From 69281f3a2982e7129305074d064c422ca8d63581 Mon Sep 17 00:00:00 2001 From: liupeng Date: Thu, 9 Jan 2025 15:23:40 +0800 Subject: [PATCH 001/118] support timestamps for numbers. --- whisperx/alignment.py | 208 +++++++++++++++++++++++++++++++++--------- 1 file changed, 164 insertions(+), 44 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index d6241bbca..03b5a496a 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -2,6 +2,8 @@ Forced Alignment with Whisper C. Max Bain """ +import math + from dataclasses import dataclass from typing import Iterable, Optional, Union, List @@ -163,10 +165,17 @@ def align( elif char_ in model_dictionary.keys(): clean_char.append(char_) clean_cdx.append(cdx) + else: + # add placeholder + clean_char.append('*') + clean_cdx.append(cdx) clean_wdx = [] for wdx, wrd in enumerate(per_word): - if any([c in model_dictionary.keys() for c in wrd]): + if any([c in model_dictionary.keys() for c in wrd.lower()]): + clean_wdx.append(wdx) + else: + # index for placeholder clean_wdx.append(wdx) @@ -211,7 +220,7 @@ def align( continue text_clean = "".join(segment["clean_char"]) - tokens = [model_dictionary[c] for c in text_clean] + tokens = [model_dictionary.get(c, -1) for c in text_clean] f1 = int(t1 * SAMPLE_RATE) f2 = int(t2 * SAMPLE_RATE) @@ -244,7 +253,8 @@ def align( blank_id = code trellis = get_trellis(emission, tokens, blank_id) - path = backtrack(trellis, emission, tokens, blank_id) + # path = backtrack(trellis, emission, tokens, blank_id) + path = backtrack_beam(trellis, emission, tokens, blank_id) if path is None: print(f'Failed to align segment ("{segment["text"]}"): backtrack failed, resorting to original...') @@ -253,7 +263,7 @@ def align( char_segments = merge_repeats(path, text_clean) - duration = t2 -t1 + duration = t2 - t1 ratio = duration * waveform_segment.size(0) / (trellis.size(0) - 1) # assign timestamps to aligned characters @@ -360,70 +370,180 @@ def align( """ source: https://pytorch.org/tutorials/intermediate/forced_alignment_with_torchaudio_tutorial.html """ + + def get_trellis(emission, tokens, blank_id=0): num_frame = emission.size(0) num_tokens = len(tokens) - # Trellis has extra diemsions for both time axis and tokens. - # The extra dim for tokens represents (start-of-sentence) - # The extra dim for time axis is for simplification of the code. - trellis = torch.empty((num_frame + 1, num_tokens + 1)) - trellis[0, 0] = 0 - trellis[1:, 0] = torch.cumsum(emission[:, 0], 0) - trellis[0, -num_tokens:] = -float("inf") - trellis[-num_tokens:, 0] = float("inf") + trellis = torch.zeros((num_frame, num_tokens)) + trellis[1:, 0] = torch.cumsum(emission[1:, blank_id], 0) + trellis[0, 1:] = -float("inf") + trellis[-num_tokens + 1:, 0] = float("inf") - for t in range(num_frame): + for t in range(num_frame - 1): trellis[t + 1, 1:] = torch.maximum( # Score for staying at the same token trellis[t, 1:] + emission[t, blank_id], # Score for changing to the next token - trellis[t, :-1] + emission[t, tokens], + # trellis[t, :-1] + emission[t, tokens[1:]], + trellis[t, :-1] + get_wildcard_emission(emission[t], tokens[1:], blank_id), ) return trellis + +def get_wildcard_emission(frame_emission, tokens, blank_id): + """处理包含通配符的token emission分数 + + Args: + frame_emission: 当前帧的emission概率向量 + tokens: token索引列表 + + Returns: + tensor: 每个token位置的最大概率分数 + """ + assert 0 <= blank_id < len(frame_emission) + scores = [] + for token in tokens: + if token == -1: # 通配符 + valid_scores = torch.cat([frame_emission[:blank_id], frame_emission[blank_id + 1:]]) + scores.append(torch.max(valid_scores)) + else: + scores.append(frame_emission[token]) + return torch.tensor(scores) + + @dataclass class Point: token_index: int time_index: int score: float + def backtrack(trellis, emission, tokens, blank_id=0): - # Note: - # j and t are indices for trellis, which has extra dimensions - # for time and tokens at the beginning. - # When referring to time frame index `T` in trellis, - # the corresponding index in emission is `T-1`. - # Similarly, when referring to token index `J` in trellis, - # the corresponding index in transcript is `J-1`. - j = trellis.size(1) - 1 - t_start = torch.argmax(trellis[:, j]).item() - - path = [] - for t in range(t_start, 0, -1): + t, j = trellis.size(0) - 1, trellis.size(1) - 1 + + path = [Point(j, t, emission[t, blank_id].exp().item())] + while j > 0: + # Should not happen but just in case + assert t > 0 + # 1. Figure out if the current position was stay or change - # Note (again): - # `emission[J-1]` is the emission at time frame `J` of trellis dimension. - # Score for token staying the same from time frame J-1 to T. - stayed = trellis[t - 1, j] + emission[t - 1, blank_id] - # Score for token changing from C-1 at T-1 to J at T. - changed = trellis[t - 1, j - 1] + emission[t - 1, tokens[j - 1]] - - # 2. Store the path with frame-wise probability. - prob = emission[t - 1, tokens[j - 1] if changed > stayed else 0].exp().item() - # Return token index and time index in non-trellis coordinate. - path.append(Point(j - 1, t - 1, prob)) - - # 3. Update the token + # Frame-wise score of stay vs change + p_stay = emission[t - 1, blank_id] + # p_change = emission[t - 1, tokens[j]] + p_change = get_wildcard_emission(emission[t - 1], [tokens[j]], blank_id)[0] + + # Context-aware score for stay vs change + stayed = trellis[t - 1, j] + p_stay + changed = trellis[t - 1, j - 1] + p_change + + # Update position + t -= 1 if changed > stayed: j -= 1 - if j == 0: - break - else: - # failed - return None + + # Store the path with frame-wise probability. + prob = (p_change if changed > stayed else p_stay).exp().item() + path.append(Point(j, t, prob)) + + # Now j == 0, which means, it reached the SoS. + # Fill up the rest for the sake of visualization + while t > 0: + prob = emission[t - 1, blank_id].exp().item() + path.append(Point(j, t - 1, prob)) + t -= 1 + return path[::-1] + + +@dataclass +class Path: + points: List[Point] + score: float + + +@dataclass +class BeamState: + """beam search中的状态""" + token_index: int # 当前token位置 + time_index: int # 当前时间步 + score: float # 累积分数 + path: List[Point] # 路径历史 + + +def backtrack_beam(trellis, emission, tokens, blank_id=0, beam_width=5): + """标准CTC beam search回溯实现 + """ + T, J = trellis.size(0) - 1, trellis.size(1) - 1 + + init_state = BeamState( + token_index=J, + time_index=T, + score=trellis[T, J], + path=[Point(J, T, emission[T, blank_id].exp().item())] + ) + + beams = [init_state] + + while beams and beams[0].token_index > 0: + next_beams = [] + + for beam in beams: + t, j = beam.time_index, beam.token_index + + if t <= 0: + continue + + p_stay = emission[t - 1, blank_id] + p_change = get_wildcard_emission(emission[t - 1], [tokens[j]], blank_id)[0] + + stay_score = trellis[t - 1, j] + change_score = trellis[t - 1, j - 1] if j > 0 else float('-inf') + + # Stay路径 + if not math.isinf(stay_score): + new_path = beam.path.copy() + new_path.append(Point(j, t - 1, p_stay.exp().item())) + next_beams.append(BeamState( + token_index=j, + time_index=t - 1, + score=stay_score, + path=new_path + )) + + # Change路径 + if j > 0 and not math.isinf(change_score): + new_path = beam.path.copy() + new_path.append(Point(j - 1, t - 1, p_change.exp().item())) + next_beams.append(BeamState( + token_index=j - 1, + time_index=t - 1, + score=change_score, + path=new_path + )) + + # 只按分数排序，不需要去重 + beams = sorted(next_beams, key=lambda x: x.score, reverse=True)[:beam_width] + + if not beams: + break + + if not beams: + raise ValueError("No valid path found") + + best_beam = beams[0] + t = best_beam.time_index + j = best_beam.token_index + while t > 0: + prob = emission[t - 1, blank_id].exp().item() + best_beam.path.append(Point(j, t - 1, prob)) + t -= 1 + + return best_beam.path[::-1] + + # Merge the labels @dataclass class Segment: From 65b2332e139843cc553f589dc54e004e3c25ba39 Mon Sep 17 00:00:00 2001 From: liupeng Date: Thu, 9 Jan 2025 19:33:26 +0800 Subject: [PATCH 002/118] make align a bit faster. --- whisperx/alignment.py | 32 ++++++++++++++++++++++---------- 1 file changed, 22 insertions(+), 10 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 03b5a496a..872859fcd 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -254,7 +254,7 @@ def align( trellis = get_trellis(emission, tokens, blank_id) # path = backtrack(trellis, emission, tokens, blank_id) - path = backtrack_beam(trellis, emission, tokens, blank_id) + path = backtrack_beam(trellis, emission, tokens, blank_id, beam_width=2) if path is None: print(f'Failed to align segment ("{segment["text"]}"): backtrack failed, resorting to original...') @@ -393,24 +393,36 @@ def get_trellis(emission, tokens, blank_id=0): def get_wildcard_emission(frame_emission, tokens, blank_id): - """处理包含通配符的token emission分数 + """处理包含通配符的token emission分数（向量化版本） Args: frame_emission: 当前帧的emission概率向量 tokens: token索引列表 + blank_id: blank token的ID Returns: tensor: 每个token位置的最大概率分数 """ assert 0 <= blank_id < len(frame_emission) - scores = [] - for token in tokens: - if token == -1: # 通配符 - valid_scores = torch.cat([frame_emission[:blank_id], frame_emission[blank_id + 1:]]) - scores.append(torch.max(valid_scores)) - else: - scores.append(frame_emission[token]) - return torch.tensor(scores) + + # 将tokens转换为tensor（如果还不是的话） + tokens = torch.tensor(tokens) if not isinstance(tokens, torch.Tensor) else tokens + + # 创建mask来标识通配符位置 + wildcard_mask = (tokens == -1) + + # 为非通配符位置获取分数 + regular_scores = frame_emission[tokens.clamp(min=0)] # clamp避免-1索引 + + # 创建掩码并计算最大值，不会修改frame_emission + max_valid_score = frame_emission.clone() # 创建副本 + max_valid_score[blank_id] = float('-inf') # 在副本上操作 + max_valid_score = max_valid_score.max() + + # 使用where操作来组合结果 + result = torch.where(wildcard_mask, max_valid_score, regular_scores) + + return result @dataclass From 4ebfb078c5af9f31bc0b80e784f04cb1e24cbdc0 Mon Sep 17 00:00:00 2001 From: liupeng Date: Thu, 9 Jan 2025 23:13:11 +0800 Subject: [PATCH 003/118] make no beam consistent with backtrack. --- whisperx/alignment.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 872859fcd..a54faa3a2 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -543,7 +543,7 @@ def backtrack_beam(trellis, emission, tokens, blank_id=0, beam_width=5): break if not beams: - raise ValueError("No valid path found") + return None best_beam = beams[0] t = best_beam.time_index From 289eadfc766dc54f67024b38d5b1161c7a739e1c Mon Sep 17 00:00:00 2001 From: liupeng Date: Mon, 13 Jan 2025 20:26:27 +0800 Subject: [PATCH 004/118] fix a merge error. --- whisperx/alignment.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 3a560ee7e..39e48e5c4 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -230,7 +230,7 @@ def align( continue text_clean = "".join(segment_data[sdx]["clean_char"]) - tokens = [model_dictionary[c] for c in text_clean] + tokens = [model_dictionary.get(c, -1) for c in text_clean] f1 = int(t1 * SAMPLE_RATE) f2 = int(t2 * SAMPLE_RATE) From ffbc73664c67aa76c3a6c5ab108d2c2905ea1803 Mon Sep 17 00:00:00 2001 From: liupeng Date: Mon, 13 Jan 2025 22:56:48 +0800 Subject: [PATCH 005/118] change the docstrings and comments to English --- whisperx/alignment.py | 55 ++++++++++++++++++++++++++----------------- 1 file changed, 33 insertions(+), 22 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 39e48e5c4..0c4e2b0e7 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -403,33 +403,33 @@ def get_trellis(emission, tokens, blank_id=0): def get_wildcard_emission(frame_emission, tokens, blank_id): - """处理包含通配符的token emission分数（向量化版本） + """Processing token emission scores containing wildcards (vectorized version) Args: - frame_emission: 当前帧的emission概率向量 - tokens: token索引列表 - blank_id: blank token的ID + frame_emission: Emission probability vector for the current frame + tokens: List of token indices + blank_id: ID of the blank token Returns: - tensor: 每个token位置的最大概率分数 + tensor: Maximum probability score for each token position """ assert 0 <= blank_id < len(frame_emission) - # 将tokens转换为tensor（如果还不是的话） + # Convert tokens to a tensor if they are not already tokens = torch.tensor(tokens) if not isinstance(tokens, torch.Tensor) else tokens - # 创建mask来标识通配符位置 + # Create a mask to identify wildcard positions wildcard_mask = (tokens == -1) - # 为非通配符位置获取分数 - regular_scores = frame_emission[tokens.clamp(min=0)] # clamp避免-1索引 + # Get scores for non-wildcard positions + regular_scores = frame_emission[tokens.clamp(min=0)] # clamp to avoid -1 index - # 创建掩码并计算最大值，不会修改frame_emission - max_valid_score = frame_emission.clone() # 创建副本 - max_valid_score[blank_id] = float('-inf') # 在副本上操作 + # Create a mask and compute the maximum value without modifying frame_emission + max_valid_score = frame_emission.clone() # Create a copy + max_valid_score[blank_id] = float('-inf') # Modify the copy to exclude the blank token max_valid_score = max_valid_score.max() - # 使用where操作来组合结果 + # Use where operation to combine results result = torch.where(wildcard_mask, max_valid_score, regular_scores) return result @@ -488,15 +488,26 @@ class Path: @dataclass class BeamState: - """beam search中的状态""" - token_index: int # 当前token位置 - time_index: int # 当前时间步 - score: float # 累积分数 - path: List[Point] # 路径历史 + """State in beam search.""" + token_index: int # Current token position + time_index: int # Current time step + score: float # Cumulative score + path: List[Point] # Path history def backtrack_beam(trellis, emission, tokens, blank_id=0, beam_width=5): - """标准CTC beam search回溯实现 + """Standard CTC beam search backtracking implementation. + + Args: + trellis (torch.Tensor): The trellis (or lattice) of shape (T, N), where T is the number of time steps + and N is the number of tokens (including the blank token). + emission (torch.Tensor): The emission probabilities of shape (T, N). + tokens (List[int]): List of token indices (excluding the blank token). + blank_id (int, optional): The ID of the blank token. Defaults to 0. + beam_width (int, optional): The number of top paths to keep during beam search. Defaults to 5. + + Returns: + List[Point]: the best path """ T, J = trellis.size(0) - 1, trellis.size(1) - 1 @@ -524,7 +535,7 @@ def backtrack_beam(trellis, emission, tokens, blank_id=0, beam_width=5): stay_score = trellis[t - 1, j] change_score = trellis[t - 1, j - 1] if j > 0 else float('-inf') - # Stay路径 + # Stay if not math.isinf(stay_score): new_path = beam.path.copy() new_path.append(Point(j, t - 1, p_stay.exp().item())) @@ -535,7 +546,7 @@ def backtrack_beam(trellis, emission, tokens, blank_id=0, beam_width=5): path=new_path )) - # Change路径 + # Change if j > 0 and not math.isinf(change_score): new_path = beam.path.copy() new_path.append(Point(j - 1, t - 1, p_change.exp().item())) @@ -546,7 +557,7 @@ def backtrack_beam(trellis, emission, tokens, blank_id=0, beam_width=5): path=new_path )) - # 只按分数排序，不需要去重 + # sort by score beams = sorted(next_beams, key=lambda x: x.score, reverse=True)[:beam_width] if not beams: From 235536e28d2c781c1357fb4dcd649a23782d03ba Mon Sep 17 00:00:00 2001 From: Markus Jochim Date: Mon, 25 Mar 2024 16:50:58 +0100 Subject: [PATCH 006/118] Update links to language models in README --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 82c435f81..10a923d8a 100644 --- a/README.md +++ b/README.md @@ -156,10 +156,10 @@ To run on CPU instead of GPU (and for running on Mac OS X): ### Other languages -The phoneme ASR alignment model is *language-specific*, for tested languages these models are [automatically picked from torchaudio pipelines or huggingface](https://github.com/m-bain/whisperX/blob/e909f2f766b23b2000f2d95df41f9b844ac53e49/whisperx/transcribe.py#L22). +The phoneme ASR alignment model is *language-specific*, for tested languages these models are [automatically picked from torchaudio pipelines or huggingface](https://github.com/m-bain/whisperX/blob/f2da2f858e99e4211fe4f64b5f2938b007827e17/whisperx/alignment.py#L24-L58). Just pass in the `--language` code, and use the whisper `--model large`. -Currently default models provided for `{en, fr, de, es, it, ja, zh, nl, uk, pt}`. If the detected language is not in this list, you need to find a phoneme-based ASR model from [huggingface model hub](https://huggingface.co/models) and test it on your data. +Currently default models provided for `{en, fr, de, es, it}` via torchaudio pipelines and [25 other languages via huggingface](https://github.com/m-bain/whisperX/blob/f2da2f858e99e4211fe4f64b5f2938b007827e17/whisperx/alignment.py#L32-L58). If the detected language is not in this list, you need to find a phoneme-based ASR model from [huggingface model hub](https://huggingface.co/models) and test it on your data. #### E.g. German From 70c639cdb57406d295f6fec45a66021c34c5f41b Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 17 Jan 2025 08:46:38 +0100 Subject: [PATCH 007/118] doc: refer to DEFAULT_ALIGN_MODELS_HF for other langs --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 10a923d8a..42df9a53c 100644 --- a/README.md +++ b/README.md @@ -159,7 +159,7 @@ To run on CPU instead of GPU (and for running on Mac OS X): The phoneme ASR alignment model is *language-specific*, for tested languages these models are [automatically picked from torchaudio pipelines or huggingface](https://github.com/m-bain/whisperX/blob/f2da2f858e99e4211fe4f64b5f2938b007827e17/whisperx/alignment.py#L24-L58). Just pass in the `--language` code, and use the whisper `--model large`. -Currently default models provided for `{en, fr, de, es, it}` via torchaudio pipelines and [25 other languages via huggingface](https://github.com/m-bain/whisperX/blob/f2da2f858e99e4211fe4f64b5f2938b007827e17/whisperx/alignment.py#L32-L58). If the detected language is not in this list, you need to find a phoneme-based ASR model from [huggingface model hub](https://huggingface.co/models) and test it on your data. +Currently default models provided for `{en, fr, de, es, it}` via torchaudio pipelines and many other languages via Hugging Face. Please find the list of currently supported languages under `DEFAULT_ALIGN_MODELS_HF` on [alignment.py](https://github.com/m-bain/whisperX/blob/main/whisperx/alignment.py). If the detected language is not in this list, you need to find a phoneme-based ASR model from [huggingface model hub](https://huggingface.co/models) and test it on your data. #### E.g. German From 86e2b3ee747a37c2afa10afd0c21b036ac28eaae Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 17 Jan 2025 09:12:05 +0100 Subject: [PATCH 008/118] chore: remove deprecated VAD_SEGMENTATION_URL --- whisperx/vads/pyannote.py | 7 ------- 1 file changed, 7 deletions(-) diff --git a/whisperx/vads/pyannote.py b/whisperx/vads/pyannote.py index 68d6a7f18..543fb81aa 100644 --- a/whisperx/vads/pyannote.py +++ b/whisperx/vads/pyannote.py @@ -17,9 +17,6 @@ from whisperx.diarize import Segment as SegmentX from whisperx.vads.vad import Vad -# deprecated -VAD_SEGMENTATION_URL = "https://whisperx.s3.eu-west-2.amazonaws.com/model_weights/segmentation/0b5b3216d60a2d32fc086b47ea8c67589aaeb26b7e07fcbe620d6d0b83e209ea/pytorch_model.bin" - def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, use_auth_token=None, model_fp=None): model_dir = torch.hub._get_torch_home() @@ -41,10 +38,6 @@ def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, use_auth_token=Non raise RuntimeError(f"{model_fp} exists and is not a regular file") model_bytes = open(model_fp, "rb").read() - if hashlib.sha256(model_bytes).hexdigest() != VAD_SEGMENTATION_URL.split('/')[-2]: - raise RuntimeError( - "Model has been downloaded but the SHA256 checksum does not match. Please retry loading the model." - ) vad_model = Model.from_pretrained(model_fp, use_auth_token=use_auth_token) hyperparameters = {"onset": vad_onset, From de0d8fe313f6a8c7d36f034e7343c5ca643d933f Mon Sep 17 00:00:00 2001 From: tan90xx <592026773@qq.com> Date: Sun, 19 Jan 2025 21:20:56 +0800 Subject: [PATCH 009/118] chore: handle empty segments_list case in silero prevent errors --- whisperx/vads/silero.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/whisperx/vads/silero.py b/whisperx/vads/silero.py index e7b44cc45..4b8cd0942 100644 --- a/whisperx/vads/silero.py +++ b/whisperx/vads/silero.py @@ -59,4 +59,8 @@ def merge_chunks(segments, offset: Optional[float] = None, ): assert chunk_size > 0 + if len(segments_list) == 0: + print("No active speech found in audio") + return [] + assert segments_list, "segments_list is empty." return Vad.merge_chunks(segments, chunk_size, onset, offset) From fca563a782e0326ebc62314fd281e58908ebe0fe Mon Sep 17 00:00:00 2001 From: tan90xx <592026773@qq.com> Date: Mon, 20 Jan 2025 19:52:37 +0800 Subject: [PATCH 010/118] Update silero.py --- whisperx/vads/silero.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/whisperx/vads/silero.py b/whisperx/vads/silero.py index 4b8cd0942..92573aab7 100644 --- a/whisperx/vads/silero.py +++ b/whisperx/vads/silero.py @@ -53,7 +53,7 @@ def preprocess_audio(audio): return audio @staticmethod - def merge_chunks(segments, + def merge_chunks(segments_list, chunk_size, onset: float = 0.5, offset: Optional[float] = None, From acbeba6057493d8a7ecdcaa6cfb462020679c466 Mon Sep 17 00:00:00 2001 From: tan90xx <592026773@qq.com> Date: Mon, 20 Jan 2025 20:01:21 +0800 Subject: [PATCH 011/118] Update silero.py --- whisperx/vads/silero.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/whisperx/vads/silero.py b/whisperx/vads/silero.py index 92573aab7..88c54b831 100644 --- a/whisperx/vads/silero.py +++ b/whisperx/vads/silero.py @@ -63,4 +63,4 @@ def merge_chunks(segments_list, print("No active speech found in audio") return [] assert segments_list, "segments_list is empty." - return Vad.merge_chunks(segments, chunk_size, onset, offset) + return Vad.merge_chunks(segments_list, chunk_size, onset, offset) From 36d2622e274ce580c529f5b9cecd15af1ce7b5e5 Mon Sep 17 00:00:00 2001 From: Reinis Ivanovs Date: Fri, 24 Jan 2025 22:24:15 +0200 Subject: [PATCH 012/118] feat: add Latvian align model --- whisperx/alignment.py | 1 + whisperx/utils.py | 1 + 2 files changed, 2 insertions(+) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 0c4e2b0e7..3b2fdae9f 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -69,6 +69,7 @@ "eu": "stefan-it/wav2vec2-large-xlsr-53-basque", "gl": "ifrz/wav2vec2-large-xlsr-galician", "ka": "xsway/wav2vec2-large-xlsr-georgian", + "lv": "jimregan/wav2vec2-large-xlsr-latvian-cv", } diff --git a/whisperx/utils.py b/whisperx/utils.py index dfe3cf2e9..4ccd77c12 100644 --- a/whisperx/utils.py +++ b/whisperx/utils.py @@ -106,6 +106,7 @@ "jw": "javanese", "su": "sundanese", "yue": "cantonese", + "lv": "latvian", } # language code lookup by name, with a few language aliases From 7b3c9ce629b38fcd4de62da0c0a282fcd7278b92 Mon Sep 17 00:00:00 2001 From: philmcmahon Date: Mon, 27 Jan 2025 12:16:37 +0000 Subject: [PATCH 013/118] Add models_cache_only param --- whisperx/transcribe.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 1d7d1ac12..ae61ed1d9 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -26,6 +26,7 @@ def cli(): parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument("audio", nargs="+", type=str, help="audio file(s) to transcribe") parser.add_argument("--model", default="small", help="name of the Whisper model to use") + parser.add_argument("--model_cache_only", type=str2bool, default=False, help="If True, will not attempt to download models, instead using cached models from --model_dir") parser.add_argument("--model_dir", type=str, default=None, help="the path to save model files; uses ~/.cache/whisper by default") parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu", help="device to use for PyTorch inference") parser.add_argument("--device_index", default=0, type=int, help="device index to use for FasterWhisper inference") @@ -90,6 +91,7 @@ def cli(): model_name: str = args.pop("model") batch_size: int = args.pop("batch_size") model_dir: str = args.pop("model_dir") + model_cache_only: bool = args.pop("model_cache_only") output_dir: str = args.pop("output_dir") output_format: str = args.pop("output_format") device: str = args.pop("device") @@ -177,7 +179,7 @@ def cli(): results = [] tmp_results = [] # model = load_model(model_name, device=device, download_root=model_dir) - model = load_model(model_name, device=device, device_index=device_index, download_root=model_dir, compute_type=compute_type, language=args['language'], asr_options=asr_options, vad_method=vad_method, vad_options={"chunk_size":chunk_size, "vad_onset": vad_onset, "vad_offset": vad_offset}, task=task, threads=faster_whisper_threads) + model = load_model(model_name, device=device, device_index=device_index, download_root=model_dir, compute_type=compute_type, language=args['language'], asr_options=asr_options, vad_method=vad_method, vad_options={"chunk_size":chunk_size, "vad_onset": vad_onset, "vad_offset": vad_offset}, task=task, local_files_only=model_cache_only, threads=faster_whisper_threads) for audio_path in args.pop("audio"): audio = load_audio(audio_path) From 272714e07da0e0d7145a63ddd3615f44a4080322 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 16 Jan 2025 08:09:57 +0100 Subject: [PATCH 014/118] feat: use uv for building package --- pyproject.toml | 32 + requirements.txt | 8 - setup.py | 33 - uv.lock | 2912 ++++++++++++++++++++++++++++++++++++++++++++++ 4 files changed, 2944 insertions(+), 41 deletions(-) create mode 100644 pyproject.toml delete mode 100644 requirements.txt delete mode 100644 setup.py create mode 100644 uv.lock diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 000000000..6bcef2f54 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,32 @@ +[project] +urls = { repository = "https://github.com/m-bain/whisperx" } +authors = [{ name = "Max Bain" }] +name = "whisperx" +version = "3.3.1" +description = "Time-Accurate Automatic Speech Recognition using Whisper." +readme = "README.md" +requires-python = ">=3.9, <3.13" +license = { text = "BSD-2-Clause" } + +dependencies = [ + "ctranslate2>=4.5.0", + "faster-whisper>=1.1.1", + "nltk>=3.9.1", + "onnxruntime==1.19", + "pandas>=2.2.3", + "pyannote-audio>=3.3.2", + "torch>=2.5.1", + "torchaudio>=2.5.1", + "transformers>=4.48.0", +] + + +[project.scripts] +whisperx = "whisperx.transcribe:cli" + +[build-system] +requires = ["setuptools"] + +[tool.setuptools] +packages = ["whisperx"] +include-package-data = true diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index e3bdecfed..000000000 --- a/requirements.txt +++ /dev/null @@ -1,8 +0,0 @@ -torch>=2 -torchaudio>=2 -faster-whisper==1.1.0 -ctranslate2<4.5.0 -transformers -pandas -setuptools>=65 -nltk diff --git a/setup.py b/setup.py deleted file mode 100644 index 13759a6c2..000000000 --- a/setup.py +++ /dev/null @@ -1,33 +0,0 @@ -import os - -import pkg_resources -from setuptools import find_packages, setup - -with open("README.md", "r", encoding="utf-8") as f: - long_description = f.read() - -setup( - name="whisperx", - py_modules=["whisperx"], - version="3.3.1", - description="Time-Accurate Automatic Speech Recognition using Whisper.", - long_description=long_description, - long_description_content_type="text/markdown", - python_requires=">=3.9, <3.13", - author="Max Bain", - url="https://github.com/m-bain/whisperx", - 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hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931", size = 9630 }, +] From 63bc1903c186838e2cbde4bd780a3816ff120c48 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 16 Jan 2025 08:10:22 +0100 Subject: [PATCH 015/118] feat: update Python compatibility workflow to use uv --- .github/workflows/python-compatibility.yml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/python-compatibility.yml b/.github/workflows/python-compatibility.yml index a5589f608..263ebb95d 100644 --- a/.github/workflows/python-compatibility.yml +++ b/.github/workflows/python-compatibility.yml @@ -5,7 +5,7 @@ on: branches: [main] pull_request: branches: [main] - workflow_dispatch: # Allows manual triggering from GitHub UI + workflow_dispatch: # Allows manual triggering from GitHub UI jobs: test: @@ -24,8 +24,8 @@ jobs: - name: Install package run: | - python -m pip install --upgrade pip - pip install . + python -m pip install uv + uv sync - name: Test import run: | From b41ebd4871f9cf9cf9b86bb61b446b2f5c9af29a Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 16 Jan 2025 08:16:46 +0100 Subject: [PATCH 016/118] chore: add numpy to deps --- pyproject.toml | 1 + uv.lock | 3 +++ 2 files changed, 4 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 6bcef2f54..9249fd9df 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,6 +12,7 @@ dependencies = [ "ctranslate2>=4.5.0", "faster-whisper>=1.1.1", "nltk>=3.9.1", + "numpy>=2.0.2", "onnxruntime==1.19", "pandas>=2.2.3", "pyannote-audio>=3.3.2", diff --git a/uv.lock b/uv.lock index 155fe1e97..72ea22c36 100644 --- a/uv.lock +++ b/uv.lock @@ -2803,6 +2803,8 @@ dependencies = [ { name = "ctranslate2" }, { name = "faster-whisper" }, { name = "nltk" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" }, + { name = "numpy", version = "2.2.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" }, { name = "onnxruntime" }, { name = "pandas" }, { name = "pyannote-audio" }, @@ -2816,6 +2818,7 @@ requires-dist = [ { name = "ctranslate2", specifier = ">=4.5.0" }, { name = "faster-whisper", specifier = ">=1.1.1" }, { name = "nltk", specifier = ">=3.9.1" }, + { name = "numpy", specifier = ">=2.0.2" }, { name = "onnxruntime", specifier = "==1.19" }, { name = "pandas", specifier = ">=2.2.3" }, { name = "pyannote-audio", specifier = ">=3.3.2" }, From 90256cc48154fad01ca96922cacdd8d11c4bb911 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 16 Jan 2025 08:21:45 +0100 Subject: [PATCH 017/118] feat: use uv recommended setup --- .github/workflows/python-compatibility.yml | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/.github/workflows/python-compatibility.yml b/.github/workflows/python-compatibility.yml index 263ebb95d..1c2fa7826 100644 --- a/.github/workflows/python-compatibility.yml +++ b/.github/workflows/python-compatibility.yml @@ -17,16 +17,15 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v5 + - name: Install uv + uses: astral-sh/setup-uv@v5 with: + version: "0.5.14" python-version: ${{ matrix.python-version }} - - name: Install package - run: | - python -m pip install uv - uv sync + - name: Install the project + run: uv sync --all-extras - name: Test import run: | - python -c "import whisperx; print('Successfully imported whisperx')" + uv run python -c "import whisperx; print('Successfully imported whisperx')" From 7489ebf87681cf0881e253a781d7c636651f8534 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 16 Jan 2025 08:38:17 +0100 Subject: [PATCH 018/118] feat: update build and release workflow to use uv for package installation and publishing --- .github/workflows/build-and-release.yml | 22 +++++++++------------- 1 file changed, 9 insertions(+), 13 deletions(-) diff --git a/.github/workflows/build-and-release.yml b/.github/workflows/build-and-release.yml index e4da6af0d..6fd84f3b4 100644 --- a/.github/workflows/build-and-release.yml +++ b/.github/workflows/build-and-release.yml @@ -11,25 +11,21 @@ jobs: - name: Checkout uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 + - name: Install uv + uses: astral-sh/setup-uv@v5 with: + version: "0.5.14" python-version: "3.9" - - name: Install dependencies - run: | - python -m pip install build - - - name: Build wheels - run: python -m build --wheel + - name: Build package + run: uv build - name: Release to Github uses: softprops/action-gh-release@v2 with: - files: dist/* + files: dist/*.whl - name: Publish package to PyPi - uses: pypa/gh-action-pypi-publish@27b31702a0e7fc50959f5ad993c78deac1bdfc29 - with: - user: __token__ - password: ${{ secrets.PYPI_API_TOKEN }} + run: uv publish + env: + UV_PUBLISH_TOKEN: ${{ secrets.PYPI_API_TOKEN }} From d2f0e53f713bcffc4286cc77fea1f0b1548fe068 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 17 Jan 2025 08:03:59 +0100 Subject: [PATCH 019/118] chore: remove tmp workflow --- .github/workflows/tmp.yml | 35 ----------------------------------- 1 file changed, 35 deletions(-) delete mode 100644 .github/workflows/tmp.yml diff --git a/.github/workflows/tmp.yml b/.github/workflows/tmp.yml deleted file mode 100644 index a83de44ee..000000000 --- a/.github/workflows/tmp.yml +++ /dev/null @@ -1,35 +0,0 @@ -name: Python Compatibility Test (PyPi) - -on: - push: - branches: [main] - pull_request: - branches: [main] - workflow_dispatch: # Allows manual triggering from GitHub UI - -jobs: - test: - runs-on: ubuntu-latest - strategy: - matrix: - python-version: ["3.9", "3.10", "3.11", "3.12"] - - steps: - - uses: actions/checkout@v4 - - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v5 - with: - python-version: ${{ matrix.python-version }} - - - name: Install package - run: | - pip install whisperx - - - name: Print packages - run: | - pip list - - - name: Test import - run: | - python -c "import whisperx; print('Successfully imported whisperx')" From f8d11df7270f80a4c9086c75abbf1b20ab2bc988 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Wed, 19 Feb 2025 08:24:04 +0100 Subject: [PATCH 020/118] docs: Update README example commands with generic audio path --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 42df9a53c..2394e0d85 100644 --- a/README.md +++ b/README.md @@ -129,7 +129,7 @@ To **enable Speaker Diarization**, include your Hugging Face access token (read) Run whisper on example segment (using default params, whisper small) add `--highlight_words True` to visualise word timings in the .srt file. - whisperx examples/sample01.wav + whisperx path/to/audio.wav Result using *WhisperX* with forced alignment to wav2vec2.0 large: @@ -143,16 +143,16 @@ https://user-images.githubusercontent.com/36994049/207743923-b4f0d537-29ae-4be2- For increased timestamp accuracy, at the cost of higher gpu mem, use bigger models (bigger alignment model not found to be that helpful, see paper) e.g. - whisperx examples/sample01.wav --model large-v2 --align_model WAV2VEC2_ASR_LARGE_LV60K_960H --batch_size 4 + whisperx path/to/audio.wav --model large-v2 --align_model WAV2VEC2_ASR_LARGE_LV60K_960H --batch_size 4 To label the transcript with speaker ID's (set number of speakers if known e.g. `--min_speakers 2` `--max_speakers 2`): - whisperx examples/sample01.wav --model large-v2 --diarize --highlight_words True + whisperx path/to/audio.wav --model large-v2 --diarize --highlight_words True To run on CPU instead of GPU (and for running on Mac OS X): - whisperx examples/sample01.wav --compute_type int8 + whisperx path/to/audio.wav --compute_type int8 ### Other languages @@ -163,7 +163,7 @@ Currently default models provided for `{en, fr, de, es, it}` via torchaudio pipe #### E.g. German - whisperx --model large-v2 --language de examples/sample_de_01.wav + whisperx --model large-v2 --language de path/to/audio.wav https://user-images.githubusercontent.com/36994049/208298811-e36002ba-3698-4731-97d4-0aebd07e0eb3.mov From 4db839018c2df845176fd9a383987e9299137779 Mon Sep 17 00:00:00 2001 From: Amerogin Kamid <90996980+mtfugin@users.noreply.github.com> Date: Sun, 23 Feb 2025 16:59:48 +0800 Subject: [PATCH 021/118] feat: add Tagalog (tl - Filipino) Phoneme-based ASR Model (#1067) --- whisperx/alignment.py | 1 + 1 file changed, 1 insertion(+) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 3b2fdae9f..552118ede 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -70,6 +70,7 @@ "gl": "ifrz/wav2vec2-large-xlsr-galician", "ka": "xsway/wav2vec2-large-xlsr-georgian", "lv": "jimregan/wav2vec2-large-xlsr-latvian-cv", + "tl": "Khalsuu/filipino-wav2vec2-l-xls-r-300m-official", } From 0d9807adc55a0ba7de8811ca9c9c0c33865e6bb3 Mon Sep 17 00:00:00 2001 From: Xabi Date: Tue, 4 Mar 2025 14:55:30 +0100 Subject: [PATCH 022/118] feat: add Basque alignment model (#1074) --- whisperx/alignment.py | 1 + 1 file changed, 1 insertion(+) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 552118ede..7f7257add 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -71,6 +71,7 @@ "ka": "xsway/wav2vec2-large-xlsr-georgian", "lv": "jimregan/wav2vec2-large-xlsr-latvian-cv", "tl": "Khalsuu/filipino-wav2vec2-l-xls-r-300m-official", + "eu": "gttsehu/wav2vec2-xls-r-300m-bp1-es_eu", } From 8c58c54635cd6ee2d9d8665a3cf789863f6ed700 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Wed, 5 Mar 2025 15:19:23 +0100 Subject: [PATCH 023/118] Revert "feat: add Basque alignment model (#1074)" (#1077) This reverts commit 0d9807adc55a0ba7de8811ca9c9c0c33865e6bb3. --- whisperx/alignment.py | 1 - 1 file changed, 1 deletion(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 7f7257add..552118ede 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -71,7 +71,6 @@ "ka": "xsway/wav2vec2-large-xlsr-georgian", "lv": "jimregan/wav2vec2-large-xlsr-latvian-cv", "tl": "Khalsuu/filipino-wav2vec2-l-xls-r-300m-official", - "eu": "gttsehu/wav2vec2-xls-r-300m-bp1-es_eu", } From 8e538667040f7a7e319612710f3280a98f1a8b7a Mon Sep 17 00:00:00 2001 From: jademlc <68696651+jademlc@users.noreply.github.com> Date: Mon, 24 Mar 2025 10:47:47 +0100 Subject: [PATCH 024/118] feat: pass hotwords argument to get_prompt (#1073) Co-authored-by: Jade Moillic --- whisperx/asr.py | 1 + 1 file changed, 1 insertion(+) diff --git a/whisperx/asr.py b/whisperx/asr.py index 6de94900f..70cfa8359 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -50,6 +50,7 @@ def generate_segment_batched( previous_tokens, without_timestamps=options.without_timestamps, prefix=options.prefix, + hotwords=options.hotwords ) encoder_output = self.encode(features) From e7712f496e3dca75e4373353197b0f4a8b704952 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Tue, 25 Mar 2025 16:13:55 +0100 Subject: [PATCH 025/118] refactor: update import statements to use explicit module paths across multiple files --- whisperx/SubtitlesProcessor.py | 3 +-- whisperx/__init__.py | 11 +++++++---- whisperx/__main__.py | 2 +- whisperx/alignment.py | 6 +++--- whisperx/asr.py | 7 ++++--- whisperx/audio.py | 2 +- whisperx/diarize.py | 4 ++-- whisperx/transcribe.py | 12 ++++++------ whisperx/vads/__init__.py | 6 +++--- whisperx/vads/pyannote.py | 4 +--- 10 files changed, 29 insertions(+), 28 deletions(-) diff --git a/whisperx/SubtitlesProcessor.py b/whisperx/SubtitlesProcessor.py index 351b88306..1a50ec801 100644 --- a/whisperx/SubtitlesProcessor.py +++ b/whisperx/SubtitlesProcessor.py @@ -1,6 +1,5 @@ import math -from .conjunctions import get_conjunctions, get_comma -from typing import TextIO +from whisperx.conjunctions import get_conjunctions, get_comma def normal_round(n): if n - math.floor(n) < 0.5: diff --git a/whisperx/__init__.py b/whisperx/__init__.py index 92e6d4241..8ab8a26cf 100644 --- a/whisperx/__init__.py +++ b/whisperx/__init__.py @@ -1,4 +1,7 @@ -from .alignment import load_align_model, align -from .audio import load_audio -from .diarize import assign_word_speakers, DiarizationPipeline -from .asr import load_model +from whisperx.alignment import load_align_model as load_align_model, align as align +from whisperx.asr import load_model as load_model +from whisperx.audio import load_audio as load_audio +from whisperx.diarize import ( + assign_word_speakers as assign_word_speakers, + DiarizationPipeline as DiarizationPipeline, +) diff --git a/whisperx/__main__.py b/whisperx/__main__.py index bc9b04a39..41412c8f4 100644 --- a/whisperx/__main__.py +++ b/whisperx/__main__.py @@ -1,4 +1,4 @@ -from .transcribe import cli +from whisperx.transcribe import cli cli() diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 552118ede..b77a7f1bf 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -13,9 +13,9 @@ import torchaudio from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor -from .audio import SAMPLE_RATE, load_audio -from .utils import interpolate_nans -from .types import ( +from whisperx.audio import SAMPLE_RATE, load_audio +from whisperx.utils import interpolate_nans +from whisperx.types import ( AlignedTranscriptionResult, SingleSegment, SingleAlignedSegment, diff --git a/whisperx/asr.py b/whisperx/asr.py index 70cfa8359..c47651675 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -11,9 +11,10 @@ from transformers import Pipeline from transformers.pipelines.pt_utils import PipelineIterator -from .audio import N_SAMPLES, SAMPLE_RATE, load_audio, log_mel_spectrogram -from .types import SingleSegment, TranscriptionResult -from .vads import Vad, Silero, Pyannote +from whisperx.audio import N_SAMPLES, SAMPLE_RATE, load_audio, log_mel_spectrogram +from whisperx.types import SingleSegment, TranscriptionResult +from whisperx.vads import Vad, Silero, Pyannote + def find_numeral_symbol_tokens(tokenizer): numeral_symbol_tokens = [] diff --git a/whisperx/audio.py b/whisperx/audio.py index 42f97b882..63a53ca32 100644 --- a/whisperx/audio.py +++ b/whisperx/audio.py @@ -7,7 +7,7 @@ import torch import torch.nn.functional as F -from .utils import exact_div +from whisperx.utils import exact_div # hard-coded audio hyperparameters SAMPLE_RATE = 16000 diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 5b685b373..97a7813cb 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -4,8 +4,8 @@ from typing import Optional, Union import torch -from .audio import load_audio, SAMPLE_RATE -from .types import TranscriptionResult, AlignedTranscriptionResult +from whisperx.audio import load_audio, SAMPLE_RATE +from whisperx.types import TranscriptionResult, AlignedTranscriptionResult class DiarizationPipeline: diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index ae61ed1d9..a67787c1b 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -6,12 +6,12 @@ import numpy as np import torch -from .alignment import align, load_align_model -from .asr import load_model -from .audio import load_audio -from .diarize import DiarizationPipeline, assign_word_speakers -from .types import AlignedTranscriptionResult, TranscriptionResult -from .utils import ( +from whisperx.alignment import align, load_align_model +from whisperx.asr import load_model +from whisperx.audio import load_audio +from whisperx.diarize import DiarizationPipeline, assign_word_speakers +from whisperx.types import AlignedTranscriptionResult, TranscriptionResult +from whisperx.utils import ( LANGUAGES, TO_LANGUAGE_CODE, get_writer, diff --git a/whisperx/vads/__init__.py b/whisperx/vads/__init__.py index 9dd82bf71..834c794be 100644 --- a/whisperx/vads/__init__.py +++ b/whisperx/vads/__init__.py @@ -1,3 +1,3 @@ -from whisperx.vads.pyannote import Pyannote -from whisperx.vads.silero import Silero -from whisperx.vads.vad import Vad \ No newline at end of file +from whisperx.vads.pyannote import Pyannote as Pyannote +from whisperx.vads.silero import Silero as Silero +from whisperx.vads.vad import Vad as Vad diff --git a/whisperx/vads/pyannote.py b/whisperx/vads/pyannote.py index 543fb81aa..62225f0a9 100644 --- a/whisperx/vads/pyannote.py +++ b/whisperx/vads/pyannote.py @@ -1,6 +1,4 @@ -import hashlib import os -import urllib from typing import Callable, Text, Union from typing import Optional @@ -12,11 +10,11 @@ from pyannote.audio.pipelines.utils import PipelineModel from pyannote.core import Annotation, SlidingWindowFeature from pyannote.core import Segment -from tqdm import tqdm from whisperx.diarize import Segment as SegmentX from whisperx.vads.vad import Vad + def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, use_auth_token=None, model_fp=None): model_dir = torch.hub._get_torch_home() From a7564c2ad607d72c44f799cb19cdd9ed359992cb Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Tue, 25 Mar 2025 17:02:02 +0100 Subject: [PATCH 026/118] docs: update installation instructions --- README.md | 49 ++++++++++++++++++------------------------------- 1 file changed, 18 insertions(+), 31 deletions(-) diff --git a/README.md b/README.md index 2394e0d85..08eb0757e 100644 --- a/README.md +++ b/README.md @@ -62,54 +62,41 @@ This repository provides fast automatic speech recognition (70x realtime with la - Paper drop🎓👨‍🏫! Please see our [ArxiV preprint](https://arxiv.org/abs/2303.00747) for benchmarking and details of WhisperX. We also introduce more efficient batch inference resulting in large-v2 with *60-70x REAL TIME speed.

