模块re提供了多种不同的限定符&#xff0c;以实现更灵活和精确的匹配操作。熟悉并理解Python中的限定符对于处理文本和字符串数据非常重要。本文将详细介绍Python中常见的…

DNS配置文件讲解

1. 概述 BIND&#xff1a;Berkeley Internet Name Domain &#xff0c;伯克利因特网域名解析服务是一种全球使用最广泛的、 最高效的、最安全的域名解析服务程序 2. 安装软件 [rootserver ~]# yum install bind -y 3. bind服务中三个关键文件 /etc/named.conf : 主配置文件…

Histone H3K27ac Antibody, SNAP-ChIP® Certified

EpiCypher是一家为表观遗传学和染色质生物学研究提供高质量试剂和工具的专业制造商。EpiCypher&#xff08;国内代理商欣博盛生物&#xff09;推出的ChIP级别的Histone H3K27ac Antibody符合EpiCypher的“SNAP-ChIP Certified”标准&#xff0c;用于ChIP实验中的特异性和有效靶…

Orion-14B-Chat-RAG本地部署的解决方案

大家好,我是herosunly。985院校硕士毕业,现担任算法研究员一职,热衷于机器学习算法研究与应用。曾获得阿里云天池比赛第一名,CCF比赛第二名,科大讯飞比赛第三名。拥有多项发明专利。对机器学习和深度学习拥有自己独到的见解。曾经辅导过若干个非计算机专业的学生进入到算法…

刷存在感,Excel转Protobuf/Json通用配置文件

使用场景 最近工作流中有将Excel转Protobuf作为配置文件的技术方案。具体实现是先定一个proto文件&#xff0c;再在一个对应excel表中定义对应字段&#xff0c;由策划在excel进行更改。proto文件可以生成对应语言的脚本&#xff0c;然后将excel转成对应protobuf的binary。 我…

【Tomcat与网络9】提高Tomcat启动速度的八大措施

本文我们来看一下如何对Tomcat进行调优&#xff0c;我们对于Tomcat的调优主要集中在三个方面&#xff1a;提高启动速度、提高系统稳定性和提高并发能力&#xff0c;后两者很多时候是相辅相成的&#xff0c;我们放在一起看。 Tomcat现在一般都嵌入在SpringBoot里&#xff0c;因…

又涨又跌 近期现货黄金价格波动怎么看?

踏入2024年一月的下旬&#xff0c;现货黄金价格可以说没了之前火热的状态&#xff0c;盘面上是又涨又跌。面对这样的行情&#xff0c;很多投资者不知道如何看了。下面我们就来讨论一下怎么把握近期的行情。 先区分走势类型。在现货黄金市场中有两种主要的走势类型&#xff0c;一…

千兆电口模块和万兆电口模块:网络速度的演变

随着信息技术的迅猛发展&#xff0c;网络通信技术也在不断进步。在过去的几十年中&#xff0c;以太网的速度发生了巨大的变化&#xff0c;从最初的百兆以太网&#xff0c;到如今的千兆以太网和万兆以太网甚至40G、100G以太网满足了大数据、云计算、人工智能等新兴应用的需求。在…

Golang语言异常机制解析:错误策略与优雅处理

前些天发现了一个巨牛的人工智能学习网站&#xff0c;通俗易懂&#xff0c;风趣幽默&#xff0c;忍不住分享一下给大家。点击跳转到网站https://www.captainbed.cn/kitie。 前言 作为开发者来说&#xff0c;我们没办法保证程序在运行过程中永远不会出现异常&#xff0c;对于异常…

前端JavaScript篇之实现一个将多维数组展示的方法有哪些,分别是?

目录 实现一个将多维数组展示的方法有哪些&#xff0c;分别是&#xff1f;方法一&#xff1a;递归展开成一维数组方法二&#xff1a;嵌套展示结构方法三&#xff1a;ES6新增的数组扩展方法 flat()方法四&#xff1a;apply() 结合 concat() 使用以展开成一维数组方法五&#xff…

2024 年 Sketch 替代品的最佳选择:Windows、Web 和 Mac 用户的详细比较

什么是Sketch Sketch是一个著名的、越来越受欢迎的矢量图形设计软件&#xff0c;它通过各种有用的UI设计和原型设计工具使这一过程更易于管理。 Sketch于2010年9月首次发布&#xff0c;后来在2012年获得苹果设计奖。对于Sketch来说&#xff0c;这正好停止了Adobe使用当时领先…

JAVA Web 学习(二)ServLet

二、动态web 资源开发技术——Servlet Servlet&#xff08;小服务程序&#xff09;是一个与协议无关的、跨平台的Web组件&#xff0c;由Servlet容器所管理。运行在服务器端&#xff0c;可以动态地扩展服务器的功能&#xff0c;并采用“请求一响应”模式提供Web服务。 Servlet的…

基于仿射区间的分布式三相不对称配电网潮流算法matlab仿真

目录 1.课题概述 2.系统仿真结果 3.核心程序与模型 4.系统原理简介 5.完整工程文件 1.课题概述 基于仿射区间的分布式三相不对称配电网潮流算法matlab仿真。 基于仿射区间的&#xff0c;含分布式电源的配电网三相潮流算法&#xff0c;算法涉及仿射&#xff0c;三相&#x…

python爬虫概念及介绍

1. 什么是互联网爬虫&#xff1f; 解释 1 &#xff1a;通过一个程序&#xff0c;根据 Url ( http : // www . taobao . com ) 进行爬取网页&#xff0c;获取有用信息 解释 2&#xff1a;使用程序模拟浏览器&#xff0c;去向服务器发送请求&#xff0c;获取响应信息 2. 爬虫核…

深度学习经典模型之BERT(下)

在"深度学习经典模型之BERT(上)"我们描述了BERT基本信息、意义、与GPT和Transformer的区别、预训练、自监督等相关信息后&#xff0c;本章节将介绍BERT的输入、Encoder、微调及两个主流变种。 BERT inputs 切词方法 BERT的切词方法用的是WordPiece embeddings&…

MongoDB数据模型和WiredTiger读写模型

MongoDB数据模型 思考&#xff1a;MongoDB为什么会使用BSON&#xff1f; BSON协议与数据类型 JSON JSON是当今非常通用的一种跨语言Web数据交互格式&#xff0c;属于ECMAScript标准规范的一个子集。JSON&#xff08;JavaScript Object Notation, JS对象简谱&#xff09;即J…