Setup ⚙️

-Tested for PyTorch 2.0, Python 3.10 (use other versions at your own risk!) -GPU execution requires the NVIDIA libraries cuBLAS 11.x and cuDNN 8.x to be installed on the system. Please refer to the [CTranslate2 documentation](https://opennmt.net/CTranslate2/installation.html). +### 1. Simple Installation (Recommended) - -### 1. Create Python3.10 environment - -`conda create --name whisperx python=3.10` - -`conda activate whisperx` - - -### 2. Install PyTorch, e.g. for Linux and Windows CUDA11.8: - -`conda install pytorch==2.0.0 torchaudio==2.0.0 pytorch-cuda=11.8 -c pytorch -c nvidia` - -See other methods [here.](https://pytorch.org/get-started/previous-versions/#v200) - -### 3. Install WhisperX - -You have several installation options: - -#### Option A: Stable Release (recommended) -Install the latest stable version from PyPI: +The easiest way to install WhisperX is through PyPi: ```bash pip install whisperx ``` -#### Option B: Development Version -Install the latest development version directly from GitHub (may be unstable): +Or if using [uvx](https://docs.astral.sh/uv/guides/tools/#running-tools): ```bash -pip install git+https://github.com/m-bain/whisperx.git +uvx whisperx ``` -If already installed, update to the most recent commit: +### 2. Advanced Installation Options + +These installation methods are for developers or users with specific needs. If you're not sure, stick with the simple installation above. + +#### Option A: Install from GitHub + +To install directly from the GitHub repository: ```bash -pip install git+https://github.com/m-bain/whisperx.git --upgrade +uvx git+https://github.com/m-bain/whisperX.git ``` -#### Option C: Development Mode -If you wish to modify the package, clone and install in editable mode: +#### Option B: Developer Installation + +If you want to modify the code or contribute to the project: + ```bash git clone https://github.com/m-bain/whisperX.git cd whisperX -pip install -e . +uv sync --all-extras --dev ``` > **Note**: The development version may contain experimental features and bugs. Use the stable PyPI release for production environments. @@ -117,12 +104,12 @@ pip install -e . You may also need to install ffmpeg, rust etc. Follow openAI instructions here https://github.com/openai/whisper#setup. ### Speaker Diarization + To **enable Speaker Diarization**, include your Hugging Face access token (read) that you can generate from [Here](https://huggingface.co/settings/tokens) after the `--hf_token` argument and accept the user agreement for the following models: [Segmentation](https://huggingface.co/pyannote/segmentation-3.0) and [Speaker-Diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) (if you choose to use Speaker-Diarization 2.x, follow requirements [here](https://huggingface.co/pyannote/speaker-diarization) instead.) > **Note**
> As of Oct 11, 2023, there is a known issue regarding slow performance with pyannote/Speaker-Diarization-3.0 in whisperX. It is due to dependency conflicts between faster-whisper and pyannote-audio 3.0.0. Please see [this issue](https://github.com/m-bain/whisperX/issues/499) for more details and potential workarounds. -

Usage 💬 (command line)

### English From f10dbf6ab1717e84db7733df9c0b21658ee68f9b Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Tue, 25 Mar 2025 18:48:57 +0100 Subject: [PATCH 027/118] fix: update setuptools configuration to include package discovery for whisperx --- pyproject.toml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 9249fd9df..4b6c23659 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -29,5 +29,8 @@ whisperx = "whisperx.transcribe:cli" requires = ["setuptools"] [tool.setuptools] -packages = ["whisperx"] include-package-data = true + +[tool.setuptools.packages.find] +where = ["."] +include = ["whisperx*"] \ No newline at end of file From 0aed8745890f12ecfe0b2d9c4ba62bcdfb16f94e Mon Sep 17 00:00:00 2001 From: Yan Cheng Cheok Date: Fri, 11 Apr 2025 21:49:00 +0800 Subject: [PATCH 028/118] Remove duplicated item "lv": "latvian" --- whisperx/utils.py | 1 - 1 file changed, 1 deletion(-) diff --git a/whisperx/utils.py b/whisperx/utils.py index 4ccd77c12..dfe3cf2e9 100644 --- a/whisperx/utils.py +++ b/whisperx/utils.py @@ -106,7 +106,6 @@ "jw": "javanese", "su": "sundanese", "yue": "cantonese", - "lv": "latvian", } # language code lookup by name, with a few language aliases From cd59f21d1a0fe1269d153a1aba4925cdc24cc4aa Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 1 May 2025 09:54:19 +0200 Subject: [PATCH 029/118] fix: downgrade ctranslate2 dependency version --- pyproject.toml | 4 ++-- uv.lock | 48 +++++++++++++++++++----------------------------- 2 files changed, 21 insertions(+), 31 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 4b6c23659..ff95d4187 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -9,11 +9,11 @@ requires-python = ">=3.9, <3.13" license = { text = "BSD-2-Clause" } dependencies = [ - "ctranslate2>=4.5.0", + "ctranslate2<4.5.0", "faster-whisper>=1.1.1", "nltk>=3.9.1", "numpy>=2.0.2", - "onnxruntime==1.19", + "onnxruntime>=1.19", "pandas>=2.2.3", "pyannote-audio>=3.3.2", "torch>=2.5.1", diff --git a/uv.lock b/uv.lock index 72ea22c36..7efc42e91 100644 --- a/uv.lock +++ b/uv.lock @@ -485,7 +485,7 @@ wheels = [ [[package]] name = "ctranslate2" -version = "4.5.0" +version = "4.4.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" }, @@ -494,22 +494,22 @@ dependencies = [ { name = "setuptools" }, ] wheels = [ - { url = "https://files.pythonhosted.org/packages/c9/67/ffa1fcda2c8265a710d34b12b6bf6d6ce904d8cad99a88479c0d3561505b/ctranslate2-4.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:241da685f8f7cb10b7afceeb3d879f778b56e6a1d55fc2964ddc949c80c9c7bb", size = 1354001 }, - { url = 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From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 1 May 2025 10:43:02 +0200 Subject: [PATCH 030/118] feat: add version and Python version arguments to CLI --- whisperx/transcribe.py | 51 +++++++++++++++++++++++++++++++++++------- 1 file changed, 43 insertions(+), 8 deletions(-) diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index a67787c1b..f6aa2798a 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -1,7 +1,10 @@ import argparse import gc import os +import sys import warnings +import importlib.metadata +import platform import numpy as np import torch @@ -85,6 +88,8 @@ def cli(): parser.add_argument("--hf_token", type=str, default=None, help="Hugging Face Access Token to access PyAnnote gated models") parser.add_argument("--print_progress", type=str2bool, default = False, help = "if True, progress will be printed in transcribe() and align() methods.") + parser.add_argument("--version", "-V", action="version", version=f"%(prog)s {importlib.metadata.version('whisperx')}",help="Show whisperx version information and exit") + parser.add_argument("--python-version", "-P", action="version", version=f"Python {platform.python_version()} ({platform.python_implementation()})",help="Show python version information and exit") # fmt: on args = parser.parse_args().__dict__ @@ -138,7 +143,9 @@ def cli(): f"{model_name} is an English-only model but received '{args['language']}'; using English instead." ) args["language"] = "en" - align_language = args["language"] if args["language"] is not None else "en" # default to loading english if not specified + align_language = ( + args["language"] if args["language"] is not None else "en" + ) # default to loading english if not specified temperature = args.pop("temperature") if (increment := args.pop("temperature_increment_on_fallback")) is not None: @@ -174,12 +181,29 @@ def cli(): if args["max_line_count"] and not args["max_line_width"]: warnings.warn("--max_line_count has no effect without --max_line_width") writer_args = {arg: args.pop(arg) for arg in word_options} - + # Part 1: VAD & ASR Loop results = [] tmp_results = [] # model = load_model(model_name, device=device, download_root=model_dir) - model = load_model(model_name, device=device, device_index=device_index, download_root=model_dir, compute_type=compute_type, language=args['language'], asr_options=asr_options, vad_method=vad_method, vad_options={"chunk_size":chunk_size, "vad_onset": vad_onset, "vad_offset": vad_offset}, task=task, local_files_only=model_cache_only, threads=faster_whisper_threads) + model = load_model( + model_name, + device=device, + device_index=device_index, + download_root=model_dir, + compute_type=compute_type, + language=args["language"], + asr_options=asr_options, + vad_method=vad_method, + vad_options={ + "chunk_size": chunk_size, + "vad_onset": vad_onset, + "vad_offset": vad_offset, + }, + task=task, + local_files_only=model_cache_only, + threads=faster_whisper_threads, + ) for audio_path in args.pop("audio"): audio = load_audio(audio_path) @@ -203,7 +227,9 @@ def cli(): if not no_align: tmp_results = results results = [] - align_model, align_metadata = load_align_model(align_language, device, model_name=align_model) + align_model, align_metadata = load_align_model( + align_language, device, model_name=align_model + ) for result, audio_path in tmp_results: # >> Align if len(tmp_results) > 1: @@ -215,8 +241,12 @@ def cli(): if align_model is not None and len(result["segments"]) > 0: if result.get("language", "en") != align_metadata["language"]: # load new language - print(f"New language found ({result['language']})! Previous was ({align_metadata['language']}), loading new alignment model for new language...") - align_model, align_metadata = load_align_model(result["language"], device) + print( + f"New language found ({result['language']})! Previous was ({align_metadata['language']}), loading new alignment model for new language..." + ) + align_model, align_metadata = load_align_model( + result["language"], device + ) print(">>Performing alignment...") result: AlignedTranscriptionResult = align( result["segments"], @@ -239,13 +269,17 @@ def cli(): # >> Diarize if diarize: if hf_token is None: - print("Warning, no --hf_token used, needs to be saved in environment variable, otherwise will throw error loading diarization model...") + print( + "Warning, no --hf_token used, needs to be saved in environment variable, otherwise will throw error loading diarization model..." + ) tmp_results = results print(">>Performing diarization...") results = [] diarize_model = DiarizationPipeline(use_auth_token=hf_token, device=device) for result, input_audio_path in tmp_results: - diarize_segments = diarize_model(input_audio_path, min_speakers=min_speakers, max_speakers=max_speakers) + diarize_segments = diarize_model( + input_audio_path, min_speakers=min_speakers, max_speakers=max_speakers + ) result = assign_word_speakers(diarize_segments, result) results.append((result, input_audio_path)) # >> Write @@ -253,5 +287,6 @@ def cli(): result["language"] = align_language writer(result, audio_path, writer_args) + if __name__ == "__main__": cli() From f5b40b5366a6bdb0dcd01fe8b462f266051e0918 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 1 May 2025 10:43:08 +0200 Subject: [PATCH 031/118] chore: update version to 3.3.3 in pyproject.toml and uv.lock --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index ff95d4187..89cd4194d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.3.1" +version = "3.3.3" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.13" diff --git a/uv.lock b/uv.lock index 7efc42e91..2be00836e 100644 --- a/uv.lock +++ b/uv.lock @@ -2787,7 +2787,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.3.1" +version = "3.3.3" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, From d2a493e91044be7161bd32e2bd0fde8a7ebf44b5 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 1 May 2025 14:15:13 +0200 Subject: [PATCH 032/118] refactor: implement lazy loading for module imports in whisperx --- whisperx/__init__.py | 47 +++++++++++++++++++++++++++++++++++++------- 1 file changed, 40 insertions(+), 7 deletions(-) diff --git a/whisperx/__init__.py b/whisperx/__init__.py index 8ab8a26cf..6356fdf7b 100644 --- a/whisperx/__init__.py +++ b/whisperx/__init__.py @@ -1,7 +1,40 @@ -from whisperx.alignment import load_align_model as load_align_model, align as align -from whisperx.asr import load_model as load_model -from whisperx.audio import load_audio as load_audio -from whisperx.diarize import ( - assign_word_speakers as assign_word_speakers, - DiarizationPipeline as DiarizationPipeline, -) +import importlib + + +def _lazy_import(name): + module = importlib.import_module(f"whisperx.{name}") + return module + + +def load_align_model(*args, **kwargs): + alignment = _lazy_import("alignment") + return alignment.load_align_model(*args, **kwargs) + + +def align(*args, **kwargs): + alignment = _lazy_import("alignment") + return alignment.align(*args, **kwargs) + + +def load_model(*args, **kwargs): + asr = _lazy_import("asr") + return asr.load_model(*args, **kwargs) + + +def load_audio(*args, **kwargs): + audio = _lazy_import("audio") + return audio.load_audio(*args, **kwargs) + + +def assign_word_speakers(*args, **kwargs): + diarize = _lazy_import("diarize") + return diarize.assign_word_speakers(*args, **kwargs) + + +class DiarizationPipeline: + def __init__(self, *args, **kwargs): + diarize = _lazy_import("diarize") + self._pipeline = diarize.DiarizationPipeline(*args, **kwargs) + + def __getattr__(self, name): + return getattr(self._pipeline, name) From 7d36b832f9bf86a219b39a74e0b50d974c5ebe42 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 1 May 2025 14:19:42 +0200 Subject: [PATCH 033/118] refactor: update CLI entry point --- pyproject.toml | 2 +- whisperx/__main__.py | 87 +++++++++++++++++++++++++++++++++++++++- whisperx/transcribe.py | 90 ++++-------------------------------------- 3 files changed, 94 insertions(+), 85 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 89cd4194d..2b0bb7359 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,7 +23,7 @@ dependencies = [ [project.scripts] -whisperx = "whisperx.transcribe:cli" +whisperx = "whisperx.__main__:cli" [build-system] requires = ["setuptools"] diff --git a/whisperx/__main__.py b/whisperx/__main__.py index 41412c8f4..6da7b8740 100644 --- a/whisperx/__main__.py +++ b/whisperx/__main__.py @@ -1,4 +1,87 @@ -from whisperx.transcribe import cli +import argparse +import importlib.metadata +import platform +import torch -cli() +from whisperx.utils import (LANGUAGES, TO_LANGUAGE_CODE, optional_float, + optional_int, str2bool) + + +def cli(): + # fmt: off + parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) + parser.add_argument("audio", nargs="+", type=str, help="audio file(s) to transcribe") + parser.add_argument("--model", default="small", help="name of the Whisper model to use") + parser.add_argument("--model_cache_only", type=str2bool, default=False, help="If True, will not attempt to download models, instead using cached models from --model_dir") + parser.add_argument("--model_dir", type=str, default=None, help="the path to save model files; uses ~/.cache/whisper by default") + parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu", help="device to use for PyTorch inference") + parser.add_argument("--device_index", default=0, type=int, help="device index to use for FasterWhisper inference") + parser.add_argument("--batch_size", default=8, type=int, help="the preferred batch size for inference") + parser.add_argument("--compute_type", default="float16", type=str, choices=["float16", "float32", "int8"], help="compute type for computation") + + parser.add_argument("--output_dir", "-o", type=str, default=".", help="directory to save the outputs") + parser.add_argument("--output_format", "-f", type=str, default="all", choices=["all", "srt", "vtt", "txt", "tsv", "json", "aud"], help="format of the output file; if not specified, all available formats will be produced") + parser.add_argument("--verbose", type=str2bool, default=True, help="whether to print out the progress and debug messages") + + parser.add_argument("--task", type=str, default="transcribe", choices=["transcribe", "translate"], help="whether to perform X->X speech recognition ('transcribe') or X->English translation ('translate')") + parser.add_argument("--language", type=str, default=None, choices=sorted(LANGUAGES.keys()) + sorted([k.title() for k in TO_LANGUAGE_CODE.keys()]), help="language spoken in the audio, specify None to perform language detection") + + # alignment params + parser.add_argument("--align_model", default=None, help="Name of phoneme-level ASR model to do alignment") + parser.add_argument("--interpolate_method", default="nearest", choices=["nearest", "linear", "ignore"], help="For word .srt, method to assign timestamps to non-aligned words, or merge them into neighbouring.") + parser.add_argument("--no_align", action='store_true', help="Do not perform phoneme alignment") + parser.add_argument("--return_char_alignments", action='store_true', help="Return character-level alignments in the output json file") + + # vad params + parser.add_argument("--vad_method", type=str, default="pyannote", choices=["pyannote", "silero"], help="VAD method to be used") + parser.add_argument("--vad_onset", type=float, default=0.500, help="Onset threshold for VAD (see pyannote.audio), reduce this if speech is not being detected") + parser.add_argument("--vad_offset", type=float, default=0.363, help="Offset threshold for VAD (see pyannote.audio), reduce this if speech is not being detected.") + parser.add_argument("--chunk_size", type=int, default=30, help="Chunk size for merging VAD segments. Default is 30, reduce this if the chunk is too long.") + + # diarization params + parser.add_argument("--diarize", action="store_true", help="Apply diarization to assign speaker labels to each segment/word") + parser.add_argument("--min_speakers", default=None, type=int, help="Minimum number of speakers to in audio file") + parser.add_argument("--max_speakers", default=None, type=int, help="Maximum number of speakers to in audio file") + + parser.add_argument("--temperature", type=float, default=0, help="temperature to use for sampling") + parser.add_argument("--best_of", type=optional_int, default=5, help="number of candidates when sampling with non-zero temperature") + parser.add_argument("--beam_size", type=optional_int, default=5, help="number of beams in beam search, only applicable when temperature is zero") + parser.add_argument("--patience", type=float, default=1.0, help="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") + parser.add_argument("--length_penalty", type=float, default=1.0, help="optional token length penalty coefficient (alpha) as in https://arxiv.org/abs/1609.08144, uses simple length normalization by default") + + parser.add_argument("--suppress_tokens", type=str, default="-1", help="comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations") + parser.add_argument("--suppress_numerals", action="store_true", help="whether to suppress numeric symbols and currency symbols during sampling, since wav2vec2 cannot align them correctly") + + parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.") + parser.add_argument("--condition_on_previous_text", type=str2bool, default=False, help="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") + parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default") + + parser.add_argument("--temperature_increment_on_fallback", type=optional_float, default=0.2, help="temperature to increase when falling back when the decoding fails to meet either of the thresholds below") + parser.add_argument("--compression_ratio_threshold", type=optional_float, default=2.4, help="if the gzip compression ratio is higher than this value, treat the decoding as failed") + parser.add_argument("--logprob_threshold", type=optional_float, default=-1.0, help="if the average log probability is lower than this value, treat the decoding as failed") + parser.add_argument("--no_speech_threshold", type=optional_float, default=0.6, help="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") + + parser.add_argument("--max_line_width", type=optional_int, default=None, help="(not possible with --no_align) the maximum number of characters in a line before breaking the line") + parser.add_argument("--max_line_count", type=optional_int, default=None, help="(not possible with --no_align) the maximum number of lines in a segment") + parser.add_argument("--highlight_words", type=str2bool, default=False, help="(not possible with --no_align) underline each word as it is spoken in srt and vtt") + parser.add_argument("--segment_resolution", type=str, default="sentence", choices=["sentence", "chunk"], help="(not possible with --no_align) the maximum number of characters in a line before breaking the line") + + parser.add_argument("--threads", type=optional_int, default=0, help="number of threads used by torch for CPU inference; supercedes MKL_NUM_THREADS/OMP_NUM_THREADS") + + parser.add_argument("--hf_token", type=str, default=None, help="Hugging Face Access Token to access PyAnnote gated models") + + parser.add_argument("--print_progress", type=str2bool, default = False, help = "if True, progress will be printed in transcribe() and align() methods.") + parser.add_argument("--version", "-V", action="version", version=f"%(prog)s {importlib.metadata.version('whisperx')}",help="Show whisperx version information and exit") + parser.add_argument("--python-version", "-P", action="version", version=f"Python {platform.python_version()} ({platform.python_implementation()})",help="Show python version information and exit") + # fmt: on + + args = parser.parse_args().__dict__ + + from whisperx.transcribe import transcribe_task + + transcribe_task(args, parser) + + +if __name__ == "__main__": + cli() diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index f6aa2798a..f56782477 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -1,10 +1,7 @@ import argparse import gc import os -import sys import warnings -import importlib.metadata -import platform import numpy as np import torch @@ -14,85 +11,18 @@ from whisperx.audio import load_audio from whisperx.diarize import DiarizationPipeline, assign_word_speakers from whisperx.types import AlignedTranscriptionResult, TranscriptionResult -from whisperx.utils import ( - LANGUAGES, - TO_LANGUAGE_CODE, - get_writer, - optional_float, - optional_int, - str2bool, -) +from whisperx.utils import LANGUAGES, TO_LANGUAGE_CODE, get_writer -def cli(): - # fmt: off - parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) - parser.add_argument("audio", nargs="+", type=str, help="audio file(s) to transcribe") - parser.add_argument("--model", default="small", help="name of the Whisper model to use") - parser.add_argument("--model_cache_only", type=str2bool, default=False, help="If True, will not attempt to download models, instead using cached models from --model_dir") - parser.add_argument("--model_dir", type=str, default=None, help="the path to save model files; uses ~/.cache/whisper by default") - parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu", help="device to use for PyTorch inference") - parser.add_argument("--device_index", default=0, type=int, help="device index to use for FasterWhisper inference") - parser.add_argument("--batch_size", default=8, type=int, help="the preferred batch size for inference") - parser.add_argument("--compute_type", default="float16", type=str, choices=["float16", "float32", "int8"], help="compute type for computation") - - parser.add_argument("--output_dir", "-o", type=str, default=".", help="directory to save the outputs") - parser.add_argument("--output_format", "-f", type=str, default="all", choices=["all", "srt", "vtt", "txt", "tsv", "json", "aud"], help="format of the output file; if not specified, all available formats will be produced") - parser.add_argument("--verbose", type=str2bool, default=True, help="whether to print out the progress and debug messages") - - parser.add_argument("--task", type=str, default="transcribe", choices=["transcribe", "translate"], help="whether to perform X->X speech recognition ('transcribe') or X->English translation ('translate')") - parser.add_argument("--language", type=str, default=None, choices=sorted(LANGUAGES.keys()) + sorted([k.title() for k in TO_LANGUAGE_CODE.keys()]), help="language spoken in the audio, specify None to perform language detection") - - # alignment params - parser.add_argument("--align_model", default=None, help="Name of phoneme-level ASR model to do alignment") - parser.add_argument("--interpolate_method", default="nearest", choices=["nearest", "linear", "ignore"], help="For word .srt, method to assign timestamps to non-aligned words, or merge them into neighbouring.") - parser.add_argument("--no_align", action='store_true', help="Do not perform phoneme alignment") - parser.add_argument("--return_char_alignments", action='store_true', help="Return character-level alignments in the output json file") - - # vad params - parser.add_argument("--vad_method", type=str, default="pyannote", choices=["pyannote", "silero"], help="VAD method to be used") - parser.add_argument("--vad_onset", type=float, default=0.500, help="Onset threshold for VAD (see pyannote.audio), reduce this if speech is not being detected") - parser.add_argument("--vad_offset", type=float, default=0.363, help="Offset threshold for VAD (see pyannote.audio), reduce this if speech is not being detected.") - parser.add_argument("--chunk_size", type=int, default=30, help="Chunk size for merging VAD segments. Default is 30, reduce this if the chunk is too long.") - - # diarization params - parser.add_argument("--diarize", action="store_true", help="Apply diarization to assign speaker labels to each segment/word") - parser.add_argument("--min_speakers", default=None, type=int, help="Minimum number of speakers to in audio file") - parser.add_argument("--max_speakers", default=None, type=int, help="Maximum number of speakers to in audio file") - - parser.add_argument("--temperature", type=float, default=0, help="temperature to use for sampling") - parser.add_argument("--best_of", type=optional_int, default=5, help="number of candidates when sampling with non-zero temperature") - parser.add_argument("--beam_size", type=optional_int, default=5, help="number of beams in beam search, only applicable when temperature is zero") - parser.add_argument("--patience", type=float, default=1.0, help="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") - parser.add_argument("--length_penalty", type=float, default=1.0, help="optional token length penalty coefficient (alpha) as in https://arxiv.org/abs/1609.08144, uses simple length normalization by default") - - parser.add_argument("--suppress_tokens", type=str, default="-1", help="comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations") - parser.add_argument("--suppress_numerals", action="store_true", help="whether to suppress numeric symbols and currency symbols during sampling, since wav2vec2 cannot align them correctly") +def transcribe_task(args: dict, parser: argparse.ArgumentParser): + """Transcription task to be called from CLI. - parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.") - parser.add_argument("--condition_on_previous_text", type=str2bool, default=False, help="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") - parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default") - - parser.add_argument("--temperature_increment_on_fallback", type=optional_float, default=0.2, help="temperature to increase when falling back when the decoding fails to meet either of the thresholds below") - parser.add_argument("--compression_ratio_threshold", type=optional_float, default=2.4, help="if the gzip compression ratio is higher than this value, treat the decoding as failed") - parser.add_argument("--logprob_threshold", type=optional_float, default=-1.0, help="if the average log probability is lower than this value, treat the decoding as failed") - parser.add_argument("--no_speech_threshold", type=optional_float, default=0.6, help="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") - - parser.add_argument("--max_line_width", type=optional_int, default=None, help="(not possible with --no_align) the maximum number of characters in a line before breaking the line") - parser.add_argument("--max_line_count", type=optional_int, default=None, help="(not possible with --no_align) the maximum number of lines in a segment") - parser.add_argument("--highlight_words", type=str2bool, default=False, help="(not possible with --no_align) underline each word as it is spoken in srt and vtt") - parser.add_argument("--segment_resolution", type=str, default="sentence", choices=["sentence", "chunk"], help="(not possible with --no_align) the maximum number of characters in a line before breaking the line") - - parser.add_argument("--threads", type=optional_int, default=0, help="number of threads used by torch for CPU inference; supercedes MKL_NUM_THREADS/OMP_NUM_THREADS") - - parser.add_argument("--hf_token", type=str, default=None, help="Hugging Face Access Token to access PyAnnote gated models") - - parser.add_argument("--print_progress", type=str2bool, default = False, help = "if True, progress will be printed in transcribe() and align() methods.") - parser.add_argument("--version", "-V", action="version", version=f"%(prog)s {importlib.metadata.version('whisperx')}",help="Show whisperx version information and exit") - parser.add_argument("--python-version", "-P", action="version", version=f"Python {platform.python_version()} ({platform.python_implementation()})",help="Show python version information and exit") - # fmt: on + Args: + args: Dictionary of command-line arguments. + parser: argparse.ArgumentParser object. + """ + # fmt: off - args = parser.parse_args().__dict__ model_name: str = args.pop("model") batch_size: int = args.pop("batch_size") model_dir: str = args.pop("model_dir") @@ -286,7 +216,3 @@ def cli(): for result, audio_path in results: result["language"] = align_language writer(result, audio_path, writer_args) - - -if __name__ == "__main__": - cli() From 36d552cad33d6a0617f6a686e3b2acff238dc702 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 2 May 2025 13:04:24 +0200 Subject: [PATCH 034/118] fix: remove DiarizationPipeline from public API --- README.md | 82 +++++++++++++++++++------------------------- whisperx/__init__.py | 9 ----- 2 files changed, 35 insertions(+), 56 deletions(-) diff --git a/README.md b/README.md index 08eb0757e..97f827bed 100644 --- a/README.md +++ b/README.md @@ -22,26 +22,20 @@

- whisperx-arch - - - This repository provides fast automatic speech recognition (70x realtime with large-v2) with word-level timestamps and speaker diarization. - ⚡️ Batched inference for 70x realtime transcription using whisper large-v2 - 🪶 [faster-whisper](https://github.com/guillaumekln/faster-whisper) backend, requires <8GB gpu memory for large-v2 with beam_size=5 - 🎯 Accurate word-level timestamps using wav2vec2 alignment -- 👯‍♂️ Multispeaker ASR using speaker diarization from [pyannote-audio](https://github.com/pyannote/pyannote-audio) (speaker ID labels) +- 👯‍♂️ Multispeaker ASR using speaker diarization from [pyannote-audio](https://github.com/pyannote/pyannote-audio) (speaker ID labels) - 🗣️ VAD preprocessing, reduces hallucination & batching with no WER degradation - - **Whisper** is an ASR model [developed by OpenAI](https://github.com/openai/whisper), trained on a large dataset of diverse audio. Whilst it does produces highly accurate transcriptions, the corresponding timestamps are at the utterance-level, not per word, and can be inaccurate by several seconds. OpenAI's whisper does not natively support batching. **Phoneme-Based ASR** A suite of models finetuned to recognise the smallest unit of speech distinguishing one word from another, e.g. the element p in "tap". A popular example model is [wav2vec2.0](https://huggingface.co/facebook/wav2vec2-large-960h-lv60-self). @@ -54,12 +48,12 @@ This repository provides fast automatic speech recognition (70x realtime with la

New🚨

-- 1st place at [Ego4d transcription challenge](https://eval.ai/web/challenges/challenge-page/1637/leaderboard/3931/WER) 🏆 -- _WhisperX_ accepted at INTERSPEECH 2023 +- 1st place at [Ego4d transcription challenge](https://eval.ai/web/challenges/challenge-page/1637/leaderboard/3931/WER) 🏆 +- _WhisperX_ accepted at INTERSPEECH 2023 - v3 transcript segment-per-sentence: using nltk sent_tokenize for better subtitlting & better diarization - v3 released, 70x speed-up open-sourced. Using batched whisper with [faster-whisper](https://github.com/guillaumekln/faster-whisper) backend! - v2 released, code cleanup, imports whisper library VAD filtering is now turned on by default, as in the paper. -- Paper drop🎓👨‍🏫! Please see our [ArxiV preprint](https://arxiv.org/abs/2303.00747) for benchmarking and details of WhisperX. We also introduce more efficient batch inference resulting in large-v2 with *60-70x REAL TIME speed. +- Paper drop🎓👨‍🏫! Please see our [ArxiV preprint](https://arxiv.org/abs/2303.00747) for benchmarking and details of WhisperX. We also introduce more efficient batch inference resulting in large-v2 with \*60-70x REAL TIME speed.

Setup ⚙️

@@ -118,8 +112,7 @@ Run whisper on example segment (using default params, whisper small) add `--high whisperx path/to/audio.wav - -Result using *WhisperX* with forced alignment to wav2vec2.0 large: +Result using _WhisperX_ with forced alignment to wav2vec2.0 large: https://user-images.githubusercontent.com/36994049/208253969-7e35fe2a-7541-434a-ae91-8e919540555d.mp4 @@ -127,12 +120,10 @@ Compare this to original whisper out the box, where many transcriptions are out https://user-images.githubusercontent.com/36994049/207743923-b4f0d537-29ae-4be2-b404-bb941db73652.mov - For increased timestamp accuracy, at the cost of higher gpu mem, use bigger models (bigger alignment model not found to be that helpful, see paper) e.g. whisperx path/to/audio.wav --model large-v2 --align_model WAV2VEC2_ASR_LARGE_LV60K_960H --batch_size 4 - To label the transcript with speaker ID's (set number of speakers if known e.g. `--min_speakers 2` `--max_speakers 2`): whisperx path/to/audio.wav --model large-v2 --diarize --highlight_words True @@ -143,27 +134,26 @@ To run on CPU instead of GPU (and for running on Mac OS X): ### Other languages -The phoneme ASR alignment model is *language-specific*, for tested languages these models are [automatically picked from torchaudio pipelines or huggingface](https://github.com/m-bain/whisperX/blob/f2da2f858e99e4211fe4f64b5f2938b007827e17/whisperx/alignment.py#L24-L58). +The phoneme ASR alignment model is _language-specific_, for tested languages these models are [automatically picked from torchaudio pipelines or huggingface](https://github.com/m-bain/whisperX/blob/f2da2f858e99e4211fe4f64b5f2938b007827e17/whisperx/alignment.py#L24-L58). Just pass in the `--language` code, and use the whisper `--model large`. Currently default models provided for `{en, fr, de, es, it}` via torchaudio pipelines and many other languages via Hugging Face. Please find the list of currently supported languages under `DEFAULT_ALIGN_MODELS_HF` on [alignment.py](https://github.com/m-bain/whisperX/blob/main/whisperx/alignment.py). If the detected language is not in this list, you need to find a phoneme-based ASR model from [huggingface model hub](https://huggingface.co/models) and test it on your data. - #### E.g. German + whisperx --model large-v2 --language de path/to/audio.wav https://user-images.githubusercontent.com/36994049/208298811-e36002ba-3698-4731-97d4-0aebd07e0eb3.mov - See more examples in other languages [here](EXAMPLES.md). -## Python usage 🐍 +## Python usage 🐍 ```python import whisperx -import gc +import gc -device = "cuda" +device = "cuda" audio_file = "audio.mp3" batch_size = 16 # reduce if low on GPU mem compute_type = "float16" # change to "int8" if low on GPU mem (may reduce accuracy) @@ -192,7 +182,7 @@ print(result["segments"]) # after alignment # import gc; gc.collect(); torch.cuda.empty_cache(); del model_a # 3. Assign speaker labels -diarize_model = whisperx.DiarizationPipeline(use_auth_token=YOUR_HF_TOKEN, device=device) +diarize_model = whisperx.diarize.DiarizationPipeline(use_auth_token=YOUR_HF_TOKEN, device=device) # add min/max number of speakers if known diarize_segments = diarize_model(audio) @@ -205,25 +195,27 @@ print(result["segments"]) # segments are now assigned speaker IDs ## Demos 🚀 -[![Replicate (large-v3](https://img.shields.io/static/v1?label=Replicate+WhisperX+large-v3&message=Demo+%26+Cloud+API&color=blue)](https://replicate.com/victor-upmeet/whisperx) -[![Replicate (large-v2](https://img.shields.io/static/v1?label=Replicate+WhisperX+large-v2&message=Demo+%26+Cloud+API&color=blue)](https://replicate.com/daanelson/whisperx) -[![Replicate (medium)](https://img.shields.io/static/v1?label=Replicate+WhisperX+medium&message=Demo+%26+Cloud+API&color=blue)](https://replicate.com/carnifexer/whisperx) +[![Replicate (large-v3](https://img.shields.io/static/v1?label=Replicate+WhisperX+large-v3&message=Demo+%26+Cloud+API&color=blue)](https://replicate.com/victor-upmeet/whisperx) +[![Replicate (large-v2](https://img.shields.io/static/v1?label=Replicate+WhisperX+large-v2&message=Demo+%26+Cloud+API&color=blue)](https://replicate.com/daanelson/whisperx) +[![Replicate (medium)](https://img.shields.io/static/v1?label=Replicate+WhisperX+medium&message=Demo+%26+Cloud+API&color=blue)](https://replicate.com/carnifexer/whisperx) -If you don't have access to your own GPUs, use the links above to try out WhisperX. +If you don't have access to your own GPUs, use the links above to try out WhisperX.

Technical Details 👷‍♂️

For specific details on the batching and alignment, the effect of VAD, as well as the chosen alignment model, see the preprint [paper](https://www.robots.ox.ac.uk/~vgg/publications/2023/Bain23/bain23.pdf). To reduce GPU memory requirements, try any of the following (2. & 3. can affect quality): + 1. reduce batch size, e.g. `--batch_size 4` -2. use a smaller ASR model `--model base` -3. Use lighter compute type `--compute_type int8` +2. use a smaller ASR model `--model base` +3. Use lighter compute type `--compute_type int8` Transcription differences from openai's whisper: + 1. Transcription without timestamps. To enable single pass batching, whisper inference is performed `--without_timestamps True`, this ensures 1 forward pass per sample in the batch. However, this can cause discrepancies the default whisper output. 2. VAD-based segment transcription, unlike the buffered transcription of openai's. In the WhisperX paper we show this reduces WER, and enables accurate batched inference -3. `--condition_on_prev_text` is set to `False` by default (reduces hallucination) +3. `--condition_on_prev_text` is set to `False` by default (reduces hallucination)

Limitations ⚠️

@@ -232,7 +224,6 @@ Transcription differences from openai's whisper: - Diarization is far from perfect - Language specific wav2vec2 model is needed -

Contribute 🧑‍🏫

If you are multilingual, a major way you can contribute to this project is to find phoneme models on huggingface (or train your own) and test them on speech for the target language. If the results look good send a pull request and some examples showing its success. @@ -241,43 +232,40 @@ Bug finding and pull requests are also highly appreciated to keep this project g

TODO 🗓

-* [x] Multilingual init +- [x] Multilingual init -* [x] Automatic align model selection based on language detection +- [x] Automatic align model selection based on language detection -* [x] Python usage +- [x] Python usage -* [x] Incorporating speaker diarization +- [x] Incorporating speaker diarization -* [x] Model flush, for low gpu mem resources +- [x] Model flush, for low gpu mem resources -* [x] Faster-whisper backend +- [x] Faster-whisper backend -* [x] Add max-line etc. see (openai's whisper utils.py) +- [x] Add max-line etc. see (openai's whisper utils.py) -* [x] Sentence-level segments (nltk toolbox) +- [x] Sentence-level segments (nltk toolbox) -* [x] Improve alignment logic +- [x] Improve alignment logic -* [ ] update examples with diarization and word highlighting +- [ ] update examples with diarization and word highlighting -* [ ] Subtitle .ass output <- bring this back (removed in v3) +- [ ] Subtitle .ass output <- bring this back (removed in v3) -* [ ] Add benchmarking code (TEDLIUM for spd/WER & word segmentation) +- [ ] Add benchmarking code (TEDLIUM for spd/WER & word segmentation) -* [x] Allow silero-vad as alternative VAD option - -* [ ] Improve diarization (word level). *Harder than first thought...* +- [x] Allow silero-vad as alternative VAD option +- [ ] Improve diarization (word level). _Harder than first thought..._

Contact/Support 📇

- Contact maxhbain@gmail.com for queries. Buy Me A Coffee -

Acknowledgements 🙏

This work, and my PhD, is supported by the [VGG (Visual Geometry Group)](https://www.robots.ox.ac.uk/~vgg/) and the University of Oxford. @@ -286,8 +274,8 @@ Of course, this is builds on [openAI's whisper](https://github.com/openai/whispe Borrows important alignment code from [PyTorch tutorial on forced alignment](https://pytorch.org/tutorials/intermediate/forced_alignment_with_torchaudio_tutorial.html) And uses the wonderful pyannote VAD / Diarization https://github.com/pyannote/pyannote-audio - Valuable VAD & Diarization Models from: + - [pyannote audio][https://github.com/pyannote/pyannote-audio] - [silero vad][https://github.com/snakers4/silero-vad] diff --git a/whisperx/__init__.py b/whisperx/__init__.py index 6356fdf7b..ace17eb7a 100644 --- a/whisperx/__init__.py +++ b/whisperx/__init__.py @@ -29,12 +29,3 @@ def load_audio(*args, **kwargs): def assign_word_speakers(*args, **kwargs): diarize = _lazy_import("diarize") return diarize.assign_word_speakers(*args, **kwargs) - - -class DiarizationPipeline: - def __init__(self, *args, **kwargs): - diarize = _lazy_import("diarize") - self._pipeline = diarize.DiarizationPipeline(*args, **kwargs) - - def __getattr__(self, name): - return getattr(self._pipeline, name) From b2d50a027b7488d0516c793020d46ae9fdf8dc2e Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Sat, 3 May 2025 11:38:54 +0200 Subject: [PATCH 035/118] chore: bump version --- pyproject.toml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 2b0bb7359..14c397692 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.3.3" +version = "3.3.4" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.13" @@ -33,4 +33,4 @@ include-package-data = true [tool.setuptools.packages.find] where = ["."] -include = ["whisperx*"] \ No newline at end of file +include = ["whisperx*"] From 108bd0c4000e8c44854ca9644e0fb71335d1efc6 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Sat, 3 May 2025 16:19:32 +0200 Subject: [PATCH 036/118] chore: add lockfile check step to CI workflows --- .github/workflows/build-and-release.yml | 3 +++ .github/workflows/python-compatibility.yml | 3 +++ 2 files changed, 6 insertions(+) diff --git a/.github/workflows/build-and-release.yml b/.github/workflows/build-and-release.yml index 6fd84f3b4..c6dc04131 100644 --- a/.github/workflows/build-and-release.yml +++ b/.github/workflows/build-and-release.yml @@ -17,6 +17,9 @@ jobs: version: "0.5.14" python-version: "3.9" + - name: Check if lockfile is up to date + run: uv lock --check + - name: Build package run: uv build diff --git a/.github/workflows/python-compatibility.yml b/.github/workflows/python-compatibility.yml index 1c2fa7826..374fa8626 100644 --- a/.github/workflows/python-compatibility.yml +++ b/.github/workflows/python-compatibility.yml @@ -23,6 +23,9 @@ jobs: version: "0.5.14" python-version: ${{ matrix.python-version }} + - name: Check if lockfile is up to date + run: uv lock --check + - name: Install the project run: uv sync --all-extras From 5012650d0f3d8966f3ea517762f952a624996d32 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Sat, 3 May 2025 16:19:45 +0200 Subject: [PATCH 037/118] chore: update lockfile --- uv.lock | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/uv.lock b/uv.lock index 2be00836e..01d50fd0f 100644 --- a/uv.lock +++ b/uv.lock @@ -2787,7 +2787,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.3.3" +version = "3.3.4" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, From 6fe0a8784a22301e92624691193c26aab96e0c5e Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Sat, 31 May 2025 11:19:36 +0000 Subject: [PATCH 038/118] docs: add troubleshooting section for libcudnn dependencies in README --- README.md | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/README.md b/README.md index 97f827bed..b453b4bd4 100644 --- a/README.md +++ b/README.md @@ -97,6 +97,25 @@ uv sync --all-extras --dev You may also need to install ffmpeg, rust etc. Follow openAI instructions here https://github.com/openai/whisper#setup. +### Common Issues & Troubleshooting 🔧 + +#### libcudnn Dependencies (GPU Users) + +If you're using WhisperX with GPU support and encounter errors like: + +- `Could not load library libcudnn_ops_infer.so.8` +- `Unable to load any of {libcudnn_cnn.so.9.1.0, libcudnn_cnn.so.9.1, libcudnn_cnn.so.9, libcudnn_cnn.so}` +- `libcudnn_ops_infer.so.8: cannot open shared object file: No such file or directory` + +This means your system is missing the CUDA Deep Neural Network library (cuDNN). This library is needed for GPU acceleration but isn't always installed by default. + +**Install cuDNN (example for apt based systems):** + +```bash +sudo apt update +sudo apt install libcudnn8 libcudnn8-dev -y +``` + ### Speaker Diarization To **enable Speaker Diarization**, include your Hugging Face access token (read) that you can generate from [Here](https://huggingface.co/settings/tokens) after the `--hf_token` argument and accept the user agreement for the following models: [Segmentation](https://huggingface.co/pyannote/segmentation-3.0) and [Speaker-Diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) (if you choose to use Speaker-Diarization 2.x, follow requirements [here](https://huggingface.co/pyannote/speaker-diarization) instead.) From b3432412530ecb0cc5ac923f161da281e41d23d2 Mon Sep 17 00:00:00 2001 From: bog Date: Sat, 31 May 2025 13:32:31 +0200 Subject: [PATCH 039/118] feat: add diarize_model arg to CLI (#1101) --- whisperx/__main__.py | 1 + whisperx/diarize.py | 5 +++-- whisperx/transcribe.py | 4 +++- 3 files changed, 7 insertions(+), 3 deletions(-) diff --git a/whisperx/__main__.py b/whisperx/__main__.py index 6da7b8740..e7f80be44 100644 --- a/whisperx/__main__.py +++ b/whisperx/__main__.py @@ -43,6 +43,7 @@ def cli(): parser.add_argument("--diarize", action="store_true", help="Apply diarization to assign speaker labels to each segment/word") parser.add_argument("--min_speakers", default=None, type=int, help="Minimum number of speakers to in audio file") parser.add_argument("--max_speakers", default=None, type=int, help="Maximum number of speakers to in audio file") + parser.add_argument("--diarize_model", default="pyannote/speaker-diarization-3.1", type=str, help="Name of the speaker diarization model to use") parser.add_argument("--temperature", type=float, default=0, help="temperature to use for sampling") parser.add_argument("--best_of", type=optional_int, default=5, help="number of candidates when sampling with non-zero temperature") diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 97a7813cb..26f33e48a 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -11,13 +11,14 @@ class DiarizationPipeline: def __init__( self, - model_name="pyannote/speaker-diarization-3.1", + model_name=None, use_auth_token=None, device: Optional[Union[str, torch.device]] = "cpu", ): if isinstance(device, str): device = torch.device(device) - self.model = Pipeline.from_pretrained(model_name, use_auth_token=use_auth_token).to(device) + model_config = model_name or "pyannote/speaker-diarization-3.1" + self.model = Pipeline.from_pretrained(model_config, use_auth_token=use_auth_token).to(device) def __call__( self, diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index f56782477..867b37855 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -57,6 +57,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): diarize: bool = args.pop("diarize") min_speakers: int = args.pop("min_speakers") max_speakers: int = args.pop("max_speakers") + diarize_model_name: str = args.pop("diarize_model") print_progress: bool = args.pop("print_progress") if args["language"] is not None: @@ -204,8 +205,9 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): ) tmp_results = results print(">>Performing diarization...") + print(">>Using model:", diarize_model_name) results = [] - diarize_model = DiarizationPipeline(use_auth_token=hf_token, device=device) + diarize_model = DiarizationPipeline(model_name=diarize_model_name, use_auth_token=hf_token, device=device) for result, input_audio_path in tmp_results: diarize_segments = diarize_model( input_audio_path, min_speakers=min_speakers, max_speakers=max_speakers From d700b56c9c402058265ecce1d2dd4563e6dcdca6 Mon Sep 17 00:00:00 2001 From: Kirill Date: Sat, 7 Jun 2025 23:36:49 +0200 Subject: [PATCH 040/118] docs: add missing torch import to Python usage example in README --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b453b4bd4..2b1addae2 100644 --- a/README.md +++ b/README.md @@ -189,7 +189,7 @@ result = model.transcribe(audio, batch_size=batch_size) print(result["segments"]) # before alignment # delete model if low on GPU resources -# import gc; gc.collect(); torch.cuda.empty_cache(); del model +# import gc; import torch; gc.collect(); torch.cuda.empty_cache(); del model # 2. Align whisper output model_a, metadata = whisperx.load_align_model(language_code=result["language"], device=device) @@ -198,7 +198,7 @@ result = whisperx.align(result["segments"], model_a, metadata, audio, device, re print(result["segments"]) # after alignment # delete model if low on GPU resources -# import gc; gc.collect(); torch.cuda.empty_cache(); del model_a +# import gc; import torch; gc.collect(); torch.cuda.empty_cache(); del model_a # 3. Assign speaker labels diarize_model = whisperx.diarize.DiarizationPipeline(use_auth_token=YOUR_HF_TOKEN, device=device) From 1631c3040f9e0d71d6e633ca1905b67f0f7d75f8 Mon Sep 17 00:00:00 2001 From: Radu-Sebastian Amarie Date: Fri, 21 Mar 2025 13:57:47 +0000 Subject: [PATCH 041/118] feat: enhance diarization with optional output of speaker embeddings - Updated DiarizationPipeline to include a return_embeddings parameter for optional speaker embeddings. - Modified assign_word_speakers to accept and process speaker embeddings. - Updated CLI to support --speaker_embeddings flag for JSON output. - Ensured backward compatibility for existing functionality. --- whisperx/__main__.py | 1 + whisperx/diarize.py | 76 +++++++++++++++++++++++++++++++++++++----- whisperx/transcribe.py | 13 ++++++-- 3 files changed, 79 insertions(+), 11 deletions(-) diff --git a/whisperx/__main__.py b/whisperx/__main__.py index e7f80be44..d1fd16de0 100644 --- a/whisperx/__main__.py +++ b/whisperx/__main__.py @@ -44,6 +44,7 @@ def cli(): parser.add_argument("--min_speakers", default=None, type=int, help="Minimum number of speakers to in audio file") parser.add_argument("--max_speakers", default=None, type=int, help="Maximum number of speakers to in audio file") parser.add_argument("--diarize_model", default="pyannote/speaker-diarization-3.1", type=str, help="Name of the speaker diarization model to use") + parser.add_argument("--speaker_embeddings", action="store_true", help="Include speaker embeddings in JSON output (only works with --diarize)") parser.add_argument("--temperature", type=float, default=0, help="temperature to use for sampling") parser.add_argument("--best_of", type=optional_int, default=5, help="number of candidates when sampling with non-zero temperature") diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 26f33e48a..12bb6bae9 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -1,7 +1,7 @@ import numpy as np import pandas as pd from pyannote.audio import Pipeline -from typing import Optional, Union +from typing import Optional, Union, Tuple, Dict, List, Any import torch from whisperx.audio import load_audio, SAMPLE_RATE @@ -26,25 +26,81 @@ def __call__( num_speakers: Optional[int] = None, min_speakers: Optional[int] = None, max_speakers: Optional[int] = None, - ): + return_embeddings: bool = False, + ) -> Union[Tuple[pd.DataFrame, Optional[Dict[str, List[float]]]], pd.DataFrame]: + """ + Perform speaker diarization on audio. + + Args: + audio: Path to audio file or audio array + num_speakers: Exact number of speakers (if known) + min_speakers: Minimum number of speakers to detect + max_speakers: Maximum number of speakers to detect + return_embeddings: Whether to return speaker embeddings + + Returns: + If return_embeddings is True: + Tuple of (diarization dataframe, speaker embeddings dictionary) + Otherwise: + Just the diarization dataframe + """ if isinstance(audio, str): audio = load_audio(audio) audio_data = { 'waveform': torch.from_numpy(audio[None, :]), 'sample_rate': SAMPLE_RATE } - segments = self.model(audio_data, num_speakers = num_speakers, min_speakers=min_speakers, max_speakers=max_speakers) - diarize_df = pd.DataFrame(segments.itertracks(yield_label=True), columns=['segment', 'label', 'speaker']) + + if return_embeddings: + diarization, embeddings = self.model( + audio_data, + num_speakers=num_speakers, + min_speakers=min_speakers, + max_speakers=max_speakers, + return_embeddings=True + ) + else: + diarization = self.model( + audio_data, + num_speakers=num_speakers, + min_speakers=min_speakers, + max_speakers=max_speakers + ) + embeddings = None + + diarize_df = pd.DataFrame(diarization.itertracks(yield_label=True), columns=['segment', 'label', 'speaker']) diarize_df['start'] = diarize_df['segment'].apply(lambda x: x.start) diarize_df['end'] = diarize_df['segment'].apply(lambda x: x.end) - return diarize_df + + if return_embeddings and embeddings is not None: + speaker_embeddings = {speaker: embeddings[s].tolist() for s, speaker in enumerate(diarization.labels())} + return diarize_df, speaker_embeddings + + # For backwards compatibility + if return_embeddings: + return diarize_df, None + else: + return diarize_df def assign_word_speakers( diarize_df: pd.DataFrame, transcript_result: Union[AlignedTranscriptionResult, TranscriptionResult], - fill_nearest=False, -) -> dict: + speaker_embeddings: Optional[Dict[str, List[float]]] = None, + fill_nearest: bool = False, +) -> Union[AlignedTranscriptionResult, TranscriptionResult]: + """ + Assign speakers to words and segments in the transcript. + + Args: + diarize_df: Diarization dataframe from DiarizationPipeline + transcript_result: Transcription result to augment with speaker labels + speaker_embeddings: Optional dictionary mapping speaker IDs to embedding vectors + fill_nearest: If True, assign speakers even when there's no direct time overlap + + Returns: + Updated transcript_result with speaker assignments and optionally embeddings + """ transcript_segments = transcript_result["segments"] for seg in transcript_segments: # assign speaker to segment (if any) @@ -75,7 +131,11 @@ def assign_word_speakers( # sum over speakers speaker = dia_tmp.groupby("speaker")["intersection"].sum().sort_values(ascending=False).index[0] word["speaker"] = speaker - + + # Add speaker embeddings to the result if provided + if speaker_embeddings is not None: + transcript_result["speaker_embeddings"] = speaker_embeddings + return transcript_result diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 867b37855..c1b599a48 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -59,6 +59,10 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): max_speakers: int = args.pop("max_speakers") diarize_model_name: str = args.pop("diarize_model") print_progress: bool = args.pop("print_progress") + return_speaker_embeddings: bool = args.pop("speaker_embeddings") + + if return_speaker_embeddings and not diarize: + warnings.warn("--speaker_embeddings has no effect without --diarize") if args["language"] is not None: args["language"] = args["language"].lower() @@ -209,10 +213,13 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): results = [] diarize_model = DiarizationPipeline(model_name=diarize_model_name, use_auth_token=hf_token, device=device) for result, input_audio_path in tmp_results: - diarize_segments = diarize_model( - input_audio_path, min_speakers=min_speakers, max_speakers=max_speakers + diarize_segments, speaker_embeddings = diarize_model( + input_audio_path, + min_speakers=min_speakers, + max_speakers=max_speakers, + return_embeddings=return_speaker_embeddings ) - result = assign_word_speakers(diarize_segments, result) + result = assign_word_speakers(diarize_segments, result, speaker_embeddings) results.append((result, input_audio_path)) # >> Write for result, audio_path in results: From 220fec9aeaa6716cfd05ce0056a16bd997993bf2 Mon Sep 17 00:00:00 2001 From: Radu-Sebastian Amarie Date: Thu, 3 Apr 2025 13:52:55 +0000 Subject: [PATCH 042/118] refactor: update type hints in diarization module (PEP 585) --- whisperx/diarize.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 12bb6bae9..8b10530c1 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -1,7 +1,7 @@ import numpy as np import pandas as pd from pyannote.audio import Pipeline -from typing import Optional, Union, Tuple, Dict, List, Any +from typing import Optional, Union import torch from whisperx.audio import load_audio, SAMPLE_RATE @@ -27,7 +27,7 @@ def __call__( min_speakers: Optional[int] = None, max_speakers: Optional[int] = None, return_embeddings: bool = False, - ) -> Union[Tuple[pd.DataFrame, Optional[Dict[str, List[float]]]], pd.DataFrame]: + ) -> Union[tuple[pd.DataFrame, Optional[dict[str, list[float]]]], pd.DataFrame]: """ Perform speaker diarization on audio. @@ -86,7 +86,7 @@ def __call__( def assign_word_speakers( diarize_df: pd.DataFrame, transcript_result: Union[AlignedTranscriptionResult, TranscriptionResult], - speaker_embeddings: Optional[Dict[str, List[float]]] = None, + speaker_embeddings: Optional[dict[str, list[float]]] = None, fill_nearest: bool = False, ) -> Union[AlignedTranscriptionResult, TranscriptionResult]: """ From 844736e4e4f42cbc796a97555c76f9e8cf4f602b Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Tue, 24 Jun 2025 12:58:40 +0000 Subject: [PATCH 043/118] style: minor code formatting --- whisperx/diarize.py | 30 +++++++++++++++--------------- 1 file changed, 15 insertions(+), 15 deletions(-) diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 8b10530c1..3632cd8c1 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -30,16 +30,16 @@ def __call__( ) -> Union[tuple[pd.DataFrame, Optional[dict[str, list[float]]]], pd.DataFrame]: """ Perform speaker diarization on audio. - + Args: audio: Path to audio file or audio array num_speakers: Exact number of speakers (if known) min_speakers: Minimum number of speakers to detect max_speakers: Maximum number of speakers to detect return_embeddings: Whether to return speaker embeddings - + Returns: - If return_embeddings is True: + If return_embeddings is True: Tuple of (diarization dataframe, speaker embeddings dictionary) Otherwise: Just the diarization dataframe @@ -53,18 +53,18 @@ def __call__( if return_embeddings: diarization, embeddings = self.model( - audio_data, + audio_data, num_speakers=num_speakers, - min_speakers=min_speakers, - max_speakers=max_speakers, - return_embeddings=True + min_speakers=min_speakers, + max_speakers=max_speakers, + return_embeddings=True, ) else: diarization = self.model( - audio_data, + audio_data, num_speakers=num_speakers, - min_speakers=min_speakers, - max_speakers=max_speakers + min_speakers=min_speakers, + max_speakers=max_speakers, ) embeddings = None @@ -91,13 +91,13 @@ def assign_word_speakers( ) -> Union[AlignedTranscriptionResult, TranscriptionResult]: """ Assign speakers to words and segments in the transcript. - + Args: diarize_df: Diarization dataframe from DiarizationPipeline transcript_result: Transcription result to augment with speaker labels speaker_embeddings: Optional dictionary mapping speaker IDs to embedding vectors fill_nearest: If True, assign speakers even when there's no direct time overlap - + Returns: Updated transcript_result with speaker assignments and optionally embeddings """ @@ -131,12 +131,12 @@ def assign_word_speakers( # sum over speakers speaker = dia_tmp.groupby("speaker")["intersection"].sum().sort_values(ascending=False).index[0] word["speaker"] = speaker - + # Add speaker embeddings to the result if provided if speaker_embeddings is not None: transcript_result["speaker_embeddings"] = speaker_embeddings - - return transcript_result + + return transcript_result class Segment: From b93e9b6f575f41017c01c51d932f756fedadcde4 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Tue, 24 Jun 2025 14:18:02 +0000 Subject: [PATCH 044/118] chore: bump version to 3.4.0 --- pyproject.toml | 2 +- uv.lock | 3153 ++++++++++++++++++++++++------------------------ 2 files changed, 1578 insertions(+), 1577 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 14c397692..7ad075c4a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.3.4" +version = "3.4.0" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.13" diff --git a/uv.lock b/uv.lock index 01d50fd0f..b7ce4d8ba 100644 --- a/uv.lock +++ b/uv.lock @@ -1,4 +1,5 @@ version = 1 +revision = 2 requires-python = ">=3.9, <3.13" resolution-markers = [ "python_full_version >= '3.12'", @@ -10,9 +11,9 @@ resolution-markers = 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a/pyproject.toml b/pyproject.toml index 7ad075c4a..bd22bfdad 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.4.0" +version = "3.4.1" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.13" diff --git a/uv.lock b/uv.lock index b7ce4d8ba..e24a7a4e8 100644 --- a/uv.lock +++ b/uv.lock @@ -2788,7 +2788,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.4.0" +version = "3.4.1" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index c1b599a48..46a774688 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -213,12 +213,19 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): results = [] diarize_model = DiarizationPipeline(model_name=diarize_model_name, use_auth_token=hf_token, device=device) for result, input_audio_path in tmp_results: - diarize_segments, speaker_embeddings = diarize_model( + diarize_result = diarize_model( input_audio_path, min_speakers=min_speakers, max_speakers=max_speakers, return_embeddings=return_speaker_embeddings ) + + if return_speaker_embeddings: + diarize_segments, speaker_embeddings = diarize_result + else: + diarize_segments = diarize_result + speaker_embeddings = None + result = assign_word_speakers(diarize_segments, result, speaker_embeddings) results.append((result, input_audio_path)) # >> Write From e0833da5dc7132006310761f7e166e120f516da3 Mon Sep 17 00:00:00 2001 From: Howard Date: Thu, 15 May 2025 14:30:55 +0800 Subject: [PATCH 046/118] Fix: Ensure integer tensor indexing in get_wildcard_emission() --- whisperx/alignment.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index b77a7f1bf..34fbbbba3 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -424,7 +424,7 @@ def get_wildcard_emission(frame_emission, tokens, blank_id): wildcard_mask = (tokens == -1) # Get scores for non-wildcard positions - regular_scores = frame_emission[tokens.clamp(min=0)] # clamp to avoid -1 index + regular_scores = frame_emission[tokens.clamp(min=0).long()] # clamp to avoid -1 index # Create a mask and compute the maximum value without modifying frame_emission max_valid_score = frame_emission.clone() # Create a copy From 429658d4ccefa55244bcdccd5d179795436093e4 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 27 Jun 2025 07:18:39 +0000 Subject: [PATCH 047/118] chore: bump version to 3.4.2 --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index bd22bfdad..9b849abae 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.4.1" +version = "3.4.2" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.13" diff --git a/uv.lock b/uv.lock index e24a7a4e8..7ed518b2c 100644 --- a/uv.lock +++ b/uv.lock @@ -2788,7 +2788,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.4.1" +version = "3.4.2" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, From f4261f34e9bff8f5ae8115f4cab3b247a8a8b710 Mon Sep 17 00:00:00 2001 From: 3manifold <22544721+3manifold@users.noreply.github.com> Date: Fri, 7 Mar 2025 09:19:32 +0100 Subject: [PATCH 048/118] Remove unused code in Vad class --- whisperx/vads/vad.py | 20 -------------------- 1 file changed, 20 deletions(-) diff --git a/whisperx/vads/vad.py b/whisperx/vads/vad.py index d3ffbb155..32521328e 100644 --- a/whisperx/vads/vad.py +++ b/whisperx/vads/vad.py @@ -52,23 +52,3 @@ def merge_chunks(segments, return merged_segments - # Unused function - @staticmethod - def merge_vad(vad_arr, pad_onset=0.0, pad_offset=0.0, min_duration_off=0.0, min_duration_on=0.0): - active = Annotation() - for k, vad_t in enumerate(vad_arr): - region = Segment(vad_t[0] - pad_onset, vad_t[1] + pad_offset) - active[region, k] = 1 - - if pad_offset > 0.0 or pad_onset > 0.0 or min_duration_off > 0.0: - active = active.support(collar=min_duration_off) - - # remove tracks shorter than min_duration_on - if min_duration_on > 0: - for segment, track in list(active.itertracks()): - if segment.duration < min_duration_on: - del active[segment, track] - - active = active.for_json() - active_segs = pd.DataFrame([x['segment'] for x in active['content']]) - return active_segs From 2d9ce44329ae73af2520196d31cd14b6192ace44 Mon Sep 17 00:00:00 2001 From: Jean Du <37294470+duj12@users.noreply.github.com> Date: Wed, 2 Jul 2025 14:07:59 +0800 Subject: [PATCH 049/118] fix(asr): load VAD model on correct CUDA device (#835) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit fix(asr): load VAD model on correct CUDA device Previously, the VAD sub‐model was always initialized on the default CUDA device (cuda:0), even when a higher device_index was specified. This change sets `device_vad` to `cuda:{device_index}` whenever `device == 'cuda'`, while falling back to the original `device` string for non‐CUDA cases. This ensures the VAD model is loaded on the intended GPU. Co-authored-by: dujing Co-authored-by: Barabazs <31799121+Barabazs@users.noreply.github.com> --- whisperx/asr.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/whisperx/asr.py b/whisperx/asr.py index c47651675..0b47127da 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -401,7 +401,11 @@ def load_model( if vad_method == "silero": vad_model = Silero(**default_vad_options) elif vad_method == "pyannote": - vad_model = Pyannote(torch.device(device), use_auth_token=None, **default_vad_options) + if device == 'cuda': + device_vad = f'cuda:{device_index}' + else: + device_vad = device + vad_model = Pyannote(torch.device(device_vad), use_auth_token=None, **default_vad_options) else: raise ValueError(f"Invalid vad_method: {vad_method}") From 83afb81ac714bd98cb0f0681dbb32cdb01e6b22f Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Wed, 1 Oct 2025 08:37:00 +0200 Subject: [PATCH 050/118] fix: restrict pyannote-audio version to avoid compatibility issues (#1242) * fix: restrict pyannote-audio version to avoid compatibility issues * chore: bump whisperX version to 3.4.3 --- pyproject.toml | 4 ++-- uv.lock | 6 +++--- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 9b849abae..b1663c5a4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.4.2" +version = "3.4.3" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.13" @@ -15,7 +15,7 @@ dependencies = [ "numpy>=2.0.2", "onnxruntime>=1.19", "pandas>=2.2.3", - "pyannote-audio>=3.3.2", + "pyannote-audio>=3.3.2,<4.0.0", "torch>=2.5.1", "torchaudio>=2.5.1", "transformers>=4.48.0", diff --git a/uv.lock b/uv.lock index 7ed518b2c..4c073e56a 100644 --- a/uv.lock +++ b/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 2 +revision = 3 requires-python = ">=3.9, <3.13" resolution-markers = [ "python_full_version >= '3.12'", @@ -2788,7 +2788,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.4.2" +version = "3.4.3" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, @@ -2812,7 +2812,7 @@ requires-dist = [ { name = "numpy", specifier = ">=2.0.2" }, { name = "onnxruntime", specifier = ">=1.19" }, { name = "pandas", specifier = ">=2.2.3" }, - { name = "pyannote-audio", specifier = ">=3.3.2" }, + { name = "pyannote-audio", specifier = ">=3.3.2,<4.0.0" }, { name = "torch", specifier = ">=2.5.1" }, { name = "torchaudio", specifier = ">=2.5.1" }, { name = "transformers", specifier = ">=4.48.0" }, From c7d31883bcce818ed78264a05cdc666ef7d022d2 Mon Sep 17 00:00:00 2001 From: Alex Cannan Date: Tue, 18 Feb 2025 12:25:57 -0500 Subject: [PATCH 051/118] Add jr, sr, and ph.d to punkt abbreviations --- whisperx/alignment.py | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 34fbbbba3..3e19292ab 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -24,7 +24,7 @@ ) from nltk.tokenize.punkt import PunktSentenceTokenizer, PunktParameters -PUNKT_ABBREVIATIONS = ['dr', 'vs', 'mr', 'mrs', 'prof'] +PUNKT_ABBREVIATIONS = ['dr', 'vs', 'mr', 'mrs', 'prof', 'jr', 'sr', 'ph.d'] LANGUAGES_WITHOUT_SPACES = ["ja", "zh"] @@ -124,14 +124,14 @@ def align( """ Align phoneme recognition predictions to known transcription. """ - + if not torch.is_tensor(audio): if isinstance(audio, str): audio = load_audio(audio) audio = torch.from_numpy(audio) if len(audio.shape) == 1: audio = audio.unsqueeze(0) - + MAX_DURATION = audio.shape[1] / SAMPLE_RATE model_dictionary = align_model_metadata["dictionary"] @@ -148,7 +148,7 @@ def align( base_progress = ((sdx + 1) / total_segments) * 100 percent_complete = (50 + base_progress / 2) if combined_progress else base_progress print(f"Progress: {percent_complete:.2f}%...") - + num_leading = len(segment["text"]) - len(segment["text"].lstrip()) num_trailing = len(segment["text"]) - len(segment["text"].rstrip()) text = segment["text"] @@ -165,7 +165,7 @@ def align( # wav2vec2 models use "|" character to represent spaces if model_lang not in LANGUAGES_WITHOUT_SPACES: char_ = char_.replace(" ", "|") - + # ignore whitespace at beginning and end of transcript if cdx < num_leading: pass @@ -187,7 +187,7 @@ def align( # index for placeholder clean_wdx.append(wdx) - + punkt_param = PunktParameters() punkt_param.abbrev_types = set(PUNKT_ABBREVIATIONS) sentence_splitter = PunktSentenceTokenizer(punkt_param) @@ -199,12 +199,12 @@ def align( "clean_wdx": clean_wdx, "sentence_spans": sentence_spans } - + aligned_segments: List[SingleAlignedSegment] = [] - + # 2. Get prediction matrix from alignment model & align for sdx, segment in enumerate(transcript): - + t1 = segment["start"] t2 = segment["end"] text = segment["text"] @@ -247,7 +247,7 @@ def align( ) else: lengths = None - + with torch.inference_mode(): if model_type == "torchaudio": emissions, _ = model(waveform_segment.to(device), lengths=lengths) @@ -304,7 +304,7 @@ def align( word_idx += 1 elif cdx == len(text) - 1 or text[cdx+1] == " ": word_idx += 1 - + char_segments_arr = pd.DataFrame(char_segments_arr) aligned_subsegments = [] @@ -333,7 +333,7 @@ def align( word_end = word_chars["end"].max() word_score = round(word_chars["score"].mean(), 3) - # -1 indicates unalignable + # -1 indicates unalignable word_segment = {"word": word_text} if not np.isnan(word_start): @@ -344,7 +344,7 @@ def align( word_segment["score"] = word_score sentence_words.append(word_segment) - + aligned_subsegments.append({ "text": sentence_text, "start": sentence_start, From ed13dc8c6c69aab52e9e687f7fb857fb3c93d295 Mon Sep 17 00:00:00 2001 From: Max Bain <36994049+m-bain@users.noreply.github.com> Date: Fri, 3 Oct 2025 00:12:53 +0100 Subject: [PATCH 052/118] recall.ai sponsor Added information about Recall.ai's Meeting Transcription API. --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index 2b1addae2..e036120bd 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,10 @@

WhisperX

+## Recall.ai - Meeting Transcription API + +If you’re looking for a transcription API for meetings, consider checking out [Recall.ai's Meeting Transcription API](https://www.recall.ai/product/meeting-transcription-api?utm_source=github&utm_medium=sponsorship&utm_campaign=mbain-whisperx), an API that works with Zoom, Google Meet, Microsoft Teams, and more. Recall.ai diarizes by pulling the speaker data and separate audio streams from the meeting platforms, which means 100% accurate speaker diarization with actual speaker names. + +

Date: Thu, 2 Oct 2025 16:06:38 +0000 Subject: [PATCH 053/118] feat: update Punkt tokenizer to use pre-trained model and handle missing data --- whisperx/alignment.py | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 3e19292ab..ae9f997c5 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -22,9 +22,8 @@ SingleWordSegment, SegmentData, ) -from nltk.tokenize.punkt import PunktSentenceTokenizer, PunktParameters - -PUNKT_ABBREVIATIONS = ['dr', 'vs', 'mr', 'mrs', 'prof', 'jr', 'sr', 'ph.d'] +import nltk +from nltk.data import load as nltk_load LANGUAGES_WITHOUT_SPACES = ["ja", "zh"] @@ -188,9 +187,11 @@ def align( clean_wdx.append(wdx) - punkt_param = PunktParameters() - punkt_param.abbrev_types = set(PUNKT_ABBREVIATIONS) - sentence_splitter = PunktSentenceTokenizer(punkt_param) + try: + sentence_splitter = nltk_load('tokenizers/punkt/english.pickle') + except LookupError: + nltk.download('punkt_tab', quiet=True) + sentence_splitter = nltk_load('tokenizers/punkt/english.pickle') sentence_spans = list(sentence_splitter.span_tokenize(text)) segment_data[sdx] = { From b1c8ac7de62c5969343352f2d10a31ebe5a107fd Mon Sep 17 00:00:00 2001 From: Nguyen Binh Date: Thu, 11 Apr 2024 16:01:20 +0200 Subject: [PATCH 054/118] Change alignment model for Vietnamese language Since the current model is a wav2vec2 pre-trained model for Vietnamese audio, it won't work with alignment tasks. To make it work as expected, I recommend chaining to a fine-tuned ASR version. --- whisperx/alignment.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index ae9f997c5..765cb82ad 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -52,7 +52,7 @@ "tr": "mpoyraz/wav2vec2-xls-r-300m-cv7-turkish", "da": "saattrupdan/wav2vec2-xls-r-300m-ftspeech", "he": "imvladikon/wav2vec2-xls-r-300m-hebrew", - "vi": 'nguyenvulebinh/wav2vec2-base-vi', + "vi": 'nguyenvulebinh/wav2vec2-base-vi-vlsp2020', "ko": "kresnik/wav2vec2-large-xlsr-korean", "ur": "kingabzpro/wav2vec2-large-xls-r-300m-Urdu", "te": "anuragshas/wav2vec2-large-xlsr-53-telugu", From 95fecb91c8739222a77dd3125f47b7dd6bb98017 Mon Sep 17 00:00:00 2001 From: Jim Chen Date: Wed, 8 Oct 2025 17:21:28 +0800 Subject: [PATCH 055/118] build: upgrade PyTorch to 2.7.1 with CUDA 12.8 and multi-platform support - feat: upgrade PyTorch to 2.7.1 and CUDA 12.8 * Update README setup to require CUDA toolkit 12.8 instead of 12.4 (Linux and Windows) * Bump torch dependency from 2.6.0 to 2.7.1 * Switch the PyTorch CUDA wheel index from cu124 to cu128 - Revert "docs: add troubleshooting section for libcudnn dependencies in README" * The issue of relying on two different versions of CUDNN in this project has been resolved. - build(pyproject): relax python version and constrain package deps * Only download torch from PyTorch; obtain all other packages from PyPI. * Restrict numpy, onnxruntime, pandas to be compatible with Python 3.9 - build(pyproject): require triton 3.3.0+ for arm64 support * Add triton version 3.3.0 or newer to the dependencies to support arm64 architecture. - build: skip Triton on Windows since it isn't supported * Add a platform marker to the triton dependency to skip it on Windows, as triton does not support Windows. - build: configure PyTorch sources for cross-platform compatibility * macOS uses CPU-only PyTorch from pytorch-cpu index * Linux and Windows use CUDA 12.8 PyTorch from pytorch index * triton only installs on Linux with CUDA 12.8 support * Update lockfile to support multi-platform builds - fix: restrict av to <16.0.0 for Python 3.9 compatibility * Add av<16.0.0 to dependencies to maintain Python 3.9 support * Update comment to include av in the restriction list * Update uv.lock accordingly PyAV dropped Python 3.9 support in v16.0.0: https://github.com/PyAV-Org/PyAV/commit/106089447cab9dc6d3ca2d1ab7e0aeff76d7a6a4 - fix: resolve PyTorch ARM64 platform compatibility issue * Update uv.lock to properly handle aarch64 platforms for PyTorch dependencies * Add resolution markers for ARM64 Linux systems to use CPU-only PyTorch builds * Ensure CUDA builds are only used on x86_64 platforms where supported Resolves ARM64 Docker build failures by preventing uv from attempting to install CUDA PyTorch on unsupported platforms - chore: change .python-version to 3.10 --- Signed-off-by: CHEN, CHUN Signed-off-by: Jim Chen Co-authored-by: GitHub Copilot --- .python-version | 1 + README.md | 28 +- pyproject.toml | 40 +- uv.lock | 3473 +++++++++++++++++++++++++++-------------------- 4 files changed, 2033 insertions(+), 1509 deletions(-) create mode 100644 .python-version diff --git a/.python-version b/.python-version new file mode 100644 index 000000000..c8cfe3959 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.10 diff --git a/README.md b/README.md index e036120bd..ff9d2aa51 100644 --- a/README.md +++ b/README.md @@ -62,6 +62,15 @@ This repository provides fast automatic speech recognition (70x realtime with la

Setup ⚙️

+### 0. CUDA Installation + +To use WhisperX with GPU acceleration, install the CUDA toolkit 12.8 before WhisperX. Skip this step if using only the CPU. + +- For **Linux** users, install the CUDA toolkit 12.8 following this guide: + [CUDA Installation Guide for Linux](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/). +- For **Windows** users, download and install the CUDA toolkit 12.8: + [CUDA Downloads](https://developer.nvidia.com/cuda-12-8-1-download-archive). + ### 1. Simple Installation (Recommended) The easiest way to install WhisperX is through PyPi: @@ -102,25 +111,6 @@ uv sync --all-extras --dev You may also need to install ffmpeg, rust etc. Follow openAI instructions here https://github.com/openai/whisper#setup. -### Common Issues & Troubleshooting 🔧 - -#### libcudnn Dependencies (GPU Users) - -If you're using WhisperX with GPU support and encounter errors like: - -- `Could not load library libcudnn_ops_infer.so.8` -- `Unable to load any of {libcudnn_cnn.so.9.1.0, libcudnn_cnn.so.9.1, libcudnn_cnn.so.9, libcudnn_cnn.so}` -- `libcudnn_ops_infer.so.8: cannot open shared object file: No such file or directory` - -This means your system is missing the CUDA Deep Neural Network library (cuDNN). This library is needed for GPU acceleration but isn't always installed by default. - -**Install cuDNN (example for apt based systems):** - -```bash -sudo apt update -sudo apt install libcudnn8 libcudnn8-dev -y -``` - ### Speaker Diarization To **enable Speaker Diarization**, include your Hugging Face access token (read) that you can generate from [Here](https://huggingface.co/settings/tokens) after the `--hf_token` argument and accept the user agreement for the following models: [Segmentation](https://huggingface.co/pyannote/segmentation-3.0) and [Speaker-Diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) (if you choose to use Speaker-Diarization 2.x, follow requirements [here](https://huggingface.co/pyannote/speaker-diarization) instead.) diff --git a/pyproject.toml b/pyproject.toml index b1663c5a4..876cf5ed0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -9,16 +9,19 @@ requires-python = ">=3.9, <3.13" license = { text = "BSD-2-Clause" } dependencies = [ - "ctranslate2<4.5.0", + "ctranslate2>=4.5.0", "faster-whisper>=1.1.1", "nltk>=3.9.1", - "numpy>=2.0.2", - "onnxruntime>=1.19", - "pandas>=2.2.3", + # Restrict numpy, onnxruntime, pandas, av to be compatible with Python 3.9 + "numpy>=2.0.2,<2.1.0", + "onnxruntime>=1.19,<1.20.0", + "pandas>=2.2.3,<2.3.0", + "av<16.0.0", "pyannote-audio>=3.3.2,<4.0.0", - "torch>=2.5.1", - "torchaudio>=2.5.1", + "torch>=2.7.1", + "torchaudio", "transformers>=4.48.0", + "triton>=3.3.0; sys_platform == 'linux'" # only install triton on Linux ] @@ -34,3 +37,28 @@ include-package-data = true [tool.setuptools.packages.find] where = ["."] include = ["whisperx*"] + +[tool.uv.sources] +torch = [ + { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" }, + { index = "pytorch-cpu", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { index = "pytorch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, +] +torchaudio = [ + { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" }, + { index = "pytorch-cpu", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { index = "pytorch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, +] +triton = [ + { index = "pytorch", marker = "sys_platform == 'linux'" }, +] + +[[tool.uv.index]] +name = "pytorch" +url = "https://download.pytorch.org/whl/cu128" +explicit = true + +[[tool.uv.index]] +name = "pytorch-cpu" +url = "https://download.pytorch.org/whl/cpu" +explicit = true diff --git a/uv.lock b/uv.lock index 4c073e56a..2690e5766 100644 --- a/uv.lock +++ b/uv.lock @@ -2,23 +2,36 @@ version = 1 revision = 3 requires-python = ">=3.9, <3.13" resolution-markers = [ - "python_full_version >= '3.12'", - "python_full_version == '3.11.*'", - "python_full_version < '3.11'", + "python_full_version >= '3.12' and sys_platform == 'darwin'", + "python_full_version == '3.11.*' and sys_platform == 'darwin'", + "python_full_version == '3.10.*' and sys_platform == 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b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.4.3" +version = "3.5.0" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.13" diff --git a/uv.lock b/uv.lock index 2690e5766..66e85fbb2 100644 --- a/uv.lock +++ b/uv.lock @@ -923,7 +923,7 @@ name = "importlib-metadata" version = "8.7.0" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "zipp", marker = "python_full_version < '3.11' and sys_platform != 'darwin'" }, + { name = "zipp", marker = "python_full_version < '3.10' and sys_platform != 'darwin'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/76/66/650a33bd90f786193e4de4b3ad86ea60b53c89b669a5c7be931fac31cdb0/importlib_metadata-8.7.0.tar.gz", hash = "sha256:d13b81ad223b890aa16c5471f2ac3056cf76c5f10f82d6f9292f0b415f389000", size = 56641, upload-time = "2025-04-27T15:29:01.736Z" } wheels = [ @@ -3278,7 +3278,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.4.3" +version = "3.5.0" source = { editable = "." } dependencies = [ { name = "av" }, From 2663f2edb5b0968f7ccc7e7d0f910bdf805093b9 Mon Sep 17 00:00:00 2001 From: Adrian Wan Date: Thu, 9 Oct 2025 16:27:07 +0900 Subject: [PATCH 057/118] doc: fix diarize import in example script (#1192) --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index ff9d2aa51..e62426bb2 100644 --- a/README.md +++ b/README.md @@ -166,6 +166,7 @@ See more examples in other languages [here](EXAMPLES.md). ```python import whisperx import gc +from whisperx.diarize import DiarizationPipeline device = "cuda" audio_file = "audio.mp3" @@ -196,7 +197,7 @@ print(result["segments"]) # after alignment # import gc; import torch; gc.collect(); torch.cuda.empty_cache(); del model_a # 3. Assign speaker labels -diarize_model = whisperx.diarize.DiarizationPipeline(use_auth_token=YOUR_HF_TOKEN, device=device) +diarize_model = DiarizationPipeline(use_auth_token=YOUR_HF_TOKEN, device=device) # add min/max number of speakers if known diarize_segments = diarize_model(audio) From 64e307cc2975c349ecc5ffa436ff1778ba8279c4 Mon Sep 17 00:00:00 2001 From: 3manifold <22544721+3manifold@users.noreply.github.com> Date: Thu, 9 Oct 2025 09:32:02 +0200 Subject: [PATCH 058/118] chore: remove redundant variable & improve load_model function documentation (#1197) * Remove redundant variable * Improve function documentation --- whisperx/asr.py | 3 ++- whisperx/transcribe.py | 1 - 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/whisperx/asr.py b/whisperx/asr.py index 0b47127da..67d8a8be2 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -319,7 +319,8 @@ def load_model( whisper_arch - The name of the Whisper model to load. device - The device to load the model on. compute_type - The compute type to use for the model. - vad_method - The vad method to use. vad_model has higher priority if is not None. + vad_model - The vad model to manually assign. + vad_method - The vad method to use. vad_model has a higher priority if it is not None. options - A dictionary of options to use for the model. language - The language of the model. (use English for now) model - The WhisperModel instance to use. diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 46a774688..8eca427a1 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -119,7 +119,6 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): # Part 1: VAD & ASR Loop results = [] - tmp_results = [] # model = load_model(model_name, device=device, download_root=model_dir) model = load_model( model_name, From 027ec57aeef86051a5591ac46552111e6d718f31 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Tom=C3=A1=C5=A1=20Hnyk?= Date: Thu, 9 Oct 2025 09:34:54 +0200 Subject: [PATCH 059/118] doc: update cpu only example (#1164) --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e62426bb2..fae1e0753 100644 --- a/README.md +++ b/README.md @@ -144,7 +144,7 @@ To label the transcript with speaker ID's (set number of speakers if known e.g. To run on CPU instead of GPU (and for running on Mac OS X): - whisperx path/to/audio.wav --compute_type int8 + whisperx path/to/audio.wav --compute_type int8 --device cpu ### Other languages From 3b1b9a8c4d2c7874f9733779d0b74a136b0964cd Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 9 Oct 2025 12:22:58 +0000 Subject: [PATCH 060/118] refactor: rename types.py to schema.py to avoid stdlib conflict --- whisperx/alignment.py | 2 +- whisperx/asr.py | 2 +- whisperx/diarize.py | 2 +- whisperx/{types.py => schema.py} | 0 whisperx/transcribe.py | 2 +- 5 files changed, 4 insertions(+), 4 deletions(-) rename whisperx/{types.py => schema.py} (100%) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 765cb82ad..7637683d3 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -15,7 +15,7 @@ from whisperx.audio import SAMPLE_RATE, load_audio from whisperx.utils import interpolate_nans -from whisperx.types import ( +from whisperx.schema import ( AlignedTranscriptionResult, SingleSegment, SingleAlignedSegment, diff --git a/whisperx/asr.py b/whisperx/asr.py index 67d8a8be2..1ad3408fb 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -12,7 +12,7 @@ from transformers.pipelines.pt_utils import PipelineIterator from whisperx.audio import N_SAMPLES, SAMPLE_RATE, load_audio, log_mel_spectrogram -from whisperx.types import SingleSegment, TranscriptionResult +from whisperx.schema import SingleSegment, TranscriptionResult from whisperx.vads import Vad, Silero, Pyannote diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 3632cd8c1..6bab799de 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -5,7 +5,7 @@ import torch from whisperx.audio import load_audio, SAMPLE_RATE -from whisperx.types import TranscriptionResult, AlignedTranscriptionResult +from whisperx.schema import TranscriptionResult, AlignedTranscriptionResult class DiarizationPipeline: diff --git a/whisperx/types.py b/whisperx/schema.py similarity index 100% rename from whisperx/types.py rename to whisperx/schema.py diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 8eca427a1..0b94c134b 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -10,7 +10,7 @@ from whisperx.asr import load_model from whisperx.audio import load_audio from whisperx.diarize import DiarizationPipeline, assign_word_speakers -from whisperx.types import AlignedTranscriptionResult, TranscriptionResult +from whisperx.schema import AlignedTranscriptionResult, TranscriptionResult from whisperx.utils import LANGUAGES, TO_LANGUAGE_CODE, get_writer From a51ae7a81a67a33ad0d7de6e0f5654c92954e5d2 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 10 Oct 2025 08:41:06 +0200 Subject: [PATCH 061/118] feat: add centralized logging to replace ad-hoc print statements (#1254) * feat: add logging utility functions * feat: add logging setup and log level argument to CLI * feat: integrate logging across modules --- whisperx/__init__.py | 26 +++++++++++++++ whisperx/__main__.py | 12 +++++++ whisperx/alignment.py | 14 +++++--- whisperx/asr.py | 11 ++++--- whisperx/diarize.py | 4 +++ whisperx/log_utils.py | 67 +++++++++++++++++++++++++++++++++++++++ whisperx/transcribe.py | 17 ++++++---- whisperx/vads/pyannote.py | 7 ++-- whisperx/vads/silero.py | 7 ++-- 9 files changed, 145 insertions(+), 20 deletions(-) create mode 100644 whisperx/log_utils.py diff --git a/whisperx/__init__.py b/whisperx/__init__.py index ace17eb7a..b8f93fecc 100644 --- a/whisperx/__init__.py +++ b/whisperx/__init__.py @@ -29,3 +29,29 @@ def load_audio(*args, **kwargs): def assign_word_speakers(*args, **kwargs): diarize = _lazy_import("diarize") return diarize.assign_word_speakers(*args, **kwargs) + + +def setup_logging(*args, **kwargs): + """ + Configure logging for WhisperX. + + Args: + level: Logging level (debug, info, warning, error, critical). Default: warning + log_file: Optional path to log file. If None, logs only to console. + """ + logging_module = _lazy_import("log_utils") + return logging_module.setup_logging(*args, **kwargs) + + +def get_logger(*args, **kwargs): + """ + Get a logger instance for the given module. + + Args: + name: Logger name (typically __name__ from calling module) + + Returns: + Logger instance configured with WhisperX settings + """ + logging_module = _lazy_import("log_utils") + return logging_module.get_logger(*args, **kwargs) diff --git a/whisperx/__main__.py b/whisperx/__main__.py index d1fd16de0..5102bc0a5 100644 --- a/whisperx/__main__.py +++ b/whisperx/__main__.py @@ -6,6 +6,7 @@ from whisperx.utils import (LANGUAGES, TO_LANGUAGE_CODE, optional_float, optional_int, str2bool) +from whisperx.log_utils import setup_logging def cli(): @@ -23,6 +24,7 @@ def cli(): parser.add_argument("--output_dir", "-o", type=str, default=".", help="directory to save the outputs") parser.add_argument("--output_format", "-f", type=str, default="all", choices=["all", "srt", "vtt", "txt", "tsv", "json", "aud"], help="format of the output file; if not specified, all available formats will be produced") parser.add_argument("--verbose", type=str2bool, default=True, help="whether to print out the progress and debug messages") + parser.add_argument("--log-level", type=str, default=None, choices=["debug", "info", "warning", "error", "critical"], help="logging level (overrides --verbose if set)") parser.add_argument("--task", type=str, default="transcribe", choices=["transcribe", "translate"], help="whether to perform X->X speech recognition ('transcribe') or X->English translation ('translate')") parser.add_argument("--language", type=str, default=None, choices=sorted(LANGUAGES.keys()) + sorted([k.title() for k in TO_LANGUAGE_CODE.keys()]), help="language spoken in the audio, specify None to perform language detection") @@ -80,6 +82,16 @@ def cli(): args = parser.parse_args().__dict__ + log_level = args.get("log_level") + verbose = args.get("verbose") + + if log_level is not None: + setup_logging(level=log_level) + elif verbose: + setup_logging(level="info") + else: + setup_logging(level="warning") + from whisperx.transcribe import transcribe_task transcribe_task(args, parser) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 7637683d3..903482668 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -24,6 +24,9 @@ ) import nltk from nltk.data import load as nltk_load +from whisperx.log_utils import get_logger + +logger = get_logger(__name__) LANGUAGES_WITHOUT_SPACES = ["ja", "zh"] @@ -81,8 +84,9 @@ def load_align_model(language_code: str, device: str, model_name: Optional[str] elif language_code in DEFAULT_ALIGN_MODELS_HF: model_name = DEFAULT_ALIGN_MODELS_HF[language_code] else: - print(f"There is no default alignment model set for this language ({language_code}).\ - Please find a wav2vec2.0 model finetuned on this language in https://huggingface.co/models, then pass the model name in --align_model [MODEL_NAME]") + logger.error(f"No default alignment model for language: {language_code}. " + f"Please find a wav2vec2.0 model finetuned on this language at https://huggingface.co/models, " + f"then pass the model name via --align_model [MODEL_NAME]") raise ValueError(f"No default align-model for language: {language_code}") if model_name in torchaudio.pipelines.__all__: @@ -223,12 +227,12 @@ def align( # check we can align if len(segment_data[sdx]["clean_char"]) == 0: - print(f'Failed to align segment ("{segment["text"]}"): no characters in this segment found in model dictionary, resorting to original...') + logger.warning(f'Failed to align segment ("{segment["text"]}"): no characters in this segment found in model dictionary, resorting to original') aligned_segments.append(aligned_seg) continue if t1 >= MAX_DURATION: - print(f'Failed to align segment ("{segment["text"]}"): original start time longer than audio duration, skipping...') + logger.warning(f'Failed to align segment ("{segment["text"]}"): original start time longer than audio duration, skipping') aligned_segments.append(aligned_seg) continue @@ -270,7 +274,7 @@ def align( path = backtrack_beam(trellis, emission, tokens, blank_id, beam_width=2) if path is None: - print(f'Failed to align segment ("{segment["text"]}"): backtrack failed, resorting to original...') + logger.warning(f'Failed to align segment ("{segment["text"]}"): backtrack failed, resorting to original') aligned_segments.append(aligned_seg) continue diff --git a/whisperx/asr.py b/whisperx/asr.py index 1ad3408fb..c35900cf9 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -14,6 +14,9 @@ from whisperx.audio import N_SAMPLES, SAMPLE_RATE, load_audio, log_mel_spectrogram from whisperx.schema import SingleSegment, TranscriptionResult from whisperx.vads import Vad, Silero, Pyannote +from whisperx.log_utils import get_logger + +logger = get_logger(__name__) def find_numeral_symbol_tokens(tokenizer): @@ -247,7 +250,7 @@ def data(audio, segments): if self.suppress_numerals: previous_suppress_tokens = self.options.suppress_tokens numeral_symbol_tokens = find_numeral_symbol_tokens(self.tokenizer) - print(f"Suppressing numeral and symbol tokens") + logger.info("Suppressing numeral and symbol tokens") new_suppressed_tokens = numeral_symbol_tokens + self.options.suppress_tokens new_suppressed_tokens = list(set(new_suppressed_tokens)) self.options = replace(self.options, suppress_tokens=new_suppressed_tokens) @@ -285,7 +288,7 @@ def data(audio, segments): def detect_language(self, audio: np.ndarray) -> str: if audio.shape[0] < N_SAMPLES: - print("Warning: audio is shorter than 30s, language detection may be inaccurate.") + logger.warning("Audio is shorter than 30s, language detection may be inaccurate") model_n_mels = self.model.feat_kwargs.get("feature_size") segment = log_mel_spectrogram(audio[: N_SAMPLES], n_mels=model_n_mels if model_n_mels is not None else 80, @@ -294,7 +297,7 @@ def detect_language(self, audio: np.ndarray) -> str: results = self.model.model.detect_language(encoder_output) language_token, language_probability = results[0][0] language = language_token[2:-2] - print(f"Detected language: {language} ({language_probability:.2f}) in first 30s of audio...") + logger.info(f"Detected language: {language} ({language_probability:.2f}) in first 30s of audio") return language @@ -344,7 +347,7 @@ def load_model( if language is not None: tokenizer = Tokenizer(model.hf_tokenizer, model.model.is_multilingual, task=task, language=language) else: - print("No language specified, language will be first be detected for each audio file (increases inference time).") + logger.info("No language specified, language will be detected for each audio file (increases inference time)") tokenizer = None default_asr_options = { diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 6bab799de..9f46b028f 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -6,6 +6,9 @@ from whisperx.audio import load_audio, SAMPLE_RATE from whisperx.schema import TranscriptionResult, AlignedTranscriptionResult +from whisperx.log_utils import get_logger + +logger = get_logger(__name__) class DiarizationPipeline: @@ -18,6 +21,7 @@ def __init__( if isinstance(device, str): device = torch.device(device) model_config = model_name or "pyannote/speaker-diarization-3.1" + logger.info(f"Loading diarization model: {model_config}") self.model = Pipeline.from_pretrained(model_config, use_auth_token=use_auth_token).to(device) def __call__( diff --git a/whisperx/log_utils.py b/whisperx/log_utils.py new file mode 100644 index 000000000..3015f5325 --- /dev/null +++ b/whisperx/log_utils.py @@ -0,0 +1,67 @@ +import logging +import sys +from typing import Optional + +_LOG_FORMAT = "%(asctime)s - %(name)s - %(levelname)s - %(message)s" +_DATE_FORMAT = "%Y-%m-%d %H:%M:%S" + + +def setup_logging( + level: str = "info", + log_file: Optional[str] = None, +) -> None: + """ + Configure logging for WhisperX. + + Args: + level: Logging level (debug, info, warning, error, critical). Default: info + log_file: Optional path to log file. If None, logs only to console. + """ + logger = logging.getLogger("whisperx") + + logger.handlers.clear() + + try: + log_level = getattr(logging, level.upper()) + except AttributeError: + log_level = logging.WARNING + logger.setLevel(log_level) + + formatter = logging.Formatter(_LOG_FORMAT, datefmt=_DATE_FORMAT) + + console_handler = logging.StreamHandler(sys.stdout) + console_handler.setLevel(log_level) + console_handler.setFormatter(formatter) + + logger.addHandler(console_handler) + + if log_file: + try: + file_handler = logging.FileHandler(log_file) + file_handler.setLevel(log_level) + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + except (OSError) as e: + logger.warning(f"Failed to create log file '{log_file}': {e}") + logger.warning("Continuing with console logging only") + + # Don't propagate to root logger to avoid duplicate messages + logger.propagate = False + + +def get_logger(name: str) -> logging.Logger: + """ + Get a logger instance for the given module. + + Args: + name: Logger name (typically __name__ from calling module) + + Returns: + Logger instance configured with WhisperX settings + """ + whisperx_logger = logging.getLogger("whisperx") + if not whisperx_logger.handlers: + setup_logging() + + logger_name = "whisperx" if name == "__main__" else name + return logging.getLogger(logger_name) diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 0b94c134b..11110c64b 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -12,6 +12,9 @@ from whisperx.diarize import DiarizationPipeline, assign_word_speakers from whisperx.schema import AlignedTranscriptionResult, TranscriptionResult from whisperx.utils import LANGUAGES, TO_LANGUAGE_CODE, get_writer +from whisperx.log_utils import get_logger + +logger = get_logger(__name__) def transcribe_task(args: dict, parser: argparse.ArgumentParser): @@ -142,7 +145,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): for audio_path in args.pop("audio"): audio = load_audio(audio_path) # >> VAD & ASR - print(">>Performing transcription...") + logger.info("Performing transcription...") result: TranscriptionResult = model.transcribe( audio, batch_size=batch_size, @@ -175,13 +178,13 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): if align_model is not None and len(result["segments"]) > 0: if result.get("language", "en") != align_metadata["language"]: # load new language - print( + logger.info( f"New language found ({result['language']})! Previous was ({align_metadata['language']}), loading new alignment model for new language..." ) align_model, align_metadata = load_align_model( result["language"], device ) - print(">>Performing alignment...") + logger.info("Performing alignment...") result: AlignedTranscriptionResult = align( result["segments"], align_model, @@ -203,12 +206,12 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): # >> Diarize if diarize: if hf_token is None: - print( - "Warning, no --hf_token used, needs to be saved in environment variable, otherwise will throw error loading diarization model..." + logger.warning( + "No --hf_token provided, needs to be saved in environment variable, otherwise will throw error loading diarization model" ) tmp_results = results - print(">>Performing diarization...") - print(">>Using model:", diarize_model_name) + logger.info("Performing diarization...") + logger.info(f"Using model: {diarize_model_name}") results = [] diarize_model = DiarizationPipeline(model_name=diarize_model_name, use_auth_token=hf_token, device=device) for result, input_audio_path in tmp_results: diff --git a/whisperx/vads/pyannote.py b/whisperx/vads/pyannote.py index 62225f0a9..0e806bb19 100644 --- a/whisperx/vads/pyannote.py +++ b/whisperx/vads/pyannote.py @@ -13,6 +13,9 @@ from whisperx.diarize import Segment as SegmentX from whisperx.vads.vad import Vad +from whisperx.log_utils import get_logger + +logger = get_logger(__name__) def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, use_auth_token=None, model_fp=None): @@ -232,7 +235,7 @@ def apply(self, file: AudioFile, hook: Optional[Callable] = None) -> Annotation: class Pyannote(Vad): def __init__(self, device, use_auth_token=None, model_fp=None, **kwargs): - print(">>Performing voice activity detection using Pyannote...") + logger.info("Performing voice activity detection using Pyannote...") super().__init__(kwargs['vad_onset']) self.vad_pipeline = load_vad_model(device, use_auth_token=use_auth_token, model_fp=model_fp) @@ -257,7 +260,7 @@ def merge_chunks(segments, segments_list.append(SegmentX(speech_turn.start, speech_turn.end, "UNKNOWN")) if len(segments_list) == 0: - print("No active speech found in audio") + logger.warning("No active speech found in audio") return [] assert segments_list, "segments_list is empty." return Vad.merge_chunks(segments_list, chunk_size, onset, offset) diff --git a/whisperx/vads/silero.py b/whisperx/vads/silero.py index 88c54b831..24a64d4f9 100644 --- a/whisperx/vads/silero.py +++ b/whisperx/vads/silero.py @@ -8,6 +8,9 @@ from whisperx.diarize import Segment as SegmentX from whisperx.vads.vad import Vad +from whisperx.log_utils import get_logger + +logger = get_logger(__name__) AudioFile = Union[Text, Path, IOBase, Mapping] @@ -15,7 +18,7 @@ class Silero(Vad): # check again default values def __init__(self, **kwargs): - print(">>Performing voice activity detection using Silero...") + logger.info("Performing voice activity detection using Silero...") super().__init__(kwargs['vad_onset']) self.vad_onset = kwargs['vad_onset'] @@ -60,7 +63,7 @@ def merge_chunks(segments_list, ): assert chunk_size > 0 if len(segments_list) == 0: - print("No active speech found in audio") + logger.warning("No active speech found in audio") return [] assert segments_list, "segments_list is empty." return Vad.merge_chunks(segments_list, chunk_size, onset, offset) From c1c08c472f13c9271d8dfbb2be2e5629a84ca00c Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 10 Oct 2025 06:45:00 +0000 Subject: [PATCH 062/118] bump: update version to 3.6.0 --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 5d8734720..340ae912e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.5.0" +version = "3.6.0" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.13" diff --git a/uv.lock b/uv.lock index 66e85fbb2..dff36e104 100644 --- a/uv.lock +++ b/uv.lock @@ -3278,7 +3278,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.5.0" +version = "3.6.0" source = { editable = "." } dependencies = [ { name = "av" }, From d13171cdde808d254517051a0bf9cd949ca1cbc9 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 10 Oct 2025 09:36:24 +0200 Subject: [PATCH 063/118] feat: add support for python 3.13 (#1256) * feat: update Python version requirement to be compatible with 3.13 * feat: add Python 3.13 to compatibility matrix * feat: update onnxruntime dependency for Python version compatibility * fix: drop onnxruntime restriction for python >= 3.10 --- .github/workflows/python-compatibility.yml | 2 +- pyproject.toml | 4 +- uv.lock | 775 +++++++++++++++++++-- 3 files changed, 723 insertions(+), 58 deletions(-) diff --git a/.github/workflows/python-compatibility.yml b/.github/workflows/python-compatibility.yml index 374fa8626..8de094aad 100644 --- a/.github/workflows/python-compatibility.yml +++ b/.github/workflows/python-compatibility.yml @@ -12,7 +12,7 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - python-version: ["3.9", "3.10", "3.11", "3.12"] + python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"] steps: - uses: actions/checkout@v4 diff --git a/pyproject.toml b/pyproject.toml index 340ae912e..45c2f4570 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,7 +5,7 @@ name = "whisperx" version = "3.6.0" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" -requires-python = ">=3.9, <3.13" +requires-python = ">=3.9, <3.14" license = { text = "BSD-2-Clause" } dependencies = [ @@ -14,7 +14,7 @@ dependencies = [ "nltk>=3.9.1", # Restrict numpy, onnxruntime, pandas, av to 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platform_machine == 'x86_64' and sys_platform != 'darwin'", + "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.10.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version < '3.10' and platform_machine == 'x86_64' and sys_platform != 'darwin'", @@ -3045,6 +3652,10 @@ wheels = [ { url = "https://download.pytorch.org/whl/cu128/torch-2.8.0%2Bcu128-cp311-cp311-win_amd64.whl", hash = "sha256:34c55443aafd31046a7963b63d30bc3b628ee4a704f826796c865fdfd05bb596" }, { url = "https://download.pytorch.org/whl/cu128/torch-2.8.0%2Bcu128-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:4354fc05bb79b208d6995a04ca1ceef6a9547b1c4334435574353d381c55087c" }, { url = "https://download.pytorch.org/whl/cu128/torch-2.8.0%2Bcu128-cp312-cp312-win_amd64.whl", hash = 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and platform_python_implementation == 'CPython' and sys_platform == 'linux'", + "python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version == '3.10.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version < '3.10' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", @@ -3112,6 +3725,10 @@ wheels = [ { url = "https://download.pytorch.org/whl/cpu/torchaudio-2.8.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:4573c6042950c20278e3608a9a38050ba0bc72e0049e1bbfd249caf859a8029b" }, { url = "https://download.pytorch.org/whl/cpu/torchaudio-2.8.0-cp312-cp312-macosx_11_0_arm64.whl", hash = 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"(python_full_version >= '3.13' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.12.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine == 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sys_platform != 'linux')", @@ -3136,6 +3754,10 @@ wheels = [ { url = "https://download.pytorch.org/whl/cpu/torchaudio-2.8.0%2Bcpu-cp311-cp311-win_amd64.whl", hash = "sha256:db37df7eee906f8fe0a639fdc673f3541cb2e173169b16d4133447eb922d1938" }, { url = "https://download.pytorch.org/whl/cpu/torchaudio-2.8.0%2Bcpu-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:9377faee65a290578280ac7f4884c3586253dac2ca28c60f458ff6efe86a6b05" }, { url = "https://download.pytorch.org/whl/cpu/torchaudio-2.8.0%2Bcpu-cp312-cp312-win_amd64.whl", hash = "sha256:9b302192b570657c1cc787a4d487ae4bbb7f2aab1c01b1fcc46757e7f86f391e" }, + { url = "https://download.pytorch.org/whl/cpu/torchaudio-2.8.0%2Bcpu-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:e1b1f530e8b71b1d079e23db45a0e621709061710ef8540aae8280aa039554ee" }, + { url = "https://download.pytorch.org/whl/cpu/torchaudio-2.8.0%2Bcpu-cp313-cp313-win_amd64.whl", hash = "sha256:0c2d081e24204768e636cbf05e1377c8a6964b8ed6fa3aa5092ba9af9bbc19c5" }, + { 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"python_full_version >= '3.13' and platform_machine == 'x86_64' and sys_platform != 'darwin'", + "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.10.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version < '3.10' and platform_machine == 'x86_64' and sys_platform != 'darwin'", @@ -3160,6 +3783,10 @@ wheels = [ { url = "https://download.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp311-cp311-win_amd64.whl", hash = "sha256:7a1eb6154e05b8056b34c7a41495e09d57f79eb0180eb4e7f3bb2a61845ca8ea" }, { url = "https://download.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:145b8a0c21cfcaa1705c67173c5d439087e0e120d5da9bc344746f937901d243" }, { url = "https://download.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp312-cp312-win_amd64.whl", hash = "sha256:cce3a60cd9a97f7360c8f95504ac349311fb7d6b9b826135936764f4de5f782d" }, + { url = "https://download.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:410bb8ea46225efe658e5d27a3802c181a2255913003621a5d25a51aca8018d9" }, + { url = "https://download.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp313-cp313-win_amd64.whl", hash = "sha256:3146bbd48992d215f6bb1aef9626d734c3180b377791ded2a4d4d2c0e63c0cc2" }, + { url = "https://download.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:04b410f93337fc6c16576d0c88e2a31091aef9d1fd212ebb8cd26899dba175e0" }, + { url = "https://download.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp313-cp313t-win_amd64.whl", hash = "sha256:1054e0a7613cac54ed9b3784a5fcbe023748a70004d9cca74c5f9ae00a1fdfd1" }, { url = "https://download.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp39-cp39-manylinux_2_28_x86_64.whl", hash = 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<31799121+Barabazs@users.noreply.github.com> Date: Fri, 10 Oct 2025 07:37:17 +0000 Subject: [PATCH 064/118] bump: update version to 3.7.0 --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 45c2f4570..11949ce45 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.6.0" +version = "3.7.0" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.14" diff --git a/uv.lock b/uv.lock index fb0e63ac1..bca6bde55 100644 --- a/uv.lock +++ b/uv.lock @@ -3909,7 +3909,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.6.0" +version = "3.7.0" source = { editable = "." } dependencies = [ { name = "av" }, From 895e5a84935193be441aac924150c7ed7d4b61e9 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Sun, 12 Oct 2025 02:31:44 -0600 Subject: [PATCH 065/118] chore: update numpy dependency constraints for Python 3.13 compatibility (#1258) * chore: update numpy dependency constraints for Python 3.13 compatibility * bump: update version to 3.7.1 --- pyproject.toml | 5 +- uv.lock | 159 ++++++++++++++++++++++++++++++++++++++++--------- 2 files changed, 135 insertions(+), 29 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 11949ce45..fb78d4be1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.7.0" +version = "3.7.1" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.14" @@ -13,10 +13,11 @@ dependencies = [ "faster-whisper>=1.1.1", "nltk>=3.9.1", # Restrict numpy, onnxruntime, pandas, av to be compatible with 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}, marker = "python_full_version < '3.10'" }, { name = "matplotlib", version = "3.10.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" }, - { name = "numpy" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, { name = "pandas" }, { name = "pyannote-core" }, { name = "pyannote-database" }, @@ -2646,7 +2741,8 @@ name = "pytorch-metric-learning" version = "2.9.0" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "numpy" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, { name = "scikit-learn", version = "1.6.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" }, { name = "scikit-learn", version = "1.7.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, @@ -2950,7 +3046,7 @@ resolution-markers = [ ] dependencies = [ { name = "joblib", marker = "python_full_version < '3.10'" }, - { name = "numpy", marker = "python_full_version < '3.10'" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" }, { name = "scipy", version = "1.13.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" }, { name = "threadpoolctl", marker = "python_full_version < '3.10'" }, ] @@ -3011,7 +3107,8 @@ resolution-markers = [ ] dependencies = [ { name = "joblib", marker = "python_full_version >= '3.10'" }, - { name = "numpy", marker = "python_full_version >= '3.10'" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10' and python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, { name = "scipy", version = "1.15.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.10.*'" }, { name = "scipy", version = "1.16.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" }, { name = "threadpoolctl", marker = "python_full_version >= '3.10'" }, @@ -3056,7 +3153,7 @@ resolution-markers = [ "python_full_version < '3.10' and platform_machine == 'x86_64' and sys_platform != 'darwin'", ] dependencies = [ - { name = "numpy", marker = "python_full_version < '3.10'" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/ae/00/48c2f661e2816ccf2ecd77982f6605b2950afe60f60a52b4cbbc2504aa8f/scipy-1.13.1.tar.gz", hash = "sha256:095a87a0312b08dfd6a6155cbbd310a8c51800fc931b8c0b84003014b874ed3c", size = 57210720, upload-time = "2024-05-23T03:29:26.079Z" } wheels = [ @@ -3097,7 +3194,7 @@ resolution-markers = [ "python_full_version == '3.10.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", ] dependencies = [ - { name = "numpy", marker = "python_full_version == '3.10.*'" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.10.*'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/0f/37/6964b830433e654ec7485e45a00fc9a27cf868d622838f6b6d9c5ec0d532/scipy-1.15.3.tar.gz", hash = "sha256:eae3cf522bc7df64b42cad3925c876e1b0b6c35c1337c93e12c0f366f55b0eaf", size = 59419214, upload-time = "2025-05-08T16:13:05.955Z" } wheels = [ @@ -3167,7 +3264,8 @@ resolution-markers = [ "python_full_version == '3.11.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", ] dependencies = [ - { name = "numpy", marker = "python_full_version >= '3.11'" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11' and python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/4c/3b/546a6f0bfe791bbb7f8d591613454d15097e53f906308ec6f7c1ce588e8e/scipy-1.16.2.tar.gz", hash = "sha256:af029b153d243a80afb6eabe40b0a07f8e35c9adc269c019f364ad747f826a6b", size = 30580599, upload-time = "2025-09-11T17:48:08.271Z" } wheels = [ @@ -3320,7 +3418,8 @@ version = "0.13.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "cffi" }, - { name = "numpy" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/e1/41/9b873a8c055582859b239be17902a85339bec6a30ad162f98c9b0288a2cc/soundfile-0.13.1.tar.gz", hash = "sha256:b2c68dab1e30297317080a5b43df57e302584c49e2942defdde0acccc53f0e5b", size = 46156, upload-time = "2025-01-25T09:17:04.831Z" } wheels = [ @@ -3341,7 +3440,8 @@ dependencies = [ { name = "huggingface-hub" }, { name = "hyperpyyaml" }, { name = "joblib" }, - { name = "numpy" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, { name = "packaging" }, { name = "scipy", version = "1.13.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" }, { name = "scipy", version = "1.15.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.10.*'" }, @@ -3439,7 +3539,8 @@ name = "tensorboardx" version = "2.6.4" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "numpy" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, { name = "packaging" }, { name = "protobuf" }, ] @@ -3797,7 +3898,8 @@ version = "1.8.2" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "lightning-utilities" }, - { name = "numpy" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, { name = "packaging" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, @@ -3827,7 +3929,8 @@ source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "filelock" }, { name = "huggingface-hub" }, - { name = "numpy" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, { name = "packaging" }, { name = "pyyaml" }, { name = "regex" }, @@ -3909,14 +4012,15 @@ wheels = [ [[package]] name = "whisperx" -version = "3.7.0" +version = "3.7.1" source = { editable = "." } dependencies = [ { name = "av" }, { name = "ctranslate2" }, { name = "faster-whisper" }, { name = "nltk" }, - { name = "numpy" }, + { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, + { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, { name = "onnxruntime", version = "1.19.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" }, { name = "pandas" }, { name = "pyannote-audio" }, @@ -3936,7 +4040,8 @@ requires-dist = [ { name = "ctranslate2", specifier = ">=4.5.0" }, { name = "faster-whisper", specifier = ">=1.1.1" }, { name = "nltk", specifier = ">=3.9.1" }, - { name = "numpy", specifier = ">=2.0.2,<2.1.0" }, + { name = "numpy", marker = "python_full_version < '3.13'", specifier = ">=2.0.2,<2.1.0" }, + { name = "numpy", marker = "python_full_version >= '3.13'", specifier = ">=2.1.0,<2.3.0" }, { name = "onnxruntime", marker = "python_full_version < '3.10'", specifier = ">=1.19,<1.20.0" }, { name = "pandas", specifier = ">=2.2.3,<2.3.0" }, { name = "pyannote-audio", specifier = ">=3.3.2,<4.0.0" }, From 505bd9c0b522674e3782f3393644e3f2d7d238ba Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Sun, 12 Oct 2025 02:38:29 -0600 Subject: [PATCH 066/118] chore: refine triton dependency to restrict installation to x86_64 Linux (#1259) * chore: refine triton dependency to restrict installation to x86_64 Linux * bump: update version to 3.7.2 --- pyproject.toml | 4 ++-- uv.lock | 18 ++++++------------ 2 files changed, 8 insertions(+), 14 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index fb78d4be1..bdb3c5450 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.7.1" +version = "3.7.2" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.14" @@ -22,7 +22,7 @@ dependencies = [ "torch>=2.7.1", "torchaudio", "transformers>=4.48.0", - "triton>=3.3.0; sys_platform == 'linux'" # only install triton on Linux + "triton>=3.3.0; sys_platform == 'linux' and platform_machine == 'x86_64'" # only install triton on x86_64 Linux ] diff --git a/uv.lock b/uv.lock index a86b1f9be..07f1daaf0 100644 --- a/uv.lock +++ b/uv.lock @@ -1102,7 +1102,7 @@ name = "importlib-metadata" version = "8.7.0" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "zipp", marker = "python_full_version < '3.10' and sys_platform != 'darwin'" }, + { name = "zipp", marker = "python_full_version < '3.10' and platform_machine == 'x86_64' and sys_platform != 'darwin'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/76/66/650a33bd90f786193e4de4b3ad86ea60b53c89b669a5c7be931fac31cdb0/importlib_metadata-8.7.0.tar.gz", hash = "sha256:d13b81ad223b890aa16c5471f2ac3056cf76c5f10f82d6f9292f0b415f389000", size = 56641, upload-time = "2025-04-27T15:29:01.736Z" } wheels = [ @@ -3949,21 +3949,15 @@ name = "triton" version = "3.4.0" source = { registry = "https://download.pytorch.org/whl/cu128" } dependencies = [ - { name = "importlib-metadata", marker = "python_full_version < '3.10' and sys_platform != 'darwin'" }, - { name = "setuptools", marker = "sys_platform != 'darwin'" }, + { name = "importlib-metadata", marker = "python_full_version < '3.10' and platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "setuptools", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, ] wheels = [ - { url = "https://download.pytorch.org/whl/triton-3.4.0-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl" }, { url = "https://download.pytorch.org/whl/triton-3.4.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl" }, - { url = "https://download.pytorch.org/whl/triton-3.4.0-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl" }, { url = "https://download.pytorch.org/whl/triton-3.4.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl" }, - { url = "https://download.pytorch.org/whl/triton-3.4.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl" }, { url = "https://download.pytorch.org/whl/triton-3.4.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl" }, - { url = "https://download.pytorch.org/whl/triton-3.4.0-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl" }, { url = "https://download.pytorch.org/whl/triton-3.4.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl" }, - { url = "https://download.pytorch.org/whl/triton-3.4.0-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl" }, { url = "https://download.pytorch.org/whl/triton-3.4.0-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl" }, - { url = "https://download.pytorch.org/whl/triton-3.4.0-cp39-cp39-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl" }, { url = "https://download.pytorch.org/whl/triton-3.4.0-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl" }, ] @@ -4012,7 +4006,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.7.1" +version = "3.7.2" source = { editable = "." } dependencies = [ { name = "av" }, @@ -4031,7 +4025,7 @@ dependencies = [ { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')" }, { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, { name = "transformers" }, - { name = "triton", marker = "sys_platform == 'linux'" }, + { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, ] [package.metadata] @@ -4052,7 +4046,7 @@ requires-dist = [ { name = "torchaudio", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", index = "https://download.pytorch.org/whl/cpu" }, { name = "torchaudio", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", index = "https://download.pytorch.org/whl/cu128" }, { name = "transformers", specifier = ">=4.48.0" }, - { name = "triton", marker = "sys_platform == 'linux'", specifier = ">=3.3.0", index = "https://download.pytorch.org/whl/cu128" }, + { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'", specifier = ">=3.3.0", index = "https://download.pytorch.org/whl/cu128" }, ] [[package]] From 0fa81b31f136b3574d6e9b2837de003acc9f9321 Mon Sep 17 00:00:00 2001 From: Paffe Date: Wed, 15 Oct 2025 08:08:18 +0200 Subject: [PATCH 067/118] feat: add Swedish alignment model (#1110) --------- Co-authored-by: Paffe --- whisperx/alignment.py | 1 + 1 file changed, 1 insertion(+) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 903482668..756d0ba70 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -73,6 +73,7 @@ "ka": "xsway/wav2vec2-large-xlsr-georgian", "lv": "jimregan/wav2vec2-large-xlsr-latvian-cv", "tl": "Khalsuu/filipino-wav2vec2-l-xls-r-300m-official", + "sv": "KBLab/wav2vec2-large-voxrex-swedish", } From 92227e74128b09cae2ccbbc81a890f55a8aecf17 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 16 Oct 2025 00:42:10 -0600 Subject: [PATCH 068/118] fix: lock down torch and torchaudio versions (#1265) * fix: update torch and torchaudio dependencies to use compatible version specifiers * chore: update version to 3.7.3 --- pyproject.toml | 6 +- uv.lock | 366 +++++++++++++++++++++++-------------------------- 2 files changed, 176 insertions(+), 196 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index bdb3c5450..954ff3a10 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.7.2" +version = "3.7.3" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.14" @@ -19,8 +19,8 @@ dependencies = [ "av<16.0.0", "numpy>=2.1.0,<2.3.0; python_version >='3.13'", "pyannote-audio>=3.3.2,<4.0.0", - "torch>=2.7.1", - "torchaudio", + "torch~=2.7.1", + "torchaudio~=2.7.1", "transformers>=4.48.0", "triton>=3.3.0; sys_platform == 'linux' and platform_machine == 'x86_64'" # only install triton on x86_64 Linux ] diff --git a/uv.lock b/uv.lock index 07f1daaf0..9476e29fe 100644 --- a/uv.lock +++ b/uv.lock @@ -177,9 +177,9 @@ source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, - { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.7.1", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, + { name = "torch", version = "2.7.1+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.7.1+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, { name = "typing-extensions" }, ] sdist = { url = "https://files.pythonhosted.org/packages/90/fa/5c2be1f96dc179f83cdd3bb267edbd1f47d08f756785c016d5c2163901a7/asteroid-filterbanks-0.4.0.tar.gz", hash = "sha256:415f89d1dcf2b13b35f03f7a9370968ac4e6fa6800633c522dac992b283409b9", size = 24599, upload-time = "2021-04-09T20:03:07.456Z" } @@ -1097,18 +1097,6 @@ wheels = [ { url = 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marker = "(platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')" }, - { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.7.1", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, + { name = "torch", version = "2.7.1+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.7.1+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torchaudio", version = "2.7.1", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux') or sys_platform == 'darwin'" }, + { name = "torchaudio", version = "2.7.1+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')" }, + { name = "torchaudio", version = "2.7.1+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, { name = "transformers" }, { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, ] @@ -4039,12 +4019,12 @@ requires-dist = [ { name = "onnxruntime", marker = "python_full_version < '3.10'", specifier = ">=1.19,<1.20.0" }, { name = "pandas", specifier = ">=2.2.3,<2.3.0" }, { name = "pyannote-audio", specifier = ">=3.3.2,<4.0.0" }, - { name = "torch", marker = "sys_platform == 'darwin'", specifier = ">=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torch", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = ">=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = ">=2.7.1", index = "https://download.pytorch.org/whl/cu128" }, - { name = "torchaudio", marker = "sys_platform == 'darwin'", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torchaudio", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torchaudio", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", index = "https://download.pytorch.org/whl/cu128" }, + { name = "torch", marker = "sys_platform == 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torch", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cu128" }, + { name = "torchaudio", marker = "sys_platform == 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torchaudio", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torchaudio", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cu128" }, { name = "transformers", specifier = ">=4.48.0" }, { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'", specifier = ">=3.3.0", index = "https://download.pytorch.org/whl/cu128" }, ] From 617835dc27ca8d6e92f9536f94a710e9d44f3903 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 16 Oct 2025 07:41:45 +0000 Subject: [PATCH 069/118] chore: upgrade torch and torchaudio dependencies to 2.8.0 --- pyproject.toml | 6 +- uv.lock | 366 ++++++++++++++++++++++++++----------------------- 2 files changed, 196 insertions(+), 176 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 954ff3a10..926d69751 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.7.3" +version = "3.7.4" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.9, <3.14" @@ -19,8 +19,8 @@ dependencies = [ "av<16.0.0", "numpy>=2.1.0,<2.3.0; python_version >='3.13'", "pyannote-audio>=3.3.2,<4.0.0", - "torch~=2.7.1", - "torchaudio~=2.7.1", + "torch~=2.8.0", + "torchaudio~=2.8.0", "transformers>=4.48.0", "triton>=3.3.0; sys_platform == 'linux' and platform_machine == 'x86_64'" # only install triton on x86_64 Linux ] diff --git a/uv.lock b/uv.lock index 9476e29fe..c6b122a92 100644 --- a/uv.lock +++ b/uv.lock @@ -177,9 +177,9 @@ source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" }, { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" }, - { name = "torch", version = "2.7.1", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" 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= "av" }, @@ -3998,12 +4018,12 @@ dependencies = [ { name = "onnxruntime", version = "1.19.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" }, { name = "pandas" }, { name = "pyannote-audio" }, - { name = "torch", version = "2.7.1", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.7.1+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.7.1+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, - { name = "torchaudio", version = "2.7.1", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux') or sys_platform == 'darwin'" }, 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"https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torchaudio", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux') or sys_platform == 'darwin'" }, + { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')" }, + { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, { name = "transformers" }, { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, ] @@ -4019,12 +4039,12 @@ requires-dist = [ { name = "onnxruntime", marker = "python_full_version < '3.10'", specifier = ">=1.19,<1.20.0" }, { name = "pandas", specifier = ">=2.2.3,<2.3.0" }, { name = "pyannote-audio", specifier = ">=3.3.2,<4.0.0" }, - { name = "torch", marker = "sys_platform == 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torch", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cu128" }, - { name = "torchaudio", marker = "sys_platform == 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torchaudio", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torchaudio", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.7.1", index = "https://download.pytorch.org/whl/cu128" }, + { name = "torch", marker = "sys_platform == 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torch", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" }, + { name = "torchaudio", marker = "sys_platform == 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torchaudio", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torchaudio", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" }, { name = "transformers", specifier = ">=4.48.0" }, { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'", specifier = ">=3.3.0", index = "https://download.pytorch.org/whl/cu128" }, ] From 5925e5f8c7d1e627f5183a3eb25bfbad8665a41d Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Thu, 16 Oct 2025 02:56:51 -0600 Subject: [PATCH 070/118] docs: add cuDNN troubleshooting for common issues (#1266) * docs: add troubleshooting guide for cuDNN loading errors * docs: add cuDNN version incompatibility troubleshooting --- CUDNN_TROUBLESHOOTING.md | 76 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 76 insertions(+) create mode 100644 CUDNN_TROUBLESHOOTING.md diff --git a/CUDNN_TROUBLESHOOTING.md b/CUDNN_TROUBLESHOOTING.md new file mode 100644 index 000000000..80b12e565 --- /dev/null +++ b/CUDNN_TROUBLESHOOTING.md @@ -0,0 +1,76 @@ +# Troubleshooting cuDNN Loading Errors + +This guide helps resolve common cuDNN-related errors when running WhisperX on GPU. These issues typically occur when the system can't locate cuDNN libraries or finds conflicting versions. + +## Unable to Load cuDNN Libraries + +If you encounter the following error when running WhisperX: + +`Unable to load any of {libcudnn_cnn.so.9.1.0, libcudnn_cnn.so.9.1, libcudnn_cnn.so.9, libcudnn_cnn.so}` + +This means the cuDNN libraries are installed (via whisperx dependencies) but aren't in a location where the system's dynamic linker can find them. + +### Solution 1: Add to LD_LIBRARY_PATH (Recommended) + +Add this at the start of your Python script or notebook: + +```python +import os + +# Get current LD_LIBRARY_PATH +original = os.environ.get("LD_LIBRARY_PATH", "") + +cudnn_path = "/usr/local/lib/python3.12/dist-packages/nvidia/cudnn/lib/" +os.environ['LD_LIBRARY_PATH'] = original + ":" + cudnn_path +``` + +**Note:** Adjust the Python version (`python3.12`) to match your environment. + +### Solution 2: Symlink to LD_LIBRARY_PATH Directory + +If Solution 1 didn't work and you still get the "unable to load" error, symlink the libraries to a directory that's already in your `LD_LIBRARY_PATH`: + +1. Check what's in your LD_LIBRARY_PATH: `echo "$LD_LIBRARY_PATH"` +2. Assuming that there is only one path set. + Symlink the downloaded libcudnn files to that path: + `ln -s /usr/local/lib/python3.12/dist-packages/nvidia/cudnn/lib/libcudnn* "$LD_LIBRARY_PATH"/` + + **Note:** If `LD_LIBRARY_PATH` contains multiple paths (separated by `:`), pick one directory and use it instead of `"$LD_LIBRARY_PATH"`. For example: `/usr/lib/x86_64-linux-gnu/` + +## cuDNN Version Incompatibility + +If you encounter this error: + +``` +RuntimeError: cuDNN version incompatibility: PyTorch was compiled against (9, 10, 2) but found runtime version (9, 2, 1) +``` + +This means PyTorch is finding a different cuDNN version than the one it was compiled with. **PyTorch comes bundled with its own cuDNN**, but a conflicting cuDNN in `LD_LIBRARY_PATH` is taking precedence. + +### Solution: Remove Conflicting cuDNN from Path + +Check if there's a conflicting cuDNN path: + +```bash +echo $LD_LIBRARY_PATH +``` + +If you see paths pointing to older cuDNN installations (e.g., system-installed cuDNN or manually downloaded), try one of these: + +**Option 1: Clear LD_LIBRARY_PATH temporarily** + +```python +import os +# Let PyTorch use its bundled cuDNN +os.environ.pop('LD_LIBRARY_PATH', None) +``` + +**Option 2: Set LD_LIBRARY_PATH to only the correct version** + +```python +import os +# Point only to the cuDNN that matches PyTorch's compiled version +os.environ['LD_LIBRARY_PATH'] = "/usr/local/lib/python3.12/dist-packages/nvidia/cudnn/lib/" +``` + +**Note:** This error is unlikely on a clean install. If it occurs anyway, [open an issue](https://github.com/m-bain/whisperX/issues). If you've modified system libraries or CUDA/cuDNN, the options above should help resolve most cases. From c8f759734537d87193be62b21d32015c12c69cae Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 17 Oct 2025 15:20:04 +0000 Subject: [PATCH 071/118] feat: add hotwords argument to CLI for improved recognition of rare terms --- whisperx/__main__.py | 1 + whisperx/transcribe.py | 1 + 2 files changed, 2 insertions(+) diff --git a/whisperx/__main__.py b/whisperx/__main__.py index 5102bc0a5..e7cc62f0e 100644 --- a/whisperx/__main__.py +++ b/whisperx/__main__.py @@ -58,6 +58,7 @@ def cli(): parser.add_argument("--suppress_numerals", action="store_true", help="whether to suppress numeric symbols and currency symbols during sampling, since wav2vec2 cannot align them correctly") parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.") + parser.add_argument("--hotwords", type=str, default=None, help="hotwords/hint phrases to the model (e.g. \"WhisperX, PyAnnote, GPU\"); improves recognition of rare/technical terms") parser.add_argument("--condition_on_previous_text", type=str2bool, default=False, help="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") parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default") diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 11110c64b..04c2ab368 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -106,6 +106,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): "no_speech_threshold": args.pop("no_speech_threshold"), "condition_on_previous_text": False, "initial_prompt": args.pop("initial_prompt"), + "hotwords": args.pop("hotwords"), "suppress_tokens": [int(x) for x in args.pop("suppress_tokens").split(",")], "suppress_numerals": args.pop("suppress_numerals"), } From 6e1d1caaf4963a4b2f0c6999a0c54486b105e038 Mon Sep 17 00:00:00 2001 From: JulianFP Date: Tue, 13 May 2025 02:45:33 +0200 Subject: [PATCH 072/118] fix: incorrect type annotation in get_writer return value The audio_path attribute that the __call__ method of the ResultWriter class takes is a str, not TextIO --- whisperx/utils.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/whisperx/utils.py b/whisperx/utils.py index dfe3cf2e9..ada0deb98 100644 --- a/whisperx/utils.py +++ b/whisperx/utils.py @@ -410,7 +410,7 @@ def write_result(self, result: dict, file: TextIO, options: dict): def get_writer( output_format: str, output_dir: str -) -> Callable[[dict, TextIO, dict], None]: +) -> Callable[[dict, str, dict], None]: writers = { "txt": WriteTXT, "vtt": WriteVTT, @@ -425,7 +425,7 @@ def get_writer( if output_format == "all": all_writers = [writer(output_dir) for writer in writers.values()] - def write_all(result: dict, file: TextIO, options: dict): + def write_all(result: dict, file: str, options: dict): for writer in all_writers: writer(result, file, options) From db317c358b6b893af6e281ec80459d460fb1d874 Mon Sep 17 00:00:00 2001 From: pplkit <129310466+pplkit@users.noreply.github.com> Date: Tue, 21 Oct 2025 19:27:26 +0530 Subject: [PATCH 073/118] feat: add language-aware sentence tokenization (#1269) * feat: add language-aware sentence tokenization * feat: add missing punkt languages --------- Co-authored-by: pulkit <129310466+p1kit@users.noreply.github.com> Co-authored-by: Barabazs <31799121+Barabazs@users.noreply.github.com> --- whisperx/alignment.py | 8 +++++--- whisperx/utils.py | 23 +++++++++++++++++++++++ 2 files changed, 28 insertions(+), 3 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 756d0ba70..81c475668 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -14,7 +14,7 @@ from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor from whisperx.audio import SAMPLE_RATE, load_audio -from whisperx.utils import interpolate_nans +from whisperx.utils import interpolate_nans, PUNKT_LANGUAGES from whisperx.schema import ( AlignedTranscriptionResult, SingleSegment, @@ -192,11 +192,13 @@ def align( clean_wdx.append(wdx) + # Use language-specific Punkt model if available otherwise we fallback to English. + punkt_lang = PUNKT_LANGUAGES.get(model_lang, 'english') try: - sentence_splitter = nltk_load('tokenizers/punkt/english.pickle') + sentence_splitter = nltk_load(f'tokenizers/punkt_tab/{punkt_lang}.pickle') except LookupError: nltk.download('punkt_tab', quiet=True) - sentence_splitter = nltk_load('tokenizers/punkt/english.pickle') + sentence_splitter = nltk_load(f'tokenizers/punkt_tab/{punkt_lang}.pickle') sentence_spans = list(sentence_splitter.span_tokenize(text)) segment_data[sdx] = { diff --git a/whisperx/utils.py b/whisperx/utils.py index ada0deb98..2cf5090ac 100644 --- a/whisperx/utils.py +++ b/whisperx/utils.py @@ -126,6 +126,29 @@ LANGUAGES_WITHOUT_SPACES = ["ja", "zh"] +# Mapping of language codes to NLTK Punkt tokenizer model names +PUNKT_LANGUAGES = { + 'cs': 'czech', + 'da': 'danish', + 'de': 'german', + 'el': 'greek', + 'en': 'english', + 'es': 'spanish', + 'et': 'estonian', + 'fi': 'finnish', + 'fr': 'french', + 'it': 'italian', + 'nl': 'dutch', + 'no': 'norwegian', + 'pl': 'polish', + 'pt': 'portuguese', + 'sl': 'slovene', + 'sv': 'swedish', + 'tr': 'turkish', + "ml": "malayalam" + "ru": "russian", +} + system_encoding = sys.getdefaultencoding() if system_encoding != "utf-8": From d32ec3e3012ec4c0934f4088424c32f3f038b249 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Tue, 21 Oct 2025 09:13:50 -0600 Subject: [PATCH 074/118] fix: add missing comma --- whisperx/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/whisperx/utils.py b/whisperx/utils.py index 2cf5090ac..8c997ce9b 100644 --- a/whisperx/utils.py +++ b/whisperx/utils.py @@ -145,7 +145,7 @@ 'sl': 'slovene', 'sv': 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[PATCH 076/118] chore: drop python 3.9 support (#1328) * chore: drop python 3.9 support - Update requires-python to >=3.10 - Remove onnxruntime constraint (only needed for 3.9) - Simplify numpy (remove version markers and upper bound) - Remove pandas upper bound (<2.3.0 was for 3.9 compat) - Remove av direct dependency (transitive via faster-whisper) * chore(ci): remove python 3.9 from workflows - Update build-and-release to use Python 3.10 - Remove 3.9 from python-compatibility matrix * chore: bump version to 3.7.6 --- .github/workflows/build-and-release.yml | 2 +- .github/workflows/python-compatibility.yml | 2 +- pyproject.toml | 12 +- uv.lock | 1124 ++------------------ 4 files changed, 100 insertions(+), 1040 deletions(-) diff --git a/.github/workflows/build-and-release.yml b/.github/workflows/build-and-release.yml index c6dc04131..f98af785e 100644 --- a/.github/workflows/build-and-release.yml +++ b/.github/workflows/build-and-release.yml @@ -15,7 +15,7 @@ jobs: uses: 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"https://files.pythonhosted.org/packages/2e/54/647ade08bf0db230bfea292f893923872fd20be6ac6f53b2b936ba839d75/zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e", size = 10276, upload-time = "2025-06-08T17:06:38.034Z" }, -] From 7892a72a3026bfe3f1b7967fbc1b8fbd6b589cc5 Mon Sep 17 00:00:00 2001 From: Mr-Neutr0n <64578610+Mr-Neutr0n@users.noreply.github.com> Date: Sat, 7 Feb 2026 12:55:26 +0530 Subject: [PATCH 077/118] Optimize assign_word_speakers with interval tree for 228x speedup Replace O(n*m) pandas operations with O(n log m) interval tree queries for speaker assignment, where n = words/segments and m = diarization segments. Performance improvement: - 7-minute video (1185 words, 147 segments): 73.9s -> 0.32s (228x faster) - 3-hour podcast: Minutes of processing -> Seconds Changes: - Add IntervalTree class using sorted array + binary search - Refactor assign_word_speakers to use interval tree for overlap queries - Maintain backward compatibility with same function signature - Identical output to original implementation The interval tree uses numpy arrays for efficient storage and binary search (np.searchsorted) for O(log n) candidate finding, then filters candidates for actual overlaps. Fixes #1335 --- whisperx/diarize.py | 158 ++++++++++++++++++++++++++++++++++++-------- 1 file changed, 130 insertions(+), 28 deletions(-) diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 9f46b028f..1b2e29600 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -1,7 +1,7 @@ import numpy as np import pandas as pd from pyannote.audio import Pipeline -from typing import Optional, Union +from typing import Optional, Union, List, Tuple import torch from whisperx.audio import load_audio, SAMPLE_RATE @@ -11,6 +11,83 @@ logger = get_logger(__name__) +class IntervalTree: + """ + Simple interval tree for fast overlap queries using sorted array + binary search. + + Uses O(n) space and provides O(log n) query time instead of O(n) linear scan. + This achieves ~228x speedup for speaker assignment in long-form content. + """ + + def __init__(self, intervals: List[Tuple[float, float, str]]): + """ + Initialize the interval tree with diarization segments. + + Args: + intervals: List of (start, end, speaker) tuples + """ + if not intervals: + self.starts = np.array([]) + self.ends = np.array([]) + self.speakers: List[str] = [] + return + + # Sort intervals by start time for binary search + sorted_intervals = sorted(intervals, key=lambda x: x[0]) + self.starts = np.array([i[0] for i in sorted_intervals], dtype=np.float64) + self.ends = np.array([i[1] for i in sorted_intervals], dtype=np.float64) + self.speakers = [i[2] for i in sorted_intervals] + + def query(self, start: float, end: float) -> List[Tuple[str, float]]: + """ + Find all intervals that overlap with [start, end] and compute intersection. + + Args: + start: Query interval start time + end: Query interval end time + + Returns: + List of (speaker, intersection_duration) tuples for overlapping segments + """ + if len(self.starts) == 0: + return [] + + # Binary search to find candidate intervals + # Only intervals with start < end could overlap + right_idx = np.searchsorted(self.starts, end, side='left') + if right_idx == 0: + return [] + + # Check candidates for actual overlap + candidates = slice(0, right_idx) + overlaps = (self.starts[candidates] < end) & (self.ends[candidates] > start) + + results = [] + for idx in np.where(overlaps)[0]: + intersection = min(self.ends[idx], end) - max(self.starts[idx], start) + if intersection > 0: + results.append((self.speakers[idx], intersection)) + return results + + def find_nearest(self, time: float) -> Optional[str]: + """ + Find the speaker of the nearest segment to a given time point. + + Args: + time: Time point to find nearest segment for + + Returns: + Speaker ID of nearest segment, or None if no segments exist + """ + if len(self.starts) == 0: + return None + + # Calculate midpoints of all segments + mids = (self.starts + self.ends) / 2 + nearest_idx = np.argmin(np.abs(mids - time)) + return self.speakers[nearest_idx] + + class DiarizationPipeline: def __init__( self, @@ -96,6 +173,9 @@ def assign_word_speakers( """ Assign speakers to words and segments in the transcript. + Uses an interval tree for O(log n) overlap queries instead of O(n) linear scan, + achieving ~228x speedup for long-form content (3+ hour podcasts). + Args: diarize_df: Diarization dataframe from DiarizationPipeline transcript_result: Transcription result to augment with speaker labels @@ -105,36 +185,58 @@ def assign_word_speakers( Returns: Updated transcript_result with speaker assignments and optionally embeddings """ - transcript_segments = transcript_result["segments"] + transcript_segments = transcript_result.get("segments", []) + if not transcript_segments or diarize_df is None or len(diarize_df) == 0: + return transcript_result + + # Build interval tree from diarization segments for O(log n) queries + intervals = [ + (row['start'], row['end'], row['speaker']) + for _, row in diarize_df.iterrows() + ] + tree = IntervalTree(intervals) + for seg in transcript_segments: - # assign speaker to segment (if any) - diarize_df['intersection'] = np.minimum(diarize_df['end'], seg['end']) - np.maximum(diarize_df['start'], seg['start']) - diarize_df['union'] = np.maximum(diarize_df['end'], seg['end']) - np.minimum(diarize_df['start'], seg['start']) - # remove no hit, otherwise we look for closest (even negative intersection...) - if not fill_nearest: - dia_tmp = diarize_df[diarize_df['intersection'] > 0] - else: - dia_tmp = diarize_df - if len(dia_tmp) > 0: - # sum over speakers - speaker = dia_tmp.groupby("speaker")["intersection"].sum().sort_values(ascending=False).index[0] - seg["speaker"] = speaker - - # assign speaker to words + seg_start = seg.get('start', 0.0) + seg_end = seg.get('end', 0.0) + + # Query overlapping segments using interval tree + overlaps = tree.query(seg_start, seg_end) + + if overlaps: + # Sum intersection durations per speaker and pick the dominant one + speaker_intersections: dict[str, float] = {} + for speaker, intersection in overlaps: + speaker_intersections[speaker] = speaker_intersections.get(speaker, 0.0) + intersection + seg['speaker'] = max(speaker_intersections.items(), key=lambda x: x[1])[0] + elif fill_nearest: + # Find nearest segment if no overlap + seg_mid = (seg_start + seg_end) / 2 + nearest_speaker = tree.find_nearest(seg_mid) + if nearest_speaker: + seg['speaker'] = nearest_speaker + + # Assign speaker to words if 'words' in seg: for word in seg['words']: - if 'start' in word: - diarize_df['intersection'] = np.minimum(diarize_df['end'], word['end']) - np.maximum(diarize_df['start'], word['start']) - diarize_df['union'] = np.maximum(diarize_df['end'], word['end']) - np.minimum(diarize_df['start'], word['start']) - # remove no hit - if not fill_nearest: - dia_tmp = diarize_df[diarize_df['intersection'] > 0] - else: - dia_tmp = diarize_df - if len(dia_tmp) > 0: - # sum over speakers - speaker = dia_tmp.groupby("speaker")["intersection"].sum().sort_values(ascending=False).index[0] - word["speaker"] = speaker + if 'start' not in word: + continue + + word_start = word['start'] + word_end = word.get('end', word_start) + + word_overlaps = tree.query(word_start, word_end) + + if word_overlaps: + speaker_intersections = {} + for speaker, intersection in word_overlaps: + speaker_intersections[speaker] = speaker_intersections.get(speaker, 0.0) + intersection + word['speaker'] = max(speaker_intersections.items(), key=lambda x: x[1])[0] + elif fill_nearest: + word_mid = (word_start + word_end) / 2 + nearest_speaker = tree.find_nearest(word_mid) + if nearest_speaker: + word['speaker'] = nearest_speaker # Add speaker embeddings to the result if provided if speaker_embeddings is not None: From 2b5ae8cafad72f325b7fb89a7cb62856f78891dd Mon Sep 17 00:00:00 2001 From: carlos Date: Mon, 9 Feb 2026 09:55:29 +0000 Subject: [PATCH 078/118] [BugFix] Type hint fix in decode_batch List[str] not str: --- whisperx/asr.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/whisperx/asr.py b/whisperx/asr.py index c35900cf9..eb844ef49 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -76,7 +76,7 @@ def generate_segment_batched( tokens_batch = [x.sequences_ids[0] for x in result] - def decode_batch(tokens: List[List[int]]) -> str: + def decode_batch(tokens: List[List[int]]) -> List[str]: res = [] for tk in tokens: res.append([token for token in tk if token < tokenizer.eot]) From 570b08b7be3d064d470b228b2d56f11bb7f9d7c8 Mon Sep 17 00:00:00 2001 From: "p.sacco" Date: Tue, 10 Feb 2026 10:44:58 +0000 Subject: [PATCH 079/118] fix: add no_repeat_ngram_size and repetition_penalty options to WhisperModel --- whisperx/asr.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/whisperx/asr.py b/whisperx/asr.py index c35900cf9..1ed22e52d 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -72,6 +72,8 @@ def generate_segment_batched( max_length=self.max_length, suppress_blank=options.suppress_blank, suppress_tokens=options.suppress_tokens, + no_repeat_ngram_size=options.no_repeat_ngram_size, + repetition_penalty=options.repetition_penalty, ) tokens_batch = [x.sequences_ids[0] for x in result] From cc6f627a39e69f118047ff492cd1eeca3ca92172 Mon Sep 17 00:00:00 2001 From: carlos Date: Tue, 10 Feb 2026 14:38:13 +0000 Subject: [PATCH 080/118] [BugFix] The variable I removed was not being used anyhwere. --- whisperx/asr.py | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/whisperx/asr.py b/whisperx/asr.py index c35900cf9..0bee277cc 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -58,11 +58,7 @@ def generate_segment_batched( ) encoder_output = self.encode(features) - - max_initial_timestamp_index = int( - round(options.max_initial_timestamp / self.time_precision) - ) - + result = self.model.generate( encoder_output, [prompt] * batch_size, From c4c1242edbeb68a91506fa142b75a0e2e0fcd784 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 13 Feb 2026 12:53:49 +0100 Subject: [PATCH 081/118] fix: derive SRT/VTT cue times from word-level timestamps (#1347) * fix: derive SRT/VTT cue times from word-level timestamps (#1315) Subtitle cue start/end times were sourced from VAD segment boundaries instead of word-level timestamps from forced alignment. This caused cues to appear prematurely and could produce backwards chronological ordering when VAD segments overlap. Use min(word starts) / max(word ends) for cue timing, falling back to segment-level times only when all words are unalignable. Co-Authored-By: Claude Opus 4.6 * chore: bump version to 3.7.7 in pyproject.toml --------- Co-authored-by: Claude-Assistant --- pyproject.toml | 2 +- uv.lock | 6 +----- whisperx/utils.py | 17 +++++++++++++---- 3 files changed, 15 insertions(+), 10 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 2a95e538f..f885d42c2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.7.6" +version = "3.7.7" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.10, <3.14" diff --git a/uv.lock b/uv.lock index b8bd294eb..59a723a0e 100644 --- a/uv.lock +++ b/uv.lock @@ -782,7 +782,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/7d/ed/6bfa4109fcb23a58819600392564fea69cdc6551ffd5e69ccf1d52a40cbc/greenlet-3.2.4-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:8c68325b0d0acf8d91dde4e6f930967dd52a5302cd4062932a6b2e7c2969f47c", size = 271061, upload-time = "2025-08-07T13:17:15.373Z" }, { url = "https://files.pythonhosted.org/packages/2a/fc/102ec1a2fc015b3a7652abab7acf3541d58c04d3d17a8d3d6a44adae1eb1/greenlet-3.2.4-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:94385f101946790ae13da500603491f04a76b6e4c059dab271b3ce2e283b2590", size = 629475, upload-time = "2025-08-07T13:42:54.009Z" }, { url = "https://files.pythonhosted.org/packages/c5/26/80383131d55a4ac0fb08d71660fd77e7660b9db6bdb4e8884f46d9f2cc04/greenlet-3.2.4-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:f10fd42b5ee276335863712fa3da6608e93f70629c631bf77145021600abc23c", size = 640802, upload-time = "2025-08-07T13:45:25.52Z" }, - 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for subtitle, _ in iterate_subtitles(): - sstart, ssend, speaker = _[0] - subtitle_start = self.format_timestamp(sstart) - subtitle_end = self.format_timestamp(ssend) + for subtitle, times in iterate_subtitles(): + speaker = times[0][2] + + # Derive cue times from word-level timestamps when available, + # falling back to segment-level times for fully unalignable subtitles. + word_starts = [w["start"] for w in subtitle if "start" in w] + word_ends = [w["end"] for w in subtitle if "end" in w] + if word_starts and word_ends: + subtitle_start = self.format_timestamp(min(word_starts)) + subtitle_end = self.format_timestamp(max(word_ends)) + else: + subtitle_start = self.format_timestamp(times[0][0]) + subtitle_end = self.format_timestamp(times[0][1]) if result["language"] in LANGUAGES_WITHOUT_SPACES: subtitle_text = "".join([word["word"] for word in subtitle]) else: From 6187d25a440e6aba916995b01ff5a4d3af894045 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Fri, 13 Feb 2026 21:52:32 +0100 Subject: [PATCH 082/118] feat: migrate to pyannote-audio v4 with speaker-diarization-community-1 (#1349) * feat: upgrade pyannote-audio dependency to v4 * fix: rename use_auth_token to token for pyannote-audio v4 compatibility * fix: add omegaconf dep * fix: use structured output API for pyannote-audio v4 diarization pyannote-audio 4.x no longer returns a plain Annotation (or tuple when> return_embeddings=True). It now returns a structured output with speaker_diarization and speaker_embeddings attributes. * feat: switch default diarization model to speaker-diarization-community-1 Update default from pyannote/speaker-diarization-3.1 to pyannote/speaker-diarization-community-1 (pyannote-audio v4), add CC-BY-4.0 attribution, and update README for v4 API changes. * fix: correct markdown link formatting for silero-vad in README.md * chore: update version to 3.8.0 Co-authored-by: Giorgio Azzinnaro --- README.md | 11 +- pyproject.toml | 11 +- uv.lock | 575 +++++++++++++++++--------------------- whisperx/__main__.py | 2 +- whisperx/asr.py | 2 +- whisperx/diarize.py | 31 +- whisperx/transcribe.py | 2 +- whisperx/vads/pyannote.py | 12 +- 8 files changed, 286 insertions(+), 360 deletions(-) diff --git a/README.md b/README.md index fae1e0753..fe8610357 100644 --- a/README.md +++ b/README.md @@ -113,10 +113,7 @@ You may also need to install ffmpeg, rust etc. Follow openAI instructions here h ### Speaker Diarization -To **enable Speaker Diarization**, include your Hugging Face access token (read) that you can generate from [Here](https://huggingface.co/settings/tokens) after the `--hf_token` argument and accept the user agreement for the following models: [Segmentation](https://huggingface.co/pyannote/segmentation-3.0) and [Speaker-Diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) (if you choose to use Speaker-Diarization 2.x, follow requirements [here](https://huggingface.co/pyannote/speaker-diarization) instead.) - -> **Note**
-> As of Oct 11, 2023, there is a known issue regarding slow performance with pyannote/Speaker-Diarization-3.0 in whisperX. It is due to dependency conflicts between faster-whisper and pyannote-audio 3.0.0. Please see [this issue](https://github.com/m-bain/whisperX/issues/499) for more details and potential workarounds. +To **enable Speaker Diarization**, include your Hugging Face access token (read) that you can generate from [Here](https://huggingface.co/settings/tokens) after the `--hf_token` argument and accept the user agreement for the [speaker-diarization-community-1](https://huggingface.co/pyannote/speaker-diarization-community-1) model.

Usage 💬 (command line)

@@ -197,7 +194,7 @@ print(result["segments"]) # after alignment # import gc; import torch; gc.collect(); torch.cuda.empty_cache(); del model_a # 3. Assign speaker labels -diarize_model = DiarizationPipeline(use_auth_token=YOUR_HF_TOKEN, device=device) +diarize_model = DiarizationPipeline(token=YOUR_HF_TOKEN, device=device) # add min/max number of speakers if known diarize_segments = diarize_model(audio) @@ -291,8 +288,8 @@ And uses the wonderful pyannote VAD / Diarization https://github.com/pyannote/py Valuable VAD & Diarization Models from: -- [pyannote audio][https://github.com/pyannote/pyannote-audio] -- [silero vad][https://github.com/snakers4/silero-vad] +- [pyannote-audio](https://github.com/pyannote/pyannote-audio) — Speaker diarization powered by the [speaker-diarization-community-1](https://huggingface.co/pyannote/speaker-diarization-community-1) model, licensed under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) by [pyannoteAI](https://www.pyannote.ai) +- [silero-vad](https://github.com/snakers4/silero-vad) Great backend from [faster-whisper](https://github.com/guillaumekln/faster-whisper) and [CTranslate2](https://github.com/OpenNMT/CTranslate2) diff --git a/pyproject.toml b/pyproject.toml index f885d42c2..61dc5df44 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.7.7" +version = "3.8.0" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.10, <3.14" @@ -13,8 +13,9 @@ dependencies = [ "faster-whisper>=1.1.1", "nltk>=3.9.1", "numpy>=2.1.0", + "omegaconf>=2.3.0", "pandas>=2.2.3", - "pyannote-audio>=3.3.2,<4.0.0", + "pyannote-audio>=4.0.0", "huggingface-hub<1.0.0", "torch~=2.8.0", "torchaudio~=2.8.0", @@ -36,6 +37,12 @@ include-package-data = true where = ["."] include = ["whisperx*"] +# torchcodec (transitive dep of pyannote-audio >=4) has no wheels for Linux aarch64 +[tool.uv] +override-dependencies = [ + "torchcodec>=0.6.0; (sys_platform == 'linux' and platform_machine 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parser.add_argument("--diarize", action="store_true", help="Apply diarization to assign speaker labels to each segment/word") parser.add_argument("--min_speakers", default=None, type=int, help="Minimum number of speakers to in audio file") parser.add_argument("--max_speakers", default=None, type=int, help="Maximum number of speakers to in audio file") - parser.add_argument("--diarize_model", default="pyannote/speaker-diarization-3.1", type=str, help="Name of the speaker diarization model to use") + parser.add_argument("--diarize_model", default="pyannote/speaker-diarization-community-1", type=str, help="Name of the speaker diarization model to use") parser.add_argument("--speaker_embeddings", action="store_true", help="Include speaker embeddings in JSON output (only works with --diarize)") parser.add_argument("--temperature", type=float, default=0, help="temperature to use for sampling") diff --git a/whisperx/asr.py b/whisperx/asr.py index bddc0b78c..f9456be8a 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -407,7 +407,7 @@ def load_model( device_vad = f'cuda:{device_index}' else: device_vad = device - vad_model = Pyannote(torch.device(device_vad), use_auth_token=None, **default_vad_options) + vad_model = Pyannote(torch.device(device_vad), token=None, **default_vad_options) else: raise ValueError(f"Invalid vad_method: {vad_method}") diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 1b2e29600..59b0f2f1b 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -92,14 +92,14 @@ class DiarizationPipeline: def __init__( self, model_name=None, - use_auth_token=None, + token=None, device: Optional[Union[str, torch.device]] = "cpu", ): if isinstance(device, str): device = torch.device(device) - model_config = model_name or "pyannote/speaker-diarization-3.1" + model_config = model_name or "pyannote/speaker-diarization-community-1" logger.info(f"Loading diarization model: {model_config}") - self.model = Pipeline.from_pretrained(model_config, use_auth_token=use_auth_token).to(device) + self.model = Pipeline.from_pretrained(model_config, token=token).to(device) def __call__( self, @@ -132,22 +132,15 @@ def __call__( 'sample_rate': SAMPLE_RATE } - if return_embeddings: - diarization, embeddings = self.model( - audio_data, - num_speakers=num_speakers, - min_speakers=min_speakers, - max_speakers=max_speakers, - return_embeddings=True, - ) - else: - diarization = self.model( - audio_data, - num_speakers=num_speakers, - min_speakers=min_speakers, - max_speakers=max_speakers, - ) - embeddings = None + output = self.model( + audio_data, + num_speakers=num_speakers, + min_speakers=min_speakers, + max_speakers=max_speakers, + ) + + diarization = output.speaker_diarization + embeddings = output.speaker_embeddings if return_embeddings else None diarize_df = pd.DataFrame(diarization.itertracks(yield_label=True), columns=['segment', 'label', 'speaker']) diarize_df['start'] = diarize_df['segment'].apply(lambda x: x.start) diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 04c2ab368..0aae410c8 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -214,7 +214,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): logger.info("Performing diarization...") logger.info(f"Using model: {diarize_model_name}") results = [] - diarize_model = DiarizationPipeline(model_name=diarize_model_name, use_auth_token=hf_token, device=device) + diarize_model = DiarizationPipeline(model_name=diarize_model_name, token=hf_token, device=device) for result, input_audio_path in tmp_results: diarize_result = diarize_model( input_audio_path, diff --git a/whisperx/vads/pyannote.py b/whisperx/vads/pyannote.py index 0e806bb19..28c1fbdf5 100644 --- a/whisperx/vads/pyannote.py +++ b/whisperx/vads/pyannote.py @@ -18,7 +18,7 @@ logger = get_logger(__name__) -def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, use_auth_token=None, model_fp=None): +def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, token=None, model_fp=None): model_dir = torch.hub._get_torch_home() main_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) @@ -40,7 +40,7 @@ def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, use_auth_token=Non model_bytes = open(model_fp, "rb").read() - vad_model = Model.from_pretrained(model_fp, use_auth_token=use_auth_token) + vad_model = Model.from_pretrained(model_fp, token=token) hyperparameters = {"onset": vad_onset, "offset": vad_offset, "min_duration_on": 0.1, @@ -192,11 +192,11 @@ def __init__( self, segmentation: PipelineModel = "pyannote/segmentation", fscore: bool = False, - use_auth_token: Union[Text, None] = None, + token: Union[Text, None] = None, **inference_kwargs, ): - super().__init__(segmentation=segmentation, fscore=fscore, use_auth_token=use_auth_token, **inference_kwargs) + super().__init__(segmentation=segmentation, fscore=fscore, token=token, **inference_kwargs) def apply(self, file: AudioFile, hook: Optional[Callable] = None) -> Annotation: """Apply voice activity detection @@ -234,10 +234,10 @@ def apply(self, file: AudioFile, hook: Optional[Callable] = None) -> Annotation: class Pyannote(Vad): - def __init__(self, device, use_auth_token=None, model_fp=None, **kwargs): + def __init__(self, device, token=None, model_fp=None, **kwargs): logger.info("Performing voice activity detection using Pyannote...") super().__init__(kwargs['vad_onset']) - self.vad_pipeline = load_vad_model(device, use_auth_token=use_auth_token, model_fp=model_fp) + self.vad_pipeline = load_vad_model(device, token=token, model_fp=model_fp) def __call__(self, audio: AudioFile, **kwargs): return self.vad_pipeline(audio) From 9d687e015e41e001900a5871c9db3bf93bafea14 Mon Sep 17 00:00:00 2001 From: MrPrayer Date: Sat, 14 Feb 2026 16:11:52 +0300 Subject: [PATCH 083/118] fix: propagate --model_dir and --model_cache_only to all model loading paths (#1285) - Add `model_cache_only` param to `load_align_model()`, pass as `local_files_only` to HuggingFace `from_pretrained` calls - Forward `model_dir` and `model_cache_only` to both `load_align_model` call sites (initial load and language-change reload) - Add `cache_dir` param to `DiarizationPipeline.__init__`, forward to pyannote `Pipeline.from_pretrained` - Pass `--model_dir` as `cache_dir` when constructing `DiarizationPipeline` in CLI Previously only the ASR model respected these flags. Alignment and diarization models would always download from HuggingFace to the default cache, breaking offline and custom-cache workflows. --------- Co-authored-by: Barabazs <31799121+Barabazs@users.noreply.github.com> --- whisperx/alignment.py | 6 +++--- whisperx/diarize.py | 3 ++- whisperx/transcribe.py | 6 +++--- 3 files changed, 8 insertions(+), 7 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 81c475668..ce92d7a4f 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -77,7 +77,7 @@ } -def load_align_model(language_code: str, device: str, model_name: Optional[str] = None, model_dir=None): +def load_align_model(language_code: str, device: str, model_name: Optional[str] = None, model_dir=None, model_cache_only: bool = False): if model_name is None: # use default model if language_code in DEFAULT_ALIGN_MODELS_TORCH: @@ -98,8 +98,8 @@ def load_align_model(language_code: str, device: str, model_name: Optional[str] align_dictionary = {c.lower(): i for i, c in enumerate(labels)} else: try: - processor = Wav2Vec2Processor.from_pretrained(model_name, cache_dir=model_dir) - align_model = Wav2Vec2ForCTC.from_pretrained(model_name, cache_dir=model_dir) + processor = Wav2Vec2Processor.from_pretrained(model_name, cache_dir=model_dir, local_files_only=model_cache_only) + align_model = Wav2Vec2ForCTC.from_pretrained(model_name, cache_dir=model_dir, local_files_only=model_cache_only) except Exception as e: print(e) print(f"Error loading model from huggingface, check https://huggingface.co/models for finetuned wav2vec2.0 models") diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 59b0f2f1b..041fb129d 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -94,12 +94,13 @@ def __init__( model_name=None, token=None, device: Optional[Union[str, torch.device]] = "cpu", + cache_dir=None, ): if isinstance(device, str): device = torch.device(device) model_config = model_name or "pyannote/speaker-diarization-community-1" logger.info(f"Loading diarization model: {model_config}") - self.model = Pipeline.from_pretrained(model_config, token=token).to(device) + self.model = Pipeline.from_pretrained(model_config, token=token, cache_dir=cache_dir).to(device) def __call__( self, diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 0aae410c8..b1ab2e01e 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -166,7 +166,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): tmp_results = results results = [] align_model, align_metadata = load_align_model( - align_language, device, model_name=align_model + align_language, device, model_name=align_model, model_dir=model_dir, model_cache_only=model_cache_only ) for result, audio_path in tmp_results: # >> Align @@ -183,7 +183,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): f"New language found ({result['language']})! Previous was ({align_metadata['language']}), loading new alignment model for new language..." ) align_model, align_metadata = load_align_model( - result["language"], device + result["language"], device, model_dir=model_dir, model_cache_only=model_cache_only ) logger.info("Performing alignment...") result: AlignedTranscriptionResult = align( @@ -214,7 +214,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): logger.info("Performing diarization...") logger.info(f"Using model: {diarize_model_name}") results = [] - diarize_model = DiarizationPipeline(model_name=diarize_model_name, token=hf_token, device=device) + diarize_model = DiarizationPipeline(model_name=diarize_model_name, token=hf_token, device=device, cache_dir=model_dir) for result, input_audio_path in tmp_results: diarize_result = diarize_model( input_audio_path, From 1baf8d2314b9622636346ae59c344e531f5fb4ba Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Sat, 14 Feb 2026 14:34:31 +0100 Subject: [PATCH 084/118] feat: pass --hf_token to WhisperModel for gated model support Forward the existing --hf_token CLI argument to faster-whisper's WhisperModel via a new use_auth_token parameter on load_model(), enabling downloads of gated/private HuggingFace models. --- whisperx/asr.py | 4 +++- whisperx/transcribe.py | 1 + 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/whisperx/asr.py b/whisperx/asr.py index f9456be8a..7540770f4 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -314,6 +314,7 @@ def load_model( download_root: Optional[str] = None, local_files_only=False, threads=4, + use_auth_token: Optional[Union[str, bool]] = None, ) -> FasterWhisperPipeline: """Load a Whisper model for inference. Args: @@ -341,7 +342,8 @@ def load_model( compute_type=compute_type, download_root=download_root, local_files_only=local_files_only, - cpu_threads=threads) + cpu_threads=threads, + use_auth_token=use_auth_token) if language is not None: tokenizer = Tokenizer(model.hf_tokenizer, model.model.is_multilingual, task=task, language=language) else: diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index b1ab2e01e..7c8be6794 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -141,6 +141,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): task=task, local_files_only=model_cache_only, threads=faster_whisper_threads, + use_auth_token=hf_token, ) for audio_path in args.pop("audio"): From 42beab1f9f2ecdc29c4e9d6c399506feca373b66 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Sat, 14 Feb 2026 15:00:56 +0100 Subject: [PATCH 085/118] chore: bump version to 3.8.1 --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 61dc5df44..15d392da6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.8.0" +version = "3.8.1" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.10, <3.14" diff --git a/uv.lock b/uv.lock index 66992af56..421c50445 100644 --- a/uv.lock +++ b/uv.lock @@ -3026,7 +3026,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.8.0" +version = "3.8.1" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, From 1430e4330010888b42e6cdd95bb384bd13564801 Mon Sep 17 00:00:00 2001 From: carlos Date: Sat, 14 Feb 2026 11:27:17 +0000 Subject: [PATCH 086/118] [fix] Batch context is updated each time. It works with the initial prompt added. Ran pdb to make sure and check output. Long audio works. Existing Logic is correct without flag. --- whisperx/__main__.py | 1 + whisperx/asr.py | 140 +++++++++++++++++++++++++++++++++++------ whisperx/transcribe.py | 2 + 3 files changed, 123 insertions(+), 20 deletions(-) diff --git a/whisperx/__main__.py b/whisperx/__main__.py index dbb92fc4f..0e523910a 100644 --- a/whisperx/__main__.py +++ b/whisperx/__main__.py @@ -60,6 +60,7 @@ def cli(): parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.") parser.add_argument("--hotwords", type=str, default=None, help="hotwords/hint phrases to the model (e.g. \"WhisperX, PyAnnote, GPU\"); improves recognition of rare/technical terms") parser.add_argument("--condition_on_previous_text", type=str2bool, default=False, help="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") + parser.add_argument("--batch_context", action="store_true", help="use previous batch's transcription as context for the next batch (slower but more coherent across batches)") parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default") parser.add_argument("--temperature_increment_on_fallback", type=optional_float, default=0.2, help="temperature to increase when falling back when the decoding fails to meet either of the thresholds below") diff --git a/whisperx/asr.py b/whisperx/asr.py index 7540770f4..0f9a08a5b 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -40,28 +40,61 @@ def generate_segment_batched( tokenizer: Tokenizer, options: TranscriptionOptions, encoder_output=None, + use_batch_context: bool = False, + previous_batch_context_tokens: List[List[int]] = None, ): batch_size = features.shape[0] - all_tokens = [] - prompt_reset_since = 0 - if options.initial_prompt is not None: - initial_prompt = " " + options.initial_prompt.strip() - initial_prompt_tokens = tokenizer.encode(initial_prompt) - all_tokens.extend(initial_prompt_tokens) - previous_tokens = all_tokens[prompt_reset_since:] - prompt = self.get_prompt( - tokenizer, - previous_tokens, - without_timestamps=options.without_timestamps, - prefix=options.prefix, - hotwords=options.hotwords - ) + if previous_batch_context_tokens is None: + previous_batch_context_tokens = [[] for _ in range(batch_size)] + + prompts = [] + batch_tokens = [] + for i in range(batch_size): + all_tokens = [] + if options.initial_prompt is not None: + initial_prompt = " " + options.initial_prompt.strip() + initial_prompt_tokens = tokenizer.encode(initial_prompt) + all_tokens.extend(initial_prompt_tokens) + + if use_batch_context: + # previous_batch_context_tokens is now List[List[int]] + # verify we have enough context history lists + if i < len(previous_batch_context_tokens): + ctx = previous_batch_context_tokens[i] + if ctx: + max_prompt_tokens = 223 + current_len = len(all_tokens) + available = max_prompt_tokens - current_len + if available > 0: + all_tokens.extend(ctx[-available:]) + batch_tokens.append(all_tokens) + + # Calculate max length in the batch + max_batch_tokens = max([len(t) for t in batch_tokens] + [0]) + + # Pad tokens to ensure consistent length across batch + # We use left-padding with EOT to preserve the immediate context before SOT + for i in range(batch_size): + current_tokens = batch_tokens[i] + if len(current_tokens) < max_batch_tokens: + padding_len = max_batch_tokens - len(current_tokens) + # Pad with EOT (End of Transcript) which is usually ignored or treated as break + current_tokens = [tokenizer.eot] * padding_len + current_tokens + + prompt = self.get_prompt( + tokenizer, + current_tokens, + without_timestamps=options.without_timestamps, + prefix=options.prefix, + hotwords=options.hotwords + ) + prompts.append(prompt) encoder_output = self.encode(features) result = self.model.generate( encoder_output, - [prompt] * batch_size, + prompts, beam_size=options.beam_size, patience=options.patience, length_penalty=options.length_penalty, @@ -82,9 +115,9 @@ def decode_batch(tokens: List[List[int]]) -> List[str]: return tokenizer.tokenizer.decode_batch(res) text = decode_batch(tokens_batch) - return text + def encode(self, features: np.ndarray) -> ctranslate2.StorageView: # When the model is running on multiple GPUs, the encoder output should be moved # to the CPU since we don't know which GPU will handle the next job. @@ -115,6 +148,7 @@ def __init__( framework="pt", language: Optional[str] = None, suppress_numerals: bool = False, + use_batch_context: bool = False, **kwargs, ): self.model = model @@ -122,6 +156,7 @@ def __init__( self.options = options self.preset_language = language self.suppress_numerals = suppress_numerals + self.use_batch_context = use_batch_context self._batch_size = kwargs.pop("batch_size", None) self._num_workers = 1 self._preprocess_params, self._forward_params, self._postprocess_params = self._sanitize_parameters(**kwargs) @@ -142,6 +177,8 @@ def __init__( super(Pipeline, self).__init__() self.vad_model = vad self._vad_params = vad_params + self.previous_batch_context_tokens = [] + def _sanitize_parameters(self, **kwargs): preprocess_kwargs = {} @@ -160,7 +197,35 @@ def preprocess(self, audio): return {'inputs': features} def _forward(self, model_inputs): - outputs = self.model.generate_segment_batched(model_inputs['inputs'], self.tokenizer, self.options) + current_batch_size = model_inputs['inputs'].shape[0] + # Ideally, batch[i] corresponds to stream[i]. + # This holds if batch_size == number of streams. + valid_contexts = self.previous_batch_context_tokens[:current_batch_size] + + outputs = self.model.generate_segment_batched( + model_inputs['inputs'], + self.tokenizer, + self.options, + use_batch_context=self.use_batch_context, + previous_batch_context_tokens=valid_contexts, + ) + if self.use_batch_context: + initial_prompt_length = 0 + if self.options.initial_prompt is not None: + initial_prompt = " " + self.options.initial_prompt.strip() + initial_prompt_length = len(self.tokenizer.encode(initial_prompt)) + + # Use 220 instead of 224 to be safe + max_context_window = max(0, 220 - initial_prompt_length) + + for i, text in enumerate(outputs): + if i < len(self.previous_batch_context_tokens): + # Filter out special tokens (timestamps, SOT, EOT, etc.) + # We only want the text content for context. + tokens = [t for t in self.tokenizer.encode(text) if t < self.tokenizer.eot] + self.previous_batch_context_tokens[i].extend(tokens) + self.previous_batch_context_tokens[i] = self.previous_batch_context_tokens[i][-max_context_window:] + return {'text': outputs} def postprocess(self, model_outputs): @@ -201,6 +266,14 @@ def transcribe( ) -> TranscriptionResult: if isinstance(audio, str): audio = load_audio(audio) + + batch_size = batch_size or self._batch_size + # Initialize context for each stream. + # We have 'batch_size' concurrent streams. + if batch_size is None or batch_size < 1: + batch_size = 1 + + self.previous_batch_context_tokens = [[] for _ in range(batch_size)] def data(audio, segments): for seg in segments: @@ -252,10 +325,33 @@ def data(audio, segments): new_suppressed_tokens = numeral_symbol_tokens + self.options.suppress_tokens new_suppressed_tokens = list(set(new_suppressed_tokens)) self.options = replace(self.options, suppress_tokens=new_suppressed_tokens) - + segments: List[SingleSegment] = [] batch_size = batch_size or self._batch_size total_segments = len(vad_segments) + + if batch_size > 1: + num_streams = batch_size + # Distribute segments into streams + # Manual split + k, m = divmod(len(vad_segments), num_streams) + # lengths of each part: first m parts have k+1, rest have k + stream_segments = [] + start_idx = 0 + for i in range(num_streams): + part_len = k + 1 if i < m else k + stream_segments.append(vad_segments[start_idx : start_idx + part_len]) + start_idx += part_len + # Interleave + # We need to pick [s0[0], s1[0], s2[0]... s0[1], s1[1]...] + interleaved_segments = [] + max_len = max(len(s) for s in stream_segments) + for i in range(max_len): + for stream in stream_segments: + if i < len(stream): + interleaved_segments.append(stream[i]) + vad_segments = interleaved_segments + for idx, out in enumerate(self.__call__(data(audio, vad_segments), batch_size=batch_size, num_workers=num_workers)): if print_progress: base_progress = ((idx + 1) / total_segments) * 100 @@ -273,6 +369,8 @@ def data(audio, segments): "end": round(vad_segments[idx]['end'], 3) } ) + # Sort segments by start time to restore original order + segments.sort(key=lambda x: x['start']) # revert the tokenizer if multilingual inference is enabled if self.preset_language is None: @@ -289,8 +387,8 @@ def detect_language(self, audio: np.ndarray) -> str: logger.warning("Audio is shorter than 30s, language detection may be inaccurate") model_n_mels = self.model.feat_kwargs.get("feature_size") segment = log_mel_spectrogram(audio[: N_SAMPLES], - n_mels=model_n_mels if model_n_mels is not None else 80, - padding=0 if audio.shape[0] >= N_SAMPLES else N_SAMPLES - audio.shape[0]) + n_mels=model_n_mels if model_n_mels is not None else 80, + padding=0 if audio.shape[0] >= N_SAMPLES else N_SAMPLES - audio.shape[0]) encoder_output = self.model.encode(segment) results = self.model.model.detect_language(encoder_output) language_token, language_probability = results[0][0] @@ -315,6 +413,7 @@ def load_model( local_files_only=False, threads=4, use_auth_token: Optional[Union[str, bool]] = None, + use_batch_context: bool = False, ) -> FasterWhisperPipeline: """Load a Whisper model for inference. Args: @@ -421,4 +520,5 @@ def load_model( language=language, suppress_numerals=suppress_numerals, vad_params=default_vad_options, + use_batch_context=use_batch_context, ) diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 7c8be6794..92a634dd1 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -63,6 +63,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): diarize_model_name: str = args.pop("diarize_model") print_progress: bool = args.pop("print_progress") return_speaker_embeddings: bool = args.pop("speaker_embeddings") + batch_context: bool = args.pop("batch_context", False) if return_speaker_embeddings and not diarize: warnings.warn("--speaker_embeddings has no effect without --diarize") @@ -142,6 +143,7 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): local_files_only=model_cache_only, threads=faster_whisper_threads, use_auth_token=hf_token, + use_batch_context=batch_context, ) for audio_path in args.pop("audio"): From e33bb1ec25bd743899ff6de2a36d7f4abd1ba3a3 Mon Sep 17 00:00:00 2001 From: carlos Date: Sat, 14 Feb 2026 11:54:07 +0000 Subject: [PATCH 087/118] Although the existing commit worked, inital prompt was in the loop no need. --- whisperx/asr.py | 41 ++++++++++++++--------------------------- 1 file changed, 14 insertions(+), 27 deletions(-) diff --git a/whisperx/asr.py b/whisperx/asr.py index 0f9a08a5b..0931d88bf 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -46,49 +46,36 @@ def generate_segment_batched( batch_size = features.shape[0] if previous_batch_context_tokens is None: previous_batch_context_tokens = [[] for _ in range(batch_size)] - - prompts = [] + + initial_prompt_tokens = [] + if options.initial_prompt is not None: + initial_prompt = " " + options.initial_prompt.strip() + initial_prompt_tokens = tokenizer.encode(initial_prompt) + batch_tokens = [] for i in range(batch_size): - all_tokens = [] - if options.initial_prompt is not None: - initial_prompt = " " + options.initial_prompt.strip() - initial_prompt_tokens = tokenizer.encode(initial_prompt) - all_tokens.extend(initial_prompt_tokens) - + all_tokens = list(initial_prompt_tokens) if use_batch_context: - # previous_batch_context_tokens is now List[List[int]] - # verify we have enough context history lists if i < len(previous_batch_context_tokens): ctx = previous_batch_context_tokens[i] if ctx: - max_prompt_tokens = 223 - current_len = len(all_tokens) - available = max_prompt_tokens - current_len + # 223 is max prompt tokens + available = 223 - len(all_tokens) if available > 0: all_tokens.extend(ctx[-available:]) batch_tokens.append(all_tokens) - # Calculate max length in the batch max_batch_tokens = max([len(t) for t in batch_tokens] + [0]) - # Pad tokens to ensure consistent length across batch - # We use left-padding with EOT to preserve the immediate context before SOT - for i in range(batch_size): - current_tokens = batch_tokens[i] - if len(current_tokens) < max_batch_tokens: - padding_len = max_batch_tokens - len(current_tokens) - # Pad with EOT (End of Transcript) which is usually ignored or treated as break - current_tokens = [tokenizer.eot] * padding_len + current_tokens - - prompt = self.get_prompt( + prompts = [ + self.get_prompt( tokenizer, - current_tokens, + [tokenizer.eot] * (max_batch_tokens - len(t)) + t, without_timestamps=options.without_timestamps, prefix=options.prefix, hotwords=options.hotwords - ) - prompts.append(prompt) + ) for t in batch_tokens + ] encoder_output = self.encode(features) From de5fa652a1866f7d936967fce6c33a0aaca3de53 Mon Sep 17 00:00:00 2001 From: carlos Date: Sat, 14 Feb 2026 20:22:37 +0000 Subject: [PATCH 088/118] [modification] added and condition before streams, existing logic is not chnaged. --- whisperx/asr.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/whisperx/asr.py b/whisperx/asr.py index 0931d88bf..768cddb61 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -317,7 +317,7 @@ def data(audio, segments): batch_size = batch_size or self._batch_size total_segments = len(vad_segments) - if batch_size > 1: + if batch_size > 1 and self.use_batch_context: num_streams = batch_size # Distribute segments into streams # Manual split From 1b6a3b78a6c7a23ac147c59939b89c11ce7358f8 Mon Sep 17 00:00:00 2001 From: carlos Date: Tue, 17 Feb 2026 13:30:03 +0000 Subject: [PATCH 089/118] [feat] First batch wrap around [New File] benchmark testing --- whisperx/asr.py | 18 +++++- whisperx/benchmark.py | 144 ++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 161 insertions(+), 1 deletion(-) create mode 100644 whisperx/benchmark.py diff --git a/whisperx/asr.py b/whisperx/asr.py index 768cddb61..342db0372 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -18,7 +18,6 @@ logger = get_logger(__name__) - def find_numeral_symbol_tokens(tokenizer): numeral_symbol_tokens = [] for i in range(tokenizer.eot): @@ -356,6 +355,23 @@ def data(audio, segments): "end": round(vad_segments[idx]['end'], 3) } ) + + if self.use_batch_context and batch_size > 1: + last_stream_index = (total_segments - 1) % batch_size + final_context = self.previous_batch_context_tokens[last_stream_index] + # Prepare context for the wrap-around re-run + # ONLY Stream 0 (which processes the start of the file) should get the context (which comes from the end of the file). + # All other streams should have EMPTY context for this re-run to avoid self-referencing loops (feeding Segment N to Segment N). + new_rerun_context = [[] for _ in range(batch_size)] + new_rerun_context[0] = final_context + # Temporarily overwrite previous_batch_context_tokens for the re-run + self.previous_batch_context_tokens = new_rerun_context + first_batch_segments = vad_segments[:batch_size] + # Runs the model again just on 'first_batch_segments' + for i, out in enumerate(self.__call__(data(audio, first_batch_segments), batch_size=batch_size, num_workers=num_workers)): + text = out['text'] + # L398: Overwrite the existing text with the new wrap-around text + segments[i]['text'] = text # Sort segments by start time to restore original order segments.sort(key=lambda x: x['start']) diff --git a/whisperx/benchmark.py b/whisperx/benchmark.py new file mode 100644 index 000000000..7e4dbaf07 --- /dev/null +++ b/whisperx/benchmark.py @@ -0,0 +1,144 @@ +import argparse +import os +import time +import torch +import torchaudio +import jiwer +import whisperx +import numpy as np +from typing import Tuple + +def load_tedlium(root: str, download: bool = False, subset: str = "test"): + print(f"Loading TEDLIUM dataset ({subset}) from {root}...") + try: + dataset = torchaudio.datasets.TEDLIUM( + root=root, + release="release3", + subset=subset, + download=download + ) + return dataset + except Exception as e: + print(f"Error loading dataset: {e}") + return None + +def normalize_text(text: str) -> str: + """ + Simple normalization: lower case, remove punctuation. + """ + import string + text = text.lower() + text = text.translate(str.maketrans('', '', string.punctuation)) + return " ".join(text.split()) + +def benchmark(dataset, model_size="large-v2", device="cuda", compute_type="float16", batch_size=4, limit=None): + print(f"Loading WhisperX model: {model_size} on {device} ({compute_type})...") + + try: + model = whisperx.load_model(model_size, device, compute_type=compute_type) + except Exception as e: + print(f"Failed to load model: {e}") + return + + print("Model loaded.") + + total_wer = 0 + total_cer = 0 + total_latency = 0 + total_audio_duration = 0 + count = 0 + + print(f"\nBenchmarking on {limit if limit else len(dataset)} samples...") + + # Clear CUDA cache for accurate VRAM measurement + if torch.cuda.is_available(): + torch.cuda.empty_cache() + torch.cuda.reset_peak_memory_stats() + initial_vram = torch.cuda.memory_allocated() / 1024**3 + print(f"Initial VRAM usage: {initial_vram:.2f} GB") + + for i, item in enumerate(dataset): + if limit and i >= limit: + break + + waveform, sample_rate, transcript, talk_id, speaker_id, identifier = item + + # WhisperX expects audio as a numpy array, float32, mono, 16kHz + # TEDLIUM is likely 16kHz, but let's verify/resample if needed + # waveform is (channels, time) + + if sample_rate != 16000: + resampler = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=16000) + waveform = resampler(waveform) + + audio_np = waveform.squeeze().numpy() + + duration = len(audio_np) / 16000 + total_audio_duration += duration + + # Measure Latency + start_time = time.time() + result = model.transcribe(audio_np, batch_size=batch_size) + end_time = time.time() + + latency = end_time - start_time + total_latency += latency + + # Combine segments for full transcript + hypothesis = " ".join([seg['text'] for seg in result['segments']]) + + # Normalize + ref_norm = normalize_text(transcript) + hyp_norm = normalize_text(hypothesis) + + if not ref_norm.strip(): + # Skip empty references to avoid division by zero in WER + continue + + # Measure WER/CER + wer = jiwer.wer(ref_norm, hyp_norm) + cer = jiwer.cer(ref_norm, hyp_norm) + + total_wer += wer + total_cer += cer + count += 1 + + print(f"Sample {i}: WER={wer:.2f}, CER={cer:.2f}, Latency={latency:.2f}s, Dur={duration:.2f}s, RTF={latency/duration:.2f}") + + if count == 0: + print("No samples processed.") + return + + avg_wer = total_wer / count + avg_cer = total_cer / count + avg_rtf = total_latency / total_audio_duration + + print("\n--- Benchmark Results ---") + print(f"Average WER: {avg_wer:.4f}") + print(f"Average CER: {avg_cer:.4f}") + print(f"Average RTF (Real Time Factor): {avg_rtf:.4f}") + print(f"Total Latency: {total_latency:.2f}s for {total_audio_duration:.2f}s audio") + + if torch.cuda.is_available(): + peak_vram = torch.cuda.max_memory_allocated() / 1024**3 + print(f"Peak VRAM Usage: {peak_vram:.2f} GB") + else: + print("VRAM Usage: N/A (CPU only)") + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Benchmark WhisperX on TEDLIUM") + parser.add_argument("--root", type=str, default="./data", help="Root directory for dataset") + parser.add_argument("--download", action="store_true", help="Download dataset if not found") + parser.add_argument("--limit", type=int, default=None, help="Limit number of samples") + parser.add_argument("--model", type=str, default="large-v2", help="Whisper model size") + parser.add_argument("--device", type=str, default="cuda" if torch.cuda.is_available() else "cpu", help="Device") + parser.add_argument("--batch_size", type=int, default=4, help="Batch size") + + args = parser.parse_args() + + # Create data dir + os.makedirs(args.root, exist_ok=True) + + ds = load_tedlium(args.root, download=args.download) + if ds: + benchmark(ds, model_size=args.model, device=args.device, batch_size=args.batch_size, limit=args.limit) \ No newline at end of file From 0e073d418c7ab0b07fce401c9e0464436920d5ed Mon Sep 17 00:00:00 2001 From: carlito Date: Tue, 17 Feb 2026 13:33:06 +0000 Subject: [PATCH 090/118] Revert "Batch wrap" --- whisperx/__main__.py | 1 - whisperx/asr.py | 139 ++++++--------------------------------- whisperx/benchmark.py | 144 ----------------------------------------- whisperx/transcribe.py | 2 - 4 files changed, 18 insertions(+), 268 deletions(-) delete mode 100644 whisperx/benchmark.py diff --git a/whisperx/__main__.py b/whisperx/__main__.py index 0e523910a..dbb92fc4f 100644 --- a/whisperx/__main__.py +++ b/whisperx/__main__.py @@ -60,7 +60,6 @@ def cli(): parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.") parser.add_argument("--hotwords", type=str, default=None, help="hotwords/hint phrases to the model (e.g. \"WhisperX, PyAnnote, GPU\"); improves recognition of rare/technical terms") parser.add_argument("--condition_on_previous_text", type=str2bool, default=False, help="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") - parser.add_argument("--batch_context", action="store_true", help="use previous batch's transcription as context for the next batch (slower but more coherent across batches)") parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default") parser.add_argument("--temperature_increment_on_fallback", type=optional_float, default=0.2, help="temperature to increase when falling back when the decoding fails to meet either of the thresholds below") diff --git a/whisperx/asr.py b/whisperx/asr.py index 342db0372..7540770f4 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -18,6 +18,7 @@ logger = get_logger(__name__) + def find_numeral_symbol_tokens(tokenizer): numeral_symbol_tokens = [] for i in range(tokenizer.eot): @@ -39,48 +40,28 @@ def generate_segment_batched( tokenizer: Tokenizer, options: TranscriptionOptions, encoder_output=None, - use_batch_context: bool = False, - previous_batch_context_tokens: List[List[int]] = None, ): batch_size = features.shape[0] - if previous_batch_context_tokens is None: - previous_batch_context_tokens = [[] for _ in range(batch_size)] - - initial_prompt_tokens = [] + all_tokens = [] + prompt_reset_since = 0 if options.initial_prompt is not None: initial_prompt = " " + options.initial_prompt.strip() initial_prompt_tokens = tokenizer.encode(initial_prompt) - - batch_tokens = [] - for i in range(batch_size): - all_tokens = list(initial_prompt_tokens) - if use_batch_context: - if i < len(previous_batch_context_tokens): - ctx = previous_batch_context_tokens[i] - if ctx: - # 223 is max prompt tokens - available = 223 - len(all_tokens) - if available > 0: - all_tokens.extend(ctx[-available:]) - batch_tokens.append(all_tokens) - - max_batch_tokens = max([len(t) for t in batch_tokens] + [0]) - - prompts = [ - self.get_prompt( - tokenizer, - [tokenizer.eot] * (max_batch_tokens - len(t)) + t, - without_timestamps=options.without_timestamps, - prefix=options.prefix, - hotwords=options.hotwords - ) for t in batch_tokens - ] + all_tokens.extend(initial_prompt_tokens) + previous_tokens = all_tokens[prompt_reset_since:] + prompt = self.get_prompt( + tokenizer, + previous_tokens, + without_timestamps=options.without_timestamps, + prefix=options.prefix, + hotwords=options.hotwords + ) encoder_output = self.encode(features) result = self.model.generate( encoder_output, - prompts, + [prompt] * batch_size, beam_size=options.beam_size, patience=options.patience, length_penalty=options.length_penalty, @@ -101,9 +82,9 @@ def decode_batch(tokens: List[List[int]]) -> List[str]: return tokenizer.tokenizer.decode_batch(res) text = decode_batch(tokens_batch) + return text - def encode(self, features: np.ndarray) -> ctranslate2.StorageView: # When the model is running on multiple GPUs, the encoder output should be moved # to the CPU since we don't know which GPU will handle the next job. @@ -134,7 +115,6 @@ def __init__( framework="pt", language: Optional[str] = None, suppress_numerals: bool = False, - use_batch_context: bool = False, **kwargs, ): self.model = model @@ -142,7 +122,6 @@ def __init__( self.options = options self.preset_language = language self.suppress_numerals = suppress_numerals - self.use_batch_context = use_batch_context self._batch_size = kwargs.pop("batch_size", None) self._num_workers = 1 self._preprocess_params, self._forward_params, self._postprocess_params = self._sanitize_parameters(**kwargs) @@ -163,8 +142,6 @@ def __init__( super(Pipeline, self).__init__() self.vad_model = vad self._vad_params = vad_params - self.previous_batch_context_tokens = [] - def _sanitize_parameters(self, **kwargs): preprocess_kwargs = {} @@ -183,35 +160,7 @@ def preprocess(self, audio): return {'inputs': features} def _forward(self, model_inputs): - current_batch_size = model_inputs['inputs'].shape[0] - # Ideally, batch[i] corresponds to stream[i]. - # This holds if batch_size == number of streams. - valid_contexts = self.previous_batch_context_tokens[:current_batch_size] - - outputs = self.model.generate_segment_batched( - model_inputs['inputs'], - self.tokenizer, - self.options, - use_batch_context=self.use_batch_context, - previous_batch_context_tokens=valid_contexts, - ) - if self.use_batch_context: - initial_prompt_length = 0 - if self.options.initial_prompt is not None: - initial_prompt = " " + self.options.initial_prompt.strip() - initial_prompt_length = len(self.tokenizer.encode(initial_prompt)) - - # Use 220 instead of 224 to be safe - max_context_window = max(0, 220 - initial_prompt_length) - - for i, text in enumerate(outputs): - if i < len(self.previous_batch_context_tokens): - # Filter out special tokens (timestamps, SOT, EOT, etc.) - # We only want the text content for context. - tokens = [t for t in self.tokenizer.encode(text) if t < self.tokenizer.eot] - self.previous_batch_context_tokens[i].extend(tokens) - self.previous_batch_context_tokens[i] = self.previous_batch_context_tokens[i][-max_context_window:] - + outputs = self.model.generate_segment_batched(model_inputs['inputs'], self.tokenizer, self.options) return {'text': outputs} def postprocess(self, model_outputs): @@ -252,14 +201,6 @@ def transcribe( ) -> TranscriptionResult: if isinstance(audio, str): audio = load_audio(audio) - - batch_size = batch_size or self._batch_size - # Initialize context for each stream. - # We have 'batch_size' concurrent streams. - if batch_size is None or batch_size < 1: - batch_size = 1 - - self.previous_batch_context_tokens = [[] for _ in range(batch_size)] def data(audio, segments): for seg in segments: @@ -311,33 +252,10 @@ def data(audio, segments): new_suppressed_tokens = numeral_symbol_tokens + self.options.suppress_tokens new_suppressed_tokens = list(set(new_suppressed_tokens)) self.options = replace(self.options, suppress_tokens=new_suppressed_tokens) - + segments: List[SingleSegment] = [] batch_size = batch_size or self._batch_size total_segments = len(vad_segments) - - if batch_size > 1 and self.use_batch_context: - num_streams = batch_size - # Distribute segments into streams - # Manual split - k, m = divmod(len(vad_segments), num_streams) - # lengths of each part: first m parts have k+1, rest have k - stream_segments = [] - start_idx = 0 - for i in range(num_streams): - part_len = k + 1 if i < m else k - stream_segments.append(vad_segments[start_idx : start_idx + part_len]) - start_idx += part_len - # Interleave - # We need to pick [s0[0], s1[0], s2[0]... s0[1], s1[1]...] - interleaved_segments = [] - max_len = max(len(s) for s in stream_segments) - for i in range(max_len): - for stream in stream_segments: - if i < len(stream): - interleaved_segments.append(stream[i]) - vad_segments = interleaved_segments - for idx, out in enumerate(self.__call__(data(audio, vad_segments), batch_size=batch_size, num_workers=num_workers)): if print_progress: base_progress = ((idx + 1) / total_segments) * 100 @@ -356,25 +274,6 @@ def data(audio, segments): } ) - if self.use_batch_context and batch_size > 1: - last_stream_index = (total_segments - 1) % batch_size - final_context = self.previous_batch_context_tokens[last_stream_index] - # Prepare context for the wrap-around re-run - # ONLY Stream 0 (which processes the start of the file) should get the context (which comes from the end of the file). - # All other streams should have EMPTY context for this re-run to avoid self-referencing loops (feeding Segment N to Segment N). - new_rerun_context = [[] for _ in range(batch_size)] - new_rerun_context[0] = final_context - # Temporarily overwrite previous_batch_context_tokens for the re-run - self.previous_batch_context_tokens = new_rerun_context - first_batch_segments = vad_segments[:batch_size] - # Runs the model again just on 'first_batch_segments' - for i, out in enumerate(self.__call__(data(audio, first_batch_segments), batch_size=batch_size, num_workers=num_workers)): - text = out['text'] - # L398: Overwrite the existing text with the new wrap-around text - segments[i]['text'] = text - # Sort segments by start time to restore original order - segments.sort(key=lambda x: x['start']) - # revert the tokenizer if multilingual inference is enabled if self.preset_language is None: self.tokenizer = None @@ -390,8 +289,8 @@ def detect_language(self, audio: np.ndarray) -> str: logger.warning("Audio is shorter than 30s, language detection may be inaccurate") model_n_mels = self.model.feat_kwargs.get("feature_size") segment = log_mel_spectrogram(audio[: N_SAMPLES], - n_mels=model_n_mels if model_n_mels is not None else 80, - padding=0 if audio.shape[0] >= N_SAMPLES else N_SAMPLES - audio.shape[0]) + n_mels=model_n_mels if model_n_mels is not None else 80, + padding=0 if audio.shape[0] >= N_SAMPLES else N_SAMPLES - audio.shape[0]) encoder_output = self.model.encode(segment) results = self.model.model.detect_language(encoder_output) language_token, language_probability = results[0][0] @@ -416,7 +315,6 @@ def load_model( local_files_only=False, threads=4, use_auth_token: Optional[Union[str, bool]] = None, - use_batch_context: bool = False, ) -> FasterWhisperPipeline: """Load a Whisper model for inference. Args: @@ -523,5 +421,4 @@ def load_model( language=language, suppress_numerals=suppress_numerals, vad_params=default_vad_options, - use_batch_context=use_batch_context, ) diff --git a/whisperx/benchmark.py b/whisperx/benchmark.py deleted file mode 100644 index 7e4dbaf07..000000000 --- a/whisperx/benchmark.py +++ /dev/null @@ -1,144 +0,0 @@ -import argparse -import os -import time -import torch -import torchaudio -import jiwer -import whisperx -import numpy as np -from typing import Tuple - -def load_tedlium(root: str, download: bool = False, subset: str = "test"): - print(f"Loading TEDLIUM dataset ({subset}) from {root}...") - try: - dataset = torchaudio.datasets.TEDLIUM( - root=root, - release="release3", - subset=subset, - download=download - ) - return dataset - except Exception as e: - print(f"Error loading dataset: {e}") - return None - -def normalize_text(text: str) -> str: - """ - Simple normalization: lower case, remove punctuation. - """ - import string - text = text.lower() - text = text.translate(str.maketrans('', '', string.punctuation)) - return " ".join(text.split()) - -def benchmark(dataset, model_size="large-v2", device="cuda", compute_type="float16", batch_size=4, limit=None): - print(f"Loading WhisperX model: {model_size} on {device} ({compute_type})...") - - try: - model = whisperx.load_model(model_size, device, compute_type=compute_type) - except Exception as e: - print(f"Failed to load model: {e}") - return - - print("Model loaded.") - - total_wer = 0 - total_cer = 0 - total_latency = 0 - total_audio_duration = 0 - count = 0 - - print(f"\nBenchmarking on {limit if limit else len(dataset)} samples...") - - # Clear CUDA cache for accurate VRAM measurement - if torch.cuda.is_available(): - torch.cuda.empty_cache() - torch.cuda.reset_peak_memory_stats() - initial_vram = torch.cuda.memory_allocated() / 1024**3 - print(f"Initial VRAM usage: {initial_vram:.2f} GB") - - for i, item in enumerate(dataset): - if limit and i >= limit: - break - - waveform, sample_rate, transcript, talk_id, speaker_id, identifier = item - - # WhisperX expects audio as a numpy array, float32, mono, 16kHz - # TEDLIUM is likely 16kHz, but let's verify/resample if needed - # waveform is (channels, time) - - if sample_rate != 16000: - resampler = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=16000) - waveform = resampler(waveform) - - audio_np = waveform.squeeze().numpy() - - duration = len(audio_np) / 16000 - total_audio_duration += duration - - # Measure Latency - start_time = time.time() - result = model.transcribe(audio_np, batch_size=batch_size) - end_time = time.time() - - latency = end_time - start_time - total_latency += latency - - # Combine segments for full transcript - hypothesis = " ".join([seg['text'] for seg in result['segments']]) - - # Normalize - ref_norm = normalize_text(transcript) - hyp_norm = normalize_text(hypothesis) - - if not ref_norm.strip(): - # Skip empty references to avoid division by zero in WER - continue - - # Measure WER/CER - wer = jiwer.wer(ref_norm, hyp_norm) - cer = jiwer.cer(ref_norm, hyp_norm) - - total_wer += wer - total_cer += cer - count += 1 - - print(f"Sample {i}: WER={wer:.2f}, CER={cer:.2f}, Latency={latency:.2f}s, Dur={duration:.2f}s, RTF={latency/duration:.2f}") - - if count == 0: - print("No samples processed.") - return - - avg_wer = total_wer / count - avg_cer = total_cer / count - avg_rtf = total_latency / total_audio_duration - - print("\n--- Benchmark Results ---") - print(f"Average WER: {avg_wer:.4f}") - print(f"Average CER: {avg_cer:.4f}") - print(f"Average RTF (Real Time Factor): {avg_rtf:.4f}") - print(f"Total Latency: {total_latency:.2f}s for {total_audio_duration:.2f}s audio") - - if torch.cuda.is_available(): - peak_vram = torch.cuda.max_memory_allocated() / 1024**3 - print(f"Peak VRAM Usage: {peak_vram:.2f} GB") - else: - print("VRAM Usage: N/A (CPU only)") - -if __name__ == "__main__": - parser = argparse.ArgumentParser(description="Benchmark WhisperX on TEDLIUM") - parser.add_argument("--root", type=str, default="./data", help="Root directory for dataset") - parser.add_argument("--download", action="store_true", help="Download dataset if not found") - parser.add_argument("--limit", type=int, default=None, help="Limit number of samples") - parser.add_argument("--model", type=str, default="large-v2", help="Whisper model size") - parser.add_argument("--device", type=str, default="cuda" if torch.cuda.is_available() else "cpu", help="Device") - parser.add_argument("--batch_size", type=int, default=4, help="Batch size") - - args = parser.parse_args() - - # Create data dir - os.makedirs(args.root, exist_ok=True) - - ds = load_tedlium(args.root, download=args.download) - if ds: - benchmark(ds, model_size=args.model, device=args.device, batch_size=args.batch_size, limit=args.limit) \ No newline at end of file diff --git a/whisperx/transcribe.py b/whisperx/transcribe.py index 92a634dd1..7c8be6794 100644 --- a/whisperx/transcribe.py +++ b/whisperx/transcribe.py @@ -63,7 +63,6 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): diarize_model_name: str = args.pop("diarize_model") print_progress: bool = args.pop("print_progress") return_speaker_embeddings: bool = args.pop("speaker_embeddings") - batch_context: bool = args.pop("batch_context", False) if return_speaker_embeddings and not diarize: warnings.warn("--speaker_embeddings has no effect without --diarize") @@ -143,7 +142,6 @@ def transcribe_task(args: dict, parser: argparse.ArgumentParser): local_files_only=model_cache_only, threads=faster_whisper_threads, use_auth_token=hf_token, - use_batch_context=batch_context, ) for audio_path in args.pop("audio"): From d8a078eed46b139f90d7f33b472119e9be9ff969 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Sat, 14 Feb 2026 09:58:45 +0100 Subject: [PATCH 091/118] feat: expose avg_logprob per segment from ctranslate2 beam search Pass through the average log probability (transcription confidence score) from ctranslate2 to the final segment output. The field is NotRequired so existing code constructing segments without it remains valid. Co-Authored-By: Claude Opus 4.6 --- whisperx/alignment.py | 13 +++++++++++-- whisperx/asr.py | 16 +++++++++++++--- whisperx/schema.py | 7 +++++++ 3 files changed, 31 insertions(+), 5 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index ce92d7a4f..9e5b63a2d 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -216,6 +216,7 @@ def align( t1 = segment["start"] t2 = segment["end"] text = segment["text"] + avg_logprob = segment.get("avg_logprob") aligned_seg: SingleAlignedSegment = { "start": t1, @@ -225,6 +226,9 @@ def align( "chars": None, } + if avg_logprob is not None: + aligned_seg["avg_logprob"] = avg_logprob + if return_char_alignments: aligned_seg["chars"] = [] @@ -353,12 +357,15 @@ def align( sentence_words.append(word_segment) - aligned_subsegments.append({ + subsegment = { "text": sentence_text, "start": sentence_start, "end": sentence_end, "words": sentence_words, - }) + } + if avg_logprob is not None: + subsegment["avg_logprob"] = avg_logprob + aligned_subsegments.append(subsegment) if return_char_alignments: curr_chars = curr_chars[["char", "start", "end", "score"]] @@ -376,6 +383,8 @@ def align( agg_dict["text"] = "".join if return_char_alignments: agg_dict["chars"] = "sum" + if avg_logprob is not None: + agg_dict["avg_logprob"] = "first" aligned_subsegments= aligned_subsegments.groupby(["start", "end"], as_index=False).agg(agg_dict) aligned_subsegments = aligned_subsegments.to_dict('records') aligned_segments += aligned_subsegments diff --git a/whisperx/asr.py b/whisperx/asr.py index 7540770f4..ea29e56f5 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -70,10 +70,17 @@ def generate_segment_batched( suppress_tokens=options.suppress_tokens, no_repeat_ngram_size=options.no_repeat_ngram_size, repetition_penalty=options.repetition_penalty, + return_scores=True, ) tokens_batch = [x.sequences_ids[0] for x in result] + avg_logprobs = [] + for res in result: + seq_len = len(res.sequences_ids[0]) + cum_logprob = res.scores[0] * (seq_len ** options.length_penalty) + avg_logprobs.append(cum_logprob / (seq_len + 1)) + def decode_batch(tokens: List[List[int]]) -> List[str]: res = [] for tk in tokens: @@ -83,7 +90,7 @@ def decode_batch(tokens: List[List[int]]) -> List[str]: text = decode_batch(tokens_batch) - return text + return {'text': text, 'avg_logprob': avg_logprobs} def encode(self, features: np.ndarray) -> ctranslate2.StorageView: # When the model is running on multiple GPUs, the encoder output should be moved @@ -161,7 +168,7 @@ def preprocess(self, audio): def _forward(self, model_inputs): outputs = self.model.generate_segment_batched(model_inputs['inputs'], self.tokenizer, self.options) - return {'text': outputs} + return outputs def postprocess(self, model_outputs): return model_outputs @@ -262,15 +269,18 @@ def data(audio, segments): percent_complete = base_progress / 2 if combined_progress else base_progress print(f"Progress: {percent_complete:.2f}%...") text = out['text'] + avg_logprob = out['avg_logprob'] if batch_size in [0, 1, None]: text = text[0] + avg_logprob = avg_logprob[0] if verbose: print(f"Transcript: [{round(vad_segments[idx]['start'], 3)} --> {round(vad_segments[idx]['end'], 3)}] {text}") segments.append( { "text": text, "start": round(vad_segments[idx]['start'], 3), - "end": round(vad_segments[idx]['end'], 3) + "end": round(vad_segments[idx]['end'], 3), + "avg_logprob": avg_logprob, } ) diff --git a/whisperx/schema.py b/whisperx/schema.py index 70b10a7b0..83d9147fd 100644 --- a/whisperx/schema.py +++ b/whisperx/schema.py @@ -1,5 +1,10 @@ from typing import TypedDict, Optional, List, Tuple +try: + from typing import NotRequired +except ImportError: + from typing_extensions import NotRequired + class SingleWordSegment(TypedDict): """ @@ -28,6 +33,7 @@ class SingleSegment(TypedDict): start: float end: float text: str + avg_logprob: NotRequired[float] class SegmentData(TypedDict): @@ -49,6 +55,7 @@ class SingleAlignedSegment(TypedDict): start: float end: float text: str + avg_logprob: NotRequired[float] words: List[SingleWordSegment] chars: Optional[List[SingleCharSegment]] From 064f7379981d744ae14ceedf92c3d1e956db18a9 Mon Sep 17 00:00:00 2001 From: Max Bain Date: Sun, 22 Feb 2026 16:12:55 +0000 Subject: [PATCH 092/118] fix: default compute_type to float32 on CPU to avoid float16 ValueError --- whisperx/__main__.py | 4 ++-- whisperx/asr.py | 7 ++++++- 2 files changed, 8 insertions(+), 3 deletions(-) diff --git a/whisperx/__main__.py b/whisperx/__main__.py index dbb92fc4f..cd2811259 100644 --- a/whisperx/__main__.py +++ b/whisperx/__main__.py @@ -16,10 +16,10 @@ def cli(): parser.add_argument("--model", default="small", help="name of the Whisper model to use") parser.add_argument("--model_cache_only", type=str2bool, default=False, help="If True, will not attempt to download models, instead using cached models from --model_dir") parser.add_argument("--model_dir", type=str, default=None, help="the path to save model files; uses ~/.cache/whisper by default") - parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu", help="device to use for PyTorch inference") + parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu", help="device type to use for PyTorch inference (e.g. cpu, cuda)") parser.add_argument("--device_index", default=0, type=int, help="device index to use for FasterWhisper inference") parser.add_argument("--batch_size", default=8, type=int, help="the preferred batch size for inference") - parser.add_argument("--compute_type", default="float16", type=str, choices=["float16", "float32", "int8"], help="compute type for computation") + parser.add_argument("--compute_type", default="default", type=str, choices=["default", "float16", "float32", "int8"], help="compute type for computation; 'default' uses float16 on GPU, float32 on CPU") parser.add_argument("--output_dir", "-o", type=str, default=".", help="directory to save the outputs") parser.add_argument("--output_format", "-f", type=str, default="all", choices=["all", "srt", "vtt", "txt", "tsv", "json", "aud"], help="format of the output file; if not specified, all available formats will be produced") diff --git a/whisperx/asr.py b/whisperx/asr.py index ea29e56f5..a5c80711d 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -313,7 +313,7 @@ def load_model( whisper_arch: str, device: str, device_index=0, - compute_type="float16", + compute_type="default", asr_options: Optional[dict] = None, language: Optional[str] = None, vad_model: Optional[Vad]= None, @@ -331,6 +331,7 @@ def load_model( whisper_arch - The name of the Whisper model to load. device - The device to load the model on. compute_type - The compute type to use for the model. + Use "default" to automatically select based on device (float16 for GPU, float32 for CPU). vad_model - The vad model to manually assign. vad_method - The vad method to use. vad_model has a higher priority if it is not None. options - A dictionary of options to use for the model. @@ -343,6 +344,10 @@ def load_model( A Whisper pipeline. """ + if compute_type == "default": + compute_type = "float16" if device == "cuda" else "float32" + logger.info(f"Compute type not specified, defaulting to {compute_type} for device {device}") + if whisper_arch.endswith(".en"): language = "en" From f2609a64b6f8a2f325f991494c24a408160d0c75 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Tue, 10 Mar 2026 09:01:22 +0100 Subject: [PATCH 093/118] fix: revert #986 wildcard alignment that broke word-level timestamps PR #986 ("support timestamps for numbers") introduced three changes that together broke CTC forced alignment: 1. Unknown chars (numbers, punctuation) were replaced with '*' wildcards mapped to token -1. get_wildcard_emission() scored these using torch.max() over all non-blank emissions, so wildcards greedily matched any speech-like signal in the segment window. 2. get_trellis() was rewritten with a different shape (num_frame, num_tokens) and incompatible initialization, discarding the original SoS-offset design from the PyTorch forced alignment tutorial. 3. backtrack() was replaced with backtrack_beam(), which always starts backtracking from the last frame of the segment window. The original backtrack() used torch.argmax() on the last token column to determine the starting frame. With padded segment boundaries (silence before/after speech), the new implementation spread all tokens across the full window, placing the first word at the start of the silence instead of the speech. This commit restores the original PyTorch tutorial implementation: - Unknown chars are skipped; words with only unknown chars become unalignable and get no timestamps (handled by interpolate_nans) - get_trellis: restored (num_frame+1, num_tokens+1) shape with SoS offset - backtrack: restored torch.argmax-based starting frame - Removed backtrack_beam, get_wildcard_emission, BeamState, Path Verified: v3.3.0 (pre-#986) produced correct timestamps with padded segment boundaries; this fix reproduces that behavior. Fixes #1220 Co-Authored-By: Claude Sonnet 4.6 --- whisperx/alignment.py | 228 +++++++++--------------------------------- 1 file changed, 45 insertions(+), 183 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 9e5b63a2d..74f9d3508 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -2,8 +2,6 @@ Forced Alignment with Whisper C. Max Bain """ -import math - from dataclasses import dataclass from typing import Iterable, Optional, Union, List @@ -86,8 +84,8 @@ def load_align_model(language_code: str, device: str, model_name: Optional[str] model_name = DEFAULT_ALIGN_MODELS_HF[language_code] else: logger.error(f"No default alignment model for language: {language_code}. " - f"Please find a wav2vec2.0 model finetuned on this language at https://huggingface.co/models, " - f"then pass the model name via --align_model [MODEL_NAME]") + f"Please find a wav2vec2.0 model finetuned on this language at https://huggingface.co/models, " + f"then pass the model name via --align_model [MODEL_NAME]") raise ValueError(f"No default align-model for language: {language_code}") if model_name in torchaudio.pipelines.__all__: @@ -178,19 +176,11 @@ def align( elif char_ in model_dictionary.keys(): clean_char.append(char_) clean_cdx.append(cdx) - else: - # add placeholder - clean_char.append('*') - clean_cdx.append(cdx) clean_wdx = [] for wdx, wrd in enumerate(per_word): if any([c in model_dictionary.keys() for c in wrd.lower()]): clean_wdx.append(wdx) - else: - # index for placeholder - clean_wdx.append(wdx) - # Use language-specific Punkt model if available otherwise we fallback to English. punkt_lang = PUNKT_LANGUAGES.get(model_lang, 'english') @@ -244,7 +234,7 @@ def align( continue text_clean = "".join(segment_data[sdx]["clean_char"]) - tokens = [model_dictionary.get(c, -1) for c in text_clean] + tokens = [model_dictionary[c] for c in text_clean] f1 = int(t1 * SAMPLE_RATE) f2 = int(t2 * SAMPLE_RATE) @@ -277,8 +267,7 @@ def align( blank_id = code trellis = get_trellis(emission, tokens, blank_id) - # path = backtrack(trellis, emission, tokens, blank_id) - path = backtrack_beam(trellis, emission, tokens, blank_id, beam_width=2) + path = backtrack(trellis, emission, tokens, blank_id) if path is None: logger.warning(f'Failed to align segment ("{segment["text"]}"): backtrack failed, resorting to original') @@ -405,55 +394,25 @@ def get_trellis(emission, tokens, blank_id=0): num_frame = emission.size(0) num_tokens = len(tokens) - trellis = torch.zeros((num_frame, num_tokens)) - trellis[1:, 0] = torch.cumsum(emission[1:, blank_id], 0) - trellis[0, 1:] = -float("inf") - trellis[-num_tokens + 1:, 0] = float("inf") + # Trellis has extra dimensions for both time axis and tokens. + # The extra dim for tokens represents (start-of-sentence) + # The extra dim for time axis is for simplification of the code. + trellis = torch.empty((num_frame + 1, num_tokens + 1)) + trellis[0, 0] = 0 + trellis[1:, 0] = torch.cumsum(emission[:, 0], 0) + trellis[0, -num_tokens:] = -float("inf") + trellis[-num_tokens:, 0] = float("inf") - for t in range(num_frame - 1): + for t in range(num_frame): trellis[t + 1, 1:] = torch.maximum( # Score for staying at the same token trellis[t, 1:] + emission[t, blank_id], # Score for changing to the next token - # trellis[t, :-1] + emission[t, tokens[1:]], - trellis[t, :-1] + get_wildcard_emission(emission[t], tokens[1:], blank_id), + trellis[t, :-1] + emission[t, tokens], ) return trellis -def get_wildcard_emission(frame_emission, tokens, blank_id): - """Processing token emission scores containing wildcards (vectorized version) - - Args: - frame_emission: Emission probability vector for the current frame - tokens: List of token indices - blank_id: ID of the blank token - - Returns: - tensor: Maximum probability score for each token position - """ - assert 0 <= blank_id < len(frame_emission) - - # Convert tokens to a tensor if they are not already - tokens = torch.tensor(tokens) if not isinstance(tokens, torch.Tensor) else tokens - - # Create a mask to identify wildcard positions - wildcard_mask = (tokens == -1) - - # Get scores for non-wildcard positions - regular_scores = frame_emission[tokens.clamp(min=0).long()] # clamp to avoid -1 index - - # Create a mask and compute the maximum value without modifying frame_emission - max_valid_score = frame_emission.clone() # Create a copy - max_valid_score[blank_id] = float('-inf') # Modify the copy to exclude the blank token - max_valid_score = max_valid_score.max() - - # Use where operation to combine results - result = torch.where(wildcard_mask, max_valid_score, regular_scores) - - return result - - @dataclass class Point: token_index: int @@ -462,138 +421,41 @@ class Point: def backtrack(trellis, emission, tokens, blank_id=0): - t, j = trellis.size(0) - 1, trellis.size(1) - 1 - - path = [Point(j, t, emission[t, blank_id].exp().item())] - while j > 0: - # Should not happen but just in case - assert t > 0 - + # Note: + # j and t are indices for trellis, which has extra dimensions + # for time and tokens at the beginning. + # When referring to time frame index `T` in trellis, + # the corresponding index in emission is `T-1`. + # Similarly, when referring to token index `J` in trellis, + # the corresponding index in transcript is `J-1`. + j = trellis.size(1) - 1 + t_start = torch.argmax(trellis[:, j]).item() + + path = [] + for t in range(t_start, 0, -1): # 1. Figure out if the current position was stay or change - # Frame-wise score of stay vs change - p_stay = emission[t - 1, blank_id] - # p_change = emission[t - 1, tokens[j]] - p_change = get_wildcard_emission(emission[t - 1], [tokens[j]], blank_id)[0] - - # Context-aware score for stay vs change - stayed = trellis[t - 1, j] + p_stay - changed = trellis[t - 1, j - 1] + p_change - - # Update position - t -= 1 + # Note (again): + # `emission[J-1]` is the emission at time frame `J` of trellis dimension. + # Score for token staying the same from time frame J-1 to T. + stayed = trellis[t - 1, j] + emission[t - 1, blank_id] + # Score for token changing from C-1 at T-1 to J at T. + changed = trellis[t - 1, j - 1] + emission[t - 1, tokens[j - 1]] + + # 2. Store the path with frame-wise probability. + prob = emission[t - 1, tokens[j - 1] if changed > stayed else 0].exp().item() + # Return token index and time index in non-trellis coordinate. + path.append(Point(j - 1, t - 1, prob)) + + # 3. Update the token if changed > stayed: j -= 1 - - # Store the path with frame-wise probability. - prob = (p_change if changed > stayed else p_stay).exp().item() - path.append(Point(j, t, prob)) - - # Now j == 0, which means, it reached the SoS. - # Fill up the rest for the sake of visualization - while t > 0: - prob = emission[t - 1, blank_id].exp().item() - path.append(Point(j, t - 1, prob)) - t -= 1 - - return path[::-1] - - - -@dataclass -class Path: - points: List[Point] - score: float - - -@dataclass -class BeamState: - """State in beam search.""" - token_index: int # Current token position - time_index: int # Current time step - score: float # Cumulative score - path: List[Point] # Path history - - -def backtrack_beam(trellis, emission, tokens, blank_id=0, beam_width=5): - """Standard CTC beam search backtracking implementation. - - Args: - trellis (torch.Tensor): The trellis (or lattice) of shape (T, N), where T is the number of time steps - and N is the number of tokens (including the blank token). - emission (torch.Tensor): The emission probabilities of shape (T, N). - tokens (List[int]): List of token indices (excluding the blank token). - blank_id (int, optional): The ID of the blank token. Defaults to 0. - beam_width (int, optional): The number of top paths to keep during beam search. Defaults to 5. - - Returns: - List[Point]: the best path - """ - T, J = trellis.size(0) - 1, trellis.size(1) - 1 - - init_state = BeamState( - token_index=J, - time_index=T, - score=trellis[T, J], - path=[Point(J, T, emission[T, blank_id].exp().item())] - ) - - beams = [init_state] - - while beams and beams[0].token_index > 0: - next_beams = [] - - for beam in beams: - t, j = beam.time_index, beam.token_index - - if t <= 0: - continue - - p_stay = emission[t - 1, blank_id] - p_change = get_wildcard_emission(emission[t - 1], [tokens[j]], blank_id)[0] - - stay_score = trellis[t - 1, j] - change_score = trellis[t - 1, j - 1] if j > 0 else float('-inf') - - # Stay - if not math.isinf(stay_score): - new_path = beam.path.copy() - new_path.append(Point(j, t - 1, p_stay.exp().item())) - next_beams.append(BeamState( - token_index=j, - time_index=t - 1, - score=stay_score, - path=new_path - )) - - # Change - if j > 0 and not math.isinf(change_score): - new_path = beam.path.copy() - new_path.append(Point(j - 1, t - 1, p_change.exp().item())) - next_beams.append(BeamState( - token_index=j - 1, - time_index=t - 1, - score=change_score, - path=new_path - )) - - # sort by score - beams = sorted(next_beams, key=lambda x: x.score, reverse=True)[:beam_width] - - if not beams: - break - - if not beams: + if j == 0: + break + else: + # failed return None - best_beam = beams[0] - t = best_beam.time_index - j = best_beam.token_index - while t > 0: - prob = emission[t - 1, blank_id].exp().item() - best_beam.path.append(Point(j, t - 1, prob)) - t -= 1 - - return best_beam.path[::-1] + return path[::-1] # Merge the labels @@ -643,4 +505,4 @@ def merge_words(segments, separator="|"): i2 = i1 else: i2 += 1 - return words + return words \ No newline at end of file From 636f2988f82bcb3ad2450c4f85865a8d435a0b7c Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Tue, 10 Mar 2026 09:04:45 +0100 Subject: [PATCH 094/118] fix: use blank_id parameter instead of hardcoded 0 in trellis and backtrack The original code accepted blank_id as a parameter but used hardcoded 0 in two places, breaking alignment for HuggingFace models where the blank token is [pad] (not index 0). Co-Authored-By: Claude Sonnet 4.6 --- whisperx/alignment.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 74f9d3508..f3095ba8c 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -399,7 +399,7 @@ def get_trellis(emission, tokens, blank_id=0): # The extra dim for time axis is for simplification of the code. trellis = torch.empty((num_frame + 1, num_tokens + 1)) trellis[0, 0] = 0 - trellis[1:, 0] = torch.cumsum(emission[:, 0], 0) + trellis[1:, 0] = torch.cumsum(emission[:, blank_id], 0) trellis[0, -num_tokens:] = -float("inf") trellis[-num_tokens:, 0] = float("inf") @@ -442,7 +442,7 @@ def backtrack(trellis, emission, tokens, blank_id=0): changed = trellis[t - 1, j - 1] + emission[t - 1, tokens[j - 1]] # 2. Store the path with frame-wise probability. - prob = emission[t - 1, tokens[j - 1] if changed > stayed else 0].exp().item() + prob = emission[t - 1, tokens[j - 1] if changed > stayed else blank_id].exp().item() # Return token index and time index in non-trellis coordinate. path.append(Point(j - 1, t - 1, prob)) From 6d3edb1c0b33d9b1bef3c7ab889b4c56162b4ff6 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Tue, 10 Mar 2026 15:30:43 +0100 Subject: [PATCH 095/118] chore: bump version --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 15d392da6..94626d605 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.8.1" +version = "3.8.2" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.10, <3.14" diff --git a/uv.lock b/uv.lock index 421c50445..22d61222e 100644 --- a/uv.lock +++ b/uv.lock @@ -3026,7 +3026,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.8.1" +version = "3.8.2" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, From d00ec69ac212d06de922e09bff56bcaca508ac76 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Wed, 11 Mar 2026 10:12:54 +0100 Subject: [PATCH 096/118] feat: add progress_callback to transcribe, align, and diarize Add optional `progress_callback: Callable[[float], None]` parameter to the three public API functions for real-time progress tracking. Each callback receives 0-100% for its own stage independently. Diarization wraps the callback into pyannote's internal hook protocol, keeping pyannote internals fully encapsulated. Co-Authored-By: Claude Opus 4.6 --- whisperx/alignment.py | 5 +++++ whisperx/asr.py | 5 ++++- whisperx/diarize.py | 26 +++++++++++++++++++++++++- whisperx/schema.py | 4 +++- 4 files changed, 37 insertions(+), 3 deletions(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index f3095ba8c..0786d0eb9 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -19,6 +19,7 @@ SingleAlignedSegment, SingleWordSegment, SegmentData, + ProgressCallback, ) import nltk from nltk.data import load as nltk_load @@ -122,6 +123,7 @@ def align( return_char_alignments: bool = False, print_progress: bool = False, combined_progress: bool = False, + progress_callback: ProgressCallback = None, ) -> AlignedTranscriptionResult: """ Align phoneme recognition predictions to known transcription. @@ -376,6 +378,9 @@ def align( agg_dict["avg_logprob"] = "first" aligned_subsegments= aligned_subsegments.groupby(["start", "end"], as_index=False).agg(agg_dict) aligned_subsegments = aligned_subsegments.to_dict('records') + if progress_callback is not None: + progress_callback(((sdx + 1) / total_segments) * 100) + aligned_segments += aligned_subsegments # create word_segments list diff --git a/whisperx/asr.py b/whisperx/asr.py index a5c80711d..401148647 100644 --- a/whisperx/asr.py +++ b/whisperx/asr.py @@ -12,7 +12,7 @@ from transformers.pipelines.pt_utils import PipelineIterator from whisperx.audio import N_SAMPLES, SAMPLE_RATE, load_audio, log_mel_spectrogram -from whisperx.schema import SingleSegment, TranscriptionResult +from whisperx.schema import SingleSegment, TranscriptionResult, ProgressCallback from whisperx.vads import Vad, Silero, Pyannote from whisperx.log_utils import get_logger @@ -205,6 +205,7 @@ def transcribe( print_progress=False, combined_progress=False, verbose=False, + progress_callback: ProgressCallback = None, ) -> TranscriptionResult: if isinstance(audio, str): audio = load_audio(audio) @@ -268,6 +269,8 @@ def data(audio, segments): base_progress = ((idx + 1) / total_segments) * 100 percent_complete = base_progress / 2 if combined_progress else base_progress print(f"Progress: {percent_complete:.2f}%...") + if progress_callback is not None: + progress_callback(((idx + 1) / total_segments) * 100) text = out['text'] avg_logprob = out['avg_logprob'] if batch_size in [0, 1, None]: diff --git a/whisperx/diarize.py b/whisperx/diarize.py index 041fb129d..b767416e6 100644 --- a/whisperx/diarize.py +++ b/whisperx/diarize.py @@ -5,7 +5,7 @@ import torch from whisperx.audio import load_audio, SAMPLE_RATE -from whisperx.schema import TranscriptionResult, AlignedTranscriptionResult +from whisperx.schema import TranscriptionResult, AlignedTranscriptionResult, ProgressCallback from whisperx.log_utils import get_logger logger = get_logger(__name__) @@ -109,6 +109,7 @@ def __call__( min_speakers: Optional[int] = None, max_speakers: Optional[int] = None, return_embeddings: bool = False, + progress_callback: ProgressCallback = None, ) -> Union[tuple[pd.DataFrame, Optional[dict[str, list[float]]]], pd.DataFrame]: """ Perform speaker diarization on audio. @@ -119,6 +120,7 @@ def __call__( min_speakers: Minimum number of speakers to detect max_speakers: Maximum number of speakers to detect return_embeddings: Whether to return speaker embeddings + progress_callback: Optional callable receiving a float (0-100) with progress percentage Returns: If return_embeddings is True: @@ -133,13 +135,35 @@ def __call__( 'sample_rate': SAMPLE_RATE } + hook = None + if progress_callback is not None: + # pyannote's diarization has two progress-trackable steps, each with + # its own completed/total counter that resets between steps. Map each + # step into a sub-range so progress is monotonic and meaningful. + _STEP_RANGES = { + "segmentation": (0.0, 50.0), + "embeddings": (50.0, 99.0), + } + last_pct = [0.0] + def hook(step_name, step_artifact, file=None, total=None, completed=None): + if total is not None and completed is not None and total > 0: + offset, end = _STEP_RANGES.get(step_name, (0.0, 99.0)) + pct = offset + min(completed / total, 1.0) * (end - offset) + if pct > last_pct[0]: + last_pct[0] = pct + progress_callback(pct) + output = self.model( audio_data, num_speakers=num_speakers, min_speakers=min_speakers, max_speakers=max_speakers, + **({"hook": hook} if hook is not None else {}), ) + if progress_callback is not None: + progress_callback(100.0) + diarization = output.speaker_diarization embeddings = output.speaker_embeddings if return_embeddings else None diff --git a/whisperx/schema.py b/whisperx/schema.py index 83d9147fd..e5287794b 100644 --- a/whisperx/schema.py +++ b/whisperx/schema.py @@ -1,4 +1,6 @@ -from typing import TypedDict, Optional, List, Tuple +from typing import Callable, TypedDict, Optional, List, Tuple + +ProgressCallback = Optional[Callable[[float], None]] try: from typing import NotRequired From 646f511e6bb47f8d2f0687e9976f8e7035b1e18d Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Tue, 17 Mar 2026 08:14:22 +0100 Subject: [PATCH 097/118] fix: remove dead model_bytes read that leaked file handle The open().read() call was left behind when the SHA-256 checksum validation was removed in 86e2b3e. The resulting model_bytes variable was never used, and the file descriptor was never closed. Closes #1376 Co-Authored-By: Claude Opus 4.6 (1M context) --- whisperx/vads/pyannote.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/whisperx/vads/pyannote.py b/whisperx/vads/pyannote.py index 28c1fbdf5..4e05101d2 100644 --- a/whisperx/vads/pyannote.py +++ b/whisperx/vads/pyannote.py @@ -38,8 +38,6 @@ def load_vad_model(device, vad_onset=0.500, vad_offset=0.363, token=None, model_ if os.path.exists(model_fp) and not os.path.isfile(model_fp): raise RuntimeError(f"{model_fp} exists and is not a regular file") - model_bytes = open(model_fp, "rb").read() - vad_model = Model.from_pretrained(model_fp, token=token) hyperparameters = {"onset": vad_onset, "offset": vad_offset, From 39aa9f50dbca20d729178e210885794fea94c1b6 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Sun, 15 Mar 2026 13:07:16 +0100 Subject: [PATCH 098/118] fix: restore word-level timestamps for unalignable characters (#1372) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Characters not in the alignment model's vocabulary (digits, symbols, foreign script) were excluded from CTC alignment and got no timestamps. Fix: extend the emission matrix with a wildcard column (max non-blank score per frame) so unknown chars participate in alignment via the existing get_trellis/backtrack — no changes to the CTC internals. Interpolation fallback fills any remaining gaps as a safety net. Unlike PR #986, this does not rewrite get_trellis or backtrack, so it avoids the regression that caused #1220. Co-Authored-By: Claude Opus 4.6 (1M context) --- tests/test_word_timestamp_interpolation.py | 135 +++++++++++++++++++++ whisperx/alignment.py | 36 +++++- 2 files changed, 166 insertions(+), 5 deletions(-) create mode 100644 tests/test_word_timestamp_interpolation.py diff --git a/tests/test_word_timestamp_interpolation.py b/tests/test_word_timestamp_interpolation.py new file mode 100644 index 000000000..08be577fd --- /dev/null +++ b/tests/test_word_timestamp_interpolation.py @@ -0,0 +1,135 @@ +"""Test that align() produces word-level timestamps for unalignable characters.""" + +import torch +from unittest.mock import MagicMock + +from whisperx.alignment import align + + +def _make_mock_model(emission, dictionary): + """Create a mock torchaudio-style model that returns a fixed emission matrix. + + The emission should be pre-log-softmax logits of shape (num_frames, vocab_size). + align() will apply log_softmax itself. + """ + model = MagicMock() + # torchaudio interface: model(waveform, lengths=lengths) -> (emissions, _) + # emissions shape: (batch=1, num_frames, vocab_size) + model.return_value = (emission.unsqueeze(0), None) + return model + + +def _make_emission(num_frames, dictionary, transcript_chars, blank_id=0): + """Build a synthetic emission matrix where known chars peak at the right frames. + + Distributes characters evenly across frames. Known chars get high logits + at their assigned frames. Unknown chars have no specific token but will + get wildcard treatment in align(). + """ + vocab_size = max(dictionary.values()) + 1 + # Start with uniform low logits, blank slightly favored + emission = torch.full((num_frames, vocab_size), -5.0) + emission[:, blank_id] = -1.0 + + # Assign each transcript char a span of frames + chars_in_dict = [(i, c) for i, c in enumerate(transcript_chars) + if c.lower() in dictionary] + if chars_in_dict: + frames_per_char = num_frames // (len(transcript_chars) + 1) + for seq_idx, (char_idx, char) in enumerate(chars_in_dict): + center = (char_idx + 1) * frames_per_char + start = max(0, center - frames_per_char // 2) + end = min(num_frames, center + frames_per_char // 2) + token_id = dictionary[char.lower()] + for t in range(start, end): + emission[t, token_id] = 2.0 # high logit for this token + emission[t, blank_id] = -3.0 # suppress blank + + return emission + + +class TestAlignWithWildcards: + """Test align() end-to-end with unknown characters.""" + + DICTIONARY = { + "": 0, # blank + "a": 1, "b": 2, "c": 3, "d": 4, "e": 5, + "f": 6, "g": 7, "h": 8, "i": 9, "k": 10, + "l": 11, "m": 12, "n": 13, "o": 14, "p": 15, + "r": 16, "s": 17, "t": 18, "u": 19, "w": 20, + "|": 21, + } + METADATA = {"language": "en", "dictionary": DICTIONARY, "type": "torchaudio"} + + def _run_align(self, text, duration=5.0, num_frames=100): + """Run align() with a mock model on a single segment.""" + torch.manual_seed(0) + emission = _make_emission(num_frames, self.DICTIONARY, list(text), blank_id=0) + model = _make_mock_model(emission, self.DICTIONARY) + + sample_rate = 16000 + num_samples = int(duration * sample_rate) + audio = torch.randn(num_samples) + + transcript = [{"text": text, "start": 0.0, "end": duration}] + result = align( + transcript=transcript, + model=model, + align_model_metadata=self.METADATA, + audio=audio, + device="cpu", + ) + return result + + def test_known_chars_get_timestamps(self): + """Baseline: words with all known chars get timestamps.""" + result = self._run_align("the cat sat") + for word in result["word_segments"]: + assert "start" in word, f"'{word['word']}' missing start" + assert "end" in word, f"'{word['word']}' missing end" + assert "score" in word, f"'{word['word']}' missing score" + + def test_unknown_word_gets_timestamps(self): + """A word made of unknown chars (digits) gets timestamps via wildcard.""" + result = self._run_align("cost 43 dollars") + words = {w["word"]: w for w in result["word_segments"]} + assert "43" in words, f"'43' not in word_segments: {list(words.keys())}" + assert "start" in words["43"], "'43' missing start timestamp" + assert "end" in words["43"], "'43' missing end timestamp" + assert "score" in words["43"], "'43' missing score" + + def test_mixed_word_gets_timestamps(self): + """A word with mixed known/unknown chars gets timestamps.""" + result = self._run_align("has 43k users") + # "43k" has unknown '4','3' and known 'k' + words = {w["word"]: w for w in result["word_segments"]} + assert "43k" in words, f"'43k' not in word_segments: {list(words.keys())}" + assert "start" in words["43k"] + assert "end" in words["43k"] + + def test_unknown_word_does_not_corrupt_neighbors(self): + """Known words adjacent to unknown words still get valid timestamps.""" + result = self._run_align("cost 43 dollars") + words = {w["word"]: w for w in result["word_segments"]} + for known in ("cost", "dollars"): + assert known in words + assert "start" in words[known], f"'{known}' missing start" + assert "end" in words[known], f"'{known}' missing end" + assert "score" in words[known], f"'{known}' missing score" + + def test_all_unknown_segment_gets_timestamps(self): + """A segment with only unknown chars gets wildcard-aligned timestamps.""" + result = self._run_align("123 456") + assert len(result["word_segments"]) > 0, "expected word_segments for all-unknown text" + for word in result["word_segments"]: + assert "start" in word, f"'{word['word']}' missing start" + assert "end" in word, f"'{word['word']}' missing end" + + def test_timestamps_are_ordered(self): + """Word timestamps are monotonically non-decreasing.""" + result = self._run_align("the 99 cats") + starts = [w["start"] for w in result["word_segments"] if "start" in w] + for i in range(1, len(starts)): + assert starts[i] >= starts[i - 1], ( + f"Timestamps not ordered: {starts}" + ) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 0786d0eb9..35b1f8aac 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -178,11 +178,12 @@ def align( elif char_ in model_dictionary.keys(): clean_char.append(char_) clean_cdx.append(cdx) + elif char_ not in (" ", "|"): + # unknown char (digit, symbol, foreign script) — use wildcard + clean_char.append(char_) + clean_cdx.append(cdx) - clean_wdx = [] - for wdx, wrd in enumerate(per_word): - if any([c in model_dictionary.keys() for c in wrd.lower()]): - clean_wdx.append(wdx) + clean_wdx = list(range(len(per_word))) # Use language-specific Punkt model if available otherwise we fallback to English. punkt_lang = PUNKT_LANGUAGES.get(model_lang, 'english') @@ -236,7 +237,6 @@ def align( continue text_clean = "".join(segment_data[sdx]["clean_char"]) - tokens = [model_dictionary[c] for c in text_clean] f1 = int(t1 * SAMPLE_RATE) f2 = int(t2 * SAMPLE_RATE) @@ -268,6 +268,19 @@ def align( if char == '[pad]' or char == '': blank_id = code + # Build tokens, mapping unknown chars to a wildcard column + has_wildcard = any(c not in model_dictionary for c in text_clean) + if has_wildcard: + # Extend emission with a wildcard column: max non-blank score per frame + non_blank_mask = torch.ones(emission.size(1), dtype=torch.bool) + non_blank_mask[blank_id] = False + wildcard_col = emission[:, non_blank_mask].max(dim=1).values + emission = torch.cat([emission, wildcard_col.unsqueeze(1)], dim=1) + wildcard_id = emission.size(1) - 1 + tokens = [model_dictionary.get(c, wildcard_id) for c in text_clean] + else: + tokens = [model_dictionary[c] for c in text_clean] + trellis = get_trellis(emission, tokens, blank_id) path = backtrack(trellis, emission, tokens, blank_id) @@ -348,6 +361,19 @@ def align( sentence_words.append(word_segment) + # Interpolate timestamps for words with no alignable characters + if sentence_words: + _starts = pd.Series([w.get("start", np.nan) for w in sentence_words]) + _ends = pd.Series([w.get("end", np.nan) for w in sentence_words]) + if _starts.isna().any() and _starts.notna().any(): + _starts = interpolate_nans(_starts, method=interpolate_method) + _ends = interpolate_nans(_ends, method=interpolate_method) + for i, w in enumerate(sentence_words): + if "start" not in w and pd.notna(_starts.iloc[i]): + w["start"] = _starts.iloc[i] + if "end" not in w and pd.notna(_ends.iloc[i]): + w["end"] = _ends.iloc[i] + subsegment = { "text": sentence_text, "start": sentence_start, From da072d6bcb593720566ff6c773f8caf86f1591e7 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Sun, 15 Mar 2026 13:33:11 +0100 Subject: [PATCH 099/118] test: add regression test for #1372 (digits+comma get no timestamps) Reproduces the exact reported bug: '4,9' embedded in text gets no start/end/score because digits and commas are not in the alignment model dictionary. Co-Authored-By: Claude Opus 4.6 (1M context) --- tests/test_word_timestamp_interpolation.py | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/tests/test_word_timestamp_interpolation.py b/tests/test_word_timestamp_interpolation.py index 08be577fd..ed2602eff 100644 --- a/tests/test_word_timestamp_interpolation.py +++ b/tests/test_word_timestamp_interpolation.py @@ -133,3 +133,17 @@ def test_timestamps_are_ordered(self): assert starts[i] >= starts[i - 1], ( f"Timestamps not ordered: {starts}" ) + + def test_issue_1372_digits_comma_no_timestamps(self): + """Regression: '4,9' (digits+comma) must get timestamps. + + https://github.com/m-bain/whisperX/issues/1372#issuecomment-4051234966 + Reporter showed that align() returned {'word': '4,9'} with no + start/end/score for German text containing '4,9'. + """ + result = self._run_align("halt mit 4,9 nicht ins parlament", num_frames=200) + words = {w["word"]: w for w in result["word_segments"]} + assert "4,9" in words, f"'4,9' not in word_segments: {list(words.keys())}" + assert "start" in words["4,9"], "'4,9' missing start" + assert "end" in words["4,9"], "'4,9' missing end" + assert "score" in words["4,9"], "'4,9' missing score" From f9a3f8fadae2832ae5b39aee7f469926acccbe58 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Sun, 15 Mar 2026 13:41:50 +0100 Subject: [PATCH 100/118] ci: add pytest dev dependency and test workflow Add pytest to optional dev dependencies and create a dedicated tests.yml workflow to run pytest across Python 3.10-3.13. Co-Authored-By: Claude Opus 4.6 (1M context) --- .github/workflows/tests.yml | 30 ++++++++++ pyproject.toml | 3 + uv.lock | 115 ++++++++++++++++++++++++++---------- 3 files changed, 118 insertions(+), 30 deletions(-) create mode 100644 .github/workflows/tests.yml diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml new file mode 100644 index 000000000..dbfd87509 --- /dev/null +++ b/.github/workflows/tests.yml @@ -0,0 +1,30 @@ +name: Tests + +on: + push: + branches: [main] + pull_request: + branches: [main] + workflow_dispatch: + +jobs: + test: + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ["3.10", "3.11", "3.12", "3.13"] + + steps: + - uses: actions/checkout@v4 + + - name: Install uv + uses: astral-sh/setup-uv@v5 + with: + version: "0.5.14" + python-version: ${{ matrix.python-version }} + + - name: Install the project + run: uv sync --all-extras + + - name: Run tests + run: uv run pytest tests/ -v diff --git a/pyproject.toml b/pyproject.toml index 94626d605..b5d69f625 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -24,6 +24,9 @@ dependencies = [ ] +[project.optional-dependencies] +dev = ["pytest"] + [project.scripts] whisperx = "whisperx.__main__:cli" diff --git a/uv.lock b/uv.lock index 22d61222e..2aace58a6 100644 --- a/uv.lock +++ b/uv.lock @@ -526,6 +526,18 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/87/62/9773de14fe6c45c23649e98b83231fffd7b9892b6cf863251dc2afa73643/einops-0.8.1-py3-none-any.whl", hash = "sha256:919387eb55330f5757c6bea9165c5ff5cfe63a642682ea788a6d472576d81737", size = 64359, upload-time = "2025-02-09T03:17:01.998Z" }, ] +[[package]] +name = "exceptiongroup" +version = "1.3.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "typing-extensions", marker = "python_full_version < '3.11'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/50/79/66800aadf48771f6b62f7eb014e352e5d06856655206165d775e675a02c9/exceptiongroup-1.3.1.tar.gz", hash = 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"https://download.pytorch.org/whl/cpu" }, { name = "torch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" }, @@ -3066,6 +3120,7 @@ requires-dist = [ { name = "transformers", specifier = ">=4.48.0" }, { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'", specifier = ">=3.3.0", index = "https://download.pytorch.org/whl/cu128" }, ] +provides-extras = ["dev"] [[package]] name = "yarl" From 94f60aab58564fdb5bfa7f34c77643daf6d22e00 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Wed, 25 Mar 2026 08:36:27 +0100 Subject: [PATCH 101/118] chore: bump version to 3.8.3 --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index b5d69f625..0a9f9f9a6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.8.2" +version = "3.8.3" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.10, <3.14" diff --git a/uv.lock b/uv.lock index 2aace58a6..c7f0e3453 100644 --- a/uv.lock +++ b/uv.lock @@ -3074,7 +3074,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.8.2" +version = "3.8.3" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, From 8efddaa2506c546fc66856405b5876033c1ca72a Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Wed, 25 Mar 2026 08:54:26 +0100 Subject: [PATCH 102/118] fix: require faster-whisper>=1.2.0 for use_auth_token support (#1385) Co-Authored-By: Claude Opus 4.6 (1M context) --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 0a9f9f9a6..1b87bd4fc 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,7 +10,7 @@ license = { text = "BSD-2-Clause" } dependencies = [ "ctranslate2>=4.5.0", - "faster-whisper>=1.1.1", + "faster-whisper>=1.2.0", "nltk>=3.9.1", "numpy>=2.1.0", "omegaconf>=2.3.0", diff --git a/uv.lock b/uv.lock index c7f0e3453..ade706d0f 100644 --- a/uv.lock +++ b/uv.lock @@ -3103,7 +3103,7 @@ dev = [ [package.metadata] requires-dist = [ { name = "ctranslate2", specifier = ">=4.5.0" }, - { name = "faster-whisper", specifier = ">=1.1.1" }, + { name = "faster-whisper", specifier = ">=1.2.0" }, { name = "huggingface-hub", specifier = "<1.0.0" }, { name = "nltk", specifier = ">=3.9.1" }, { name = "numpy", specifier = ">=2.1.0" }, From 095b36b5573ae2b6b7d0711d36c0e0c09df088d1 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Wed, 25 Mar 2026 09:10:59 +0100 Subject: [PATCH 103/118] chore: bump version to 3.8.4 --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 1b87bd4fc..df0592eaf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.8.3" +version = "3.8.4" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.10, <3.14" diff --git a/uv.lock b/uv.lock index ade706d0f..7b26699df 100644 --- a/uv.lock +++ b/uv.lock @@ -3074,7 +3074,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.8.3" +version = "3.8.4" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, From 5efa8592bb978e3f298112d37a2de8cc96f20f16 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Wed, 1 Apr 2026 08:55:43 +0200 Subject: [PATCH 104/118] fix: add torchvision~=0.23.0 dep to prevent torch version mismatch On environments like Google Colab where torchvision is pre-installed, `pip install whisperx` upgrades torch to 2.8.0 but leaves the old incompatible torchvision behind. The version mismatch causes `RuntimeError: operator torchvision::nms does not exist` which cascades through transformers' import chain into the confusing `ModuleNotFoundError: Could not import module 'Wav2Vec2ForCTC'`. Fixes #1339 Co-Authored-By: Claude Opus 4.6 (1M context) --- pyproject.toml | 1 + uv.lock | 46 +++++++++++++++++++++++++++++++++++++++++----- 2 files changed, 42 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index df0592eaf..1c04227bf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -19,6 +19,7 @@ dependencies = [ "huggingface-hub<1.0.0", "torch~=2.8.0", "torchaudio~=2.8.0", + "torchvision~=0.23.0", "transformers>=4.48.0", "triton>=3.3.0; sys_platform == 'linux' and platform_machine == 'x86_64'" # only install triton on x86_64 Linux ] diff --git a/uv.lock b/uv.lock index 7b26699df..5092333fd 100644 --- a/uv.lock +++ b/uv.lock @@ -2997,6 +2997,40 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/02/21/aa0f434434c48490f91b65962b1ce863fdcce63febc166ca9fe9d706c2b6/torchmetrics-1.8.2-py3-none-any.whl", hash = "sha256:08382fd96b923e39e904c4d570f3d49e2cc71ccabd2a94e0f895d1f0dac86242", size = 983161, upload-time = "2025-09-03T14:00:51.921Z" }, ] 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and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, { name = "torchaudio", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" }, + { name = "torchvision", specifier = "~=0.23.0" }, { name = "transformers", specifier = ">=4.48.0" }, { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'", specifier = ">=3.3.0", index = "https://download.pytorch.org/whl/cu128" }, ] From 03f5017c2ee7d15c4a21dfde8e2773c7a4f4f8d5 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Wed, 1 Apr 2026 08:56:15 +0200 Subject: [PATCH 105/118] fix: cap torchcodec <0.8.0 for torch 2.8 compatibility torchcodec 0.10.0 requires torch 2.10; only 0.6.x-0.7.x are compatible with torch 2.8. Without the cap, pip resolves to 0.10.0+ causing runtime errors. Platform markers are preserved since torchcodec has no aarch64 Linux wheels for these versions. Fixes #1392 Co-Authored-By: ssakkout <145016316+ssakkout@users.noreply.github.com> Co-Authored-By: Claude Opus 4.6 (1M context) --- pyproject.toml | 3 ++- uv.lock | 30 ++++++++++++++++-------------- 2 files changed, 18 insertions(+), 15 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 1c04227bf..7aa3c079a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -20,6 +20,7 @@ dependencies = [ "torch~=2.8.0", "torchaudio~=2.8.0", "torchvision~=0.23.0", + "torchcodec>=0.6.0,<0.8.0; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'darwin' or sys_platform == 'win32'", "transformers>=4.48.0", "triton>=3.3.0; sys_platform == 'linux' and platform_machine == 'x86_64'" # only install triton on x86_64 Linux ] @@ -44,7 +45,7 @@ include = ["whisperx*"] # torchcodec (transitive dep of pyannote-audio >=4) has no wheels for Linux aarch64 [tool.uv] override-dependencies = [ - "torchcodec>=0.6.0; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'darwin' or sys_platform == 'win32'", + "torchcodec>=0.6.0,<0.8.0; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'darwin' or sys_platform == 'win32'", ] [tool.uv.sources] diff --git a/uv.lock b/uv.lock index 5092333fd..ecf0aa6f5 100644 --- a/uv.lock +++ b/uv.lock @@ -21,7 +21,7 @@ resolution-markers = [ ] [manifest] -overrides = [{ name = "torchcodec", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'", specifier = ">=0.6.0" }] +overrides = [{ name = "torchcodec", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'", specifier = ">=0.6.0,<0.8.0" }] [[package]] name = "aiohappyeyeballs" @@ -2963,21 +2963,21 @@ wheels = [ [[package]] name = "torchcodec" -version = "0.10.0" +version = "0.7.0" source = { registry = "https://pypi.org/simple" } wheels = [ - { url = 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"torchvision" }, { name = "transformers" }, { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, @@ -3152,6 +3153,7 @@ requires-dist = [ { name = "torchaudio", marker = "sys_platform == 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, { name = "torchaudio", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, { name = "torchaudio", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" }, + { name = "torchcodec", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'", specifier = ">=0.6.0,<0.8.0" }, { name = "torchvision", specifier = "~=0.23.0" }, { name = "transformers", specifier = ">=4.48.0" }, { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'", specifier = ">=3.3.0", index = "https://download.pytorch.org/whl/cu128" }, From 4a6477e5e52ad516faab5363bdafbfa9840aec5e Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Wed, 1 Apr 2026 09:02:59 +0200 Subject: [PATCH 106/118] chore: bump version to 3.8.5 Co-Authored-By: Claude Opus 4.6 (1M context) --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 7aa3c079a..b7dc90f71 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.8.4" +version = "3.8.5" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.10, <3.14" diff --git a/uv.lock b/uv.lock index ecf0aa6f5..ce2213397 100644 --- a/uv.lock +++ b/uv.lock @@ -3108,7 +3108,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.8.4" +version = "3.8.5" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, From 1c4b23e13d79280a076e98644ac1e38321d253a9 Mon Sep 17 00:00:00 2001 From: Romario Martinus <67970344+aziib@users.noreply.github.com> Date: Sat, 4 Apr 2026 13:41:42 +0700 Subject: [PATCH 107/118] feat: add Indonesian language model to alignment (#1400) --- whisperx/alignment.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/whisperx/alignment.py b/whisperx/alignment.py index 35b1f8aac..12f123fd2 100644 --- a/whisperx/alignment.py +++ b/whisperx/alignment.py @@ -73,6 +73,7 @@ "lv": "jimregan/wav2vec2-large-xlsr-latvian-cv", "tl": "Khalsuu/filipino-wav2vec2-l-xls-r-300m-official", "sv": "KBLab/wav2vec2-large-voxrex-swedish", + "id": "cahya/wav2vec2-large-xlsr-indonesian", } @@ -536,4 +537,4 @@ def merge_words(segments, separator="|"): i2 = i1 else: i2 += 1 - return words \ No newline at end of file + return words From 9ccb28117bc626e04ced01219635f6e4c6bf3ad6 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Mon, 25 May 2026 09:38:11 +0200 Subject: [PATCH 108/118] fix: handle 'ignore' interpolation method in interpolate_nans (#1368) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit `--interpolate_method ignore` crashed with ValueError because pandas doesn't support "ignore" as a Series.interpolate() method. Return the series unchanged so NaN values are preserved — callers already guard with pd.notna() before assigning timestamps. Closes #1368 Co-Authored-By: Claude Opus 4.6 --- tests/test_word_timestamp_interpolation.py | 84 +++++++++++++++++++++- whisperx/utils.py | 2 + 2 files changed, 85 insertions(+), 1 deletion(-) diff --git a/tests/test_word_timestamp_interpolation.py b/tests/test_word_timestamp_interpolation.py index ed2602eff..ec2e9cf24 100644 --- a/tests/test_word_timestamp_interpolation.py +++ b/tests/test_word_timestamp_interpolation.py @@ -1,9 +1,12 @@ """Test that align() produces word-level timestamps for unalignable characters.""" +import numpy as np +import pandas as pd import torch from unittest.mock import MagicMock from whisperx.alignment import align +from whisperx.utils import interpolate_nans def _make_mock_model(emission, dictionary): @@ -61,7 +64,7 @@ class TestAlignWithWildcards: } METADATA = {"language": "en", "dictionary": DICTIONARY, "type": "torchaudio"} - def _run_align(self, text, duration=5.0, num_frames=100): + def _run_align(self, text, duration=5.0, num_frames=100, interpolate_method="nearest"): """Run align() with a mock model on a single segment.""" torch.manual_seed(0) emission = _make_emission(num_frames, self.DICTIONARY, list(text), blank_id=0) @@ -78,6 +81,7 @@ def _run_align(self, text, duration=5.0, num_frames=100): align_model_metadata=self.METADATA, audio=audio, device="cpu", + interpolate_method=interpolate_method, ) return result @@ -147,3 +151,81 @@ def test_issue_1372_digits_comma_no_timestamps(self): assert "start" in words["4,9"], "'4,9' missing start" assert "end" in words["4,9"], "'4,9' missing end" assert "score" in words["4,9"], "'4,9' missing score" + + def test_ignore_does_not_crash(self): + """interpolate_method='ignore' must not crash (issue #1368).""" + result = self._run_align("the 99 cats", interpolate_method="ignore") + words = {w["word"]: w for w in result["word_segments"]} + assert len(words) == 3 + for known in ("the", "cats"): + assert "start" in words[known], f"'{known}' missing start" + assert "end" in words[known], f"'{known}' missing end" + + def test_ignore_segments_have_valid_timestamps(self): + """Segments always have valid float start/end even with interpolate_method='ignore'.""" + result = self._run_align("the 99 cats", interpolate_method="ignore") + for seg in result["segments"]: + assert isinstance(seg["start"], float), f"segment start not float: {seg['start']}" + assert isinstance(seg["end"], float), f"segment end not float: {seg['end']}" + assert not np.isnan(seg["start"]), "segment start is NaN" + assert not np.isnan(seg["end"]), "segment end is NaN" + + +class TestInterpolateNans: + """Unit tests for interpolate_nans().""" + + def test_ignore_preserves_nans(self): + x = pd.Series([1.0, np.nan, 3.0, np.nan, 5.0]) + result = interpolate_nans(x, method="ignore") + assert result is x + assert result.isna().sum() == 2 + + def test_nearest_fills_nans(self): + x = pd.Series([1.0, np.nan, 3.0, np.nan, 5.0]) + result = interpolate_nans(x, method="nearest") + assert result.notna().all() + + def test_ignore_word_assignment_integration(self): + """Simulate the word-timestamp assignment logic from alignment.py:365-376. + + With wildcard CTC, this path is rarely reached in practice, but it's + the code that "ignore" is designed to affect. This test proves the + pieces fit together: interpolate_nans preserves NaN, and the pd.notna + guard prevents timestamp assignment to unaligned words. + """ + sentence_words = [ + {"word": "the", "start": 0.1, "end": 0.3}, + {"word": "99"}, # simulates a word with no CTC timestamps + {"word": "cats", "start": 0.6, "end": 0.9}, + ] + _starts = pd.Series([0.1, np.nan, 0.6]) + _ends = pd.Series([0.3, np.nan, 0.9]) + + # With "ignore": NaNs preserved, unaligned word stays without timestamps + _starts_ign = interpolate_nans(_starts, method="ignore") + _ends_ign = interpolate_nans(_ends, method="ignore") + for i, w in enumerate(sentence_words): + if "start" not in w and pd.notna(_starts_ign.iloc[i]): + w["start"] = _starts_ign.iloc[i] + if "end" not in w and pd.notna(_ends_ign.iloc[i]): + w["end"] = _ends_ign.iloc[i] + + assert "start" not in sentence_words[1], "'99' should not get start with ignore" + assert "end" not in sentence_words[1], "'99' should not get end with ignore" + + # With "nearest": NaNs filled, unaligned word gets interpolated timestamps + sentence_words_nearest = [ + {"word": "the", "start": 0.1, "end": 0.3}, + {"word": "99"}, + {"word": "cats", "start": 0.6, "end": 0.9}, + ] + _starts_nr = interpolate_nans(_starts.copy(), method="nearest") + _ends_nr = interpolate_nans(_ends.copy(), method="nearest") + for i, w in enumerate(sentence_words_nearest): + if "start" not in w and pd.notna(_starts_nr.iloc[i]): + w["start"] = _starts_nr.iloc[i] + if "end" not in w and pd.notna(_ends_nr.iloc[i]): + w["end"] = _ends_nr.iloc[i] + + assert "start" in sentence_words_nearest[1], "'99' should get start with nearest" + assert "end" in sentence_words_nearest[1], "'99' should get end with nearest" diff --git a/whisperx/utils.py b/whisperx/utils.py index ac8fb290d..510fd9c87 100644 --- a/whisperx/utils.py +++ b/whisperx/utils.py @@ -468,6 +468,8 @@ def write_all(result: dict, file: str, options: dict): return writers[output_format](output_dir) def interpolate_nans(x, method='nearest'): + if method == "ignore": + return x if x.notnull().sum() > 1: return x.interpolate(method=method).ffill().bfill() else: From 2b5236697e492aec0d300cfdb0f5c31c0aac8ce5 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 25 May 2026 07:52:24 +0000 Subject: [PATCH 109/118] build(deps): bump nltk from 3.9.2 to 3.9.4 Bumps [nltk](https://github.com/nltk/nltk) from 3.9.2 to 3.9.4. - [Changelog](https://github.com/nltk/nltk/blob/develop/ChangeLog) - [Commits](https://github.com/nltk/nltk/compare/3.9.2...3.9.4) --- updated-dependencies: - dependency-name: nltk dependency-version: 3.9.4 dependency-type: direct:production ... 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Fix all existing workflow findings: pin actions to commit hashes, add persist-credentials: false, set explicit least-privilege permissions, disable uv cache in release workflow to prevent cache poisoning. Co-Authored-By: Claude Opus 4.6 --- .github/workflows/build-and-release.yml | 13 ++++++++--- .github/workflows/python-compatibility.yml | 10 +++++++-- .github/workflows/tests.yml | 10 +++++++-- .github/workflows/zizmor.yml | 26 ++++++++++++++++++++++ 4 files changed, 52 insertions(+), 7 deletions(-) create mode 100644 .github/workflows/zizmor.yml diff --git a/.github/workflows/build-and-release.yml b/.github/workflows/build-and-release.yml index f98af785e..469a04ad8 100644 --- a/.github/workflows/build-and-release.yml +++ b/.github/workflows/build-and-release.yml @@ -4,18 +4,25 @@ on: release: types: [published] +permissions: {} + jobs: build: runs-on: ubuntu-latest + permissions: + contents: write steps: - name: Checkout - uses: actions/checkout@v4 + uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1 + with: + persist-credentials: false - name: Install uv - uses: astral-sh/setup-uv@v5 + uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2 with: version: "0.5.14" python-version: "3.10" + enable-cache: false - name: Check if lockfile is up to date run: uv lock --check @@ -24,7 +31,7 @@ jobs: run: uv build - name: Release to Github - uses: softprops/action-gh-release@v2 + uses: softprops/action-gh-release@3bb12739c298aeb8a4eeaf626c5b8d85266b0e65 # v2.6.2 with: files: dist/*.whl diff --git a/.github/workflows/python-compatibility.yml b/.github/workflows/python-compatibility.yml index 17a793bf3..43c29384b 100644 --- a/.github/workflows/python-compatibility.yml +++ b/.github/workflows/python-compatibility.yml @@ -7,18 +7,24 @@ on: branches: [main] workflow_dispatch: # Allows manual triggering from GitHub UI +permissions: {} + jobs: test: runs-on: ubuntu-latest + permissions: + contents: read strategy: matrix: python-version: ["3.10", "3.11", "3.12", "3.13"] steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1 + with: + persist-credentials: false - name: Install uv - uses: astral-sh/setup-uv@v5 + uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2 with: version: "0.5.14" python-version: ${{ matrix.python-version }} diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index dbfd87509..89fa3d358 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -7,18 +7,24 @@ on: branches: [main] workflow_dispatch: +permissions: {} + jobs: test: runs-on: ubuntu-latest + permissions: + contents: read strategy: matrix: python-version: ["3.10", "3.11", "3.12", "3.13"] steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1 + with: + persist-credentials: false - name: Install uv - uses: astral-sh/setup-uv@v5 + uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2 with: version: "0.5.14" python-version: ${{ matrix.python-version }} diff --git a/.github/workflows/zizmor.yml b/.github/workflows/zizmor.yml new file mode 100644 index 000000000..1d46a1da1 --- /dev/null +++ b/.github/workflows/zizmor.yml @@ -0,0 +1,26 @@ +name: GitHub Actions Security Analysis with zizmor + +on: + push: + branches: [main] + pull_request: + branches: ["**"] + +permissions: {} + +jobs: + zizmor: + name: Run zizmor + runs-on: ubuntu-latest + permissions: + security-events: write + contents: read + actions: read + steps: + - name: Checkout repository + uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2 + with: + persist-credentials: false + + - name: Run zizmor + uses: zizmorcore/zizmor-action@5f14fd08f7cf1cb1609c1e344975f152c7ee938d # v0.5.6 From 1e413774344ca0e617ad05d8a8c671c8c2369141 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Mon, 25 May 2026 10:08:06 +0200 Subject: [PATCH 111/118] ci: align actions/checkout to v6.0.2 across all workflows Co-Authored-By: Claude Opus 4.6 --- .github/workflows/build-and-release.yml | 2 +- .github/workflows/python-compatibility.yml | 2 +- .github/workflows/tests.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/build-and-release.yml b/.github/workflows/build-and-release.yml index 469a04ad8..56a862fca 100644 --- a/.github/workflows/build-and-release.yml +++ b/.github/workflows/build-and-release.yml @@ -13,7 +13,7 @@ jobs: contents: write steps: - name: Checkout - uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1 + uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2 with: persist-credentials: false diff --git a/.github/workflows/python-compatibility.yml b/.github/workflows/python-compatibility.yml index 43c29384b..fe9d55f2a 100644 --- a/.github/workflows/python-compatibility.yml +++ b/.github/workflows/python-compatibility.yml @@ -19,7 +19,7 @@ jobs: python-version: ["3.10", "3.11", "3.12", "3.13"] steps: - - uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1 + - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2 with: persist-credentials: false diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 89fa3d358..5713a0c4b 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -19,7 +19,7 @@ jobs: python-version: ["3.10", "3.11", "3.12", "3.13"] steps: - - uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1 + - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2 with: persist-credentials: false From e6ad0ca587477c8cbc02c0b4dba26650a4ff6511 Mon Sep 17 00:00:00 2001 From: Claude-Assistant Date: Mon, 25 May 2026 10:13:31 +0200 Subject: [PATCH 112/118] ci: replace softprops/action-gh-release with gh CLI Remove third-party action in favor of pre-installed gh CLI. Pass release tag via env var to prevent template injection. Co-Authored-By: Claude Opus 4.6 --- .github/workflows/build-and-release.yml | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/.github/workflows/build-and-release.yml b/.github/workflows/build-and-release.yml index 56a862fca..9318e7a13 100644 --- a/.github/workflows/build-and-release.yml +++ b/.github/workflows/build-and-release.yml @@ -31,9 +31,10 @@ jobs: run: uv build - name: Release to Github - uses: softprops/action-gh-release@3bb12739c298aeb8a4eeaf626c5b8d85266b0e65 # v2.6.2 - with: - files: dist/*.whl + run: gh release upload "$RELEASE_TAG" dist/*.whl + env: + GH_TOKEN: ${{ github.token }} + RELEASE_TAG: ${{ github.event.release.tag_name }} - name: Publish package to PyPi run: uv publish From a75cd503eb2ee1f3e5d3439c159693f1d113301c Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Mon, 25 May 2026 10:32:38 +0200 Subject: [PATCH 113/118] chore(deps): update exclude-newer settings --- pyproject.toml | 4 ++++ uv.lock | 4 ++++ 2 files changed, 8 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index b7dc90f71..4d28509e5 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -44,10 +44,14 @@ include = ["whisperx*"] # torchcodec (transitive dep of pyannote-audio >=4) has no wheels for Linux aarch64 [tool.uv] +exclude-newer = "1 week" override-dependencies = [ "torchcodec>=0.6.0,<0.8.0; (sys_platform == 'linux' and platform_machine == 'x86_64') or sys_platform == 'darwin' or sys_platform == 'win32'", ] +[tool.uv.pip] +exclude-newer = "1 week" + [tool.uv.sources] torch = [ { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" }, diff --git a/uv.lock b/uv.lock index cfbaff748..90cbb9425 100644 --- a/uv.lock +++ b/uv.lock @@ -20,6 +20,10 @@ resolution-markers = [ "python_full_version < '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin'", ] +[options] +exclude-newer = "0001-01-01T00:00:00Z" # This has no effect and is included for backwards compatibility when using relative exclude-newer values. +exclude-newer-span = "P1W" + [manifest] overrides = [{ name = "torchcodec", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'", specifier = ">=0.6.0,<0.8.0" }] From 4cbcd1a13809b71fca3e2f3fe93fb8183d4e9821 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Mon, 25 May 2026 14:26:59 +0200 Subject: [PATCH 114/118] chore(deps): update uv version to 0.11.6 in workflows --- .github/workflows/build-and-release.yml | 2 +- .github/workflows/python-compatibility.yml | 2 +- .github/workflows/tests.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/build-and-release.yml b/.github/workflows/build-and-release.yml index 9318e7a13..e0d70d958 100644 --- a/.github/workflows/build-and-release.yml +++ b/.github/workflows/build-and-release.yml @@ -20,7 +20,7 @@ jobs: - name: Install uv uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2 with: - version: "0.5.14" + version: "0.11.6 python-version: "3.10" enable-cache: false diff --git a/.github/workflows/python-compatibility.yml b/.github/workflows/python-compatibility.yml index fe9d55f2a..8b748c5da 100644 --- a/.github/workflows/python-compatibility.yml +++ b/.github/workflows/python-compatibility.yml @@ -26,7 +26,7 @@ jobs: - name: Install uv uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2 with: - version: "0.5.14" + version: "0.11.6" python-version: ${{ matrix.python-version }} - name: Check if lockfile is up to date diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 5713a0c4b..794e818dd 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -26,7 +26,7 @@ jobs: - name: Install uv uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2 with: - version: "0.5.14" + version: "0.11.6" python-version: ${{ matrix.python-version }} - name: Install the project From 5d8c276a3cd87d872e2abaedfbc25ae84d072ff8 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Mon, 25 May 2026 14:33:02 +0200 Subject: [PATCH 115/118] fix: correct syntax error in uv version specification --- .github/workflows/build-and-release.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build-and-release.yml b/.github/workflows/build-and-release.yml index e0d70d958..8c5fe43a7 100644 --- a/.github/workflows/build-and-release.yml +++ b/.github/workflows/build-and-release.yml @@ -20,7 +20,7 @@ jobs: - name: Install uv uses: astral-sh/setup-uv@d4b2f3b6ecc6e67c4457f6d3e41ec42d3d0fcb86 # v5.4.2 with: - version: "0.11.6 + version: "0.11.6" python-version: "3.10" enable-cache: false From 3ccc17b8de34f305300f8a3fd3c9f76ba820c0d0 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Mon, 25 May 2026 14:34:44 +0200 Subject: [PATCH 116/118] chore: bump whisperx to 3.8.6 --- pyproject.toml | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 4d28509e5..0759abbbd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,7 @@ urls = { repository = "https://github.com/m-bain/whisperx" } authors = [{ name = "Max Bain" }] name = "whisperx" -version = "3.8.5" +version = "3.8.6" description = "Time-Accurate Automatic Speech Recognition using Whisper." readme = "README.md" requires-python = ">=3.10, <3.14" diff --git a/uv.lock b/uv.lock index 90cbb9425..c71d72d7d 100644 --- a/uv.lock +++ b/uv.lock @@ -3112,7 +3112,7 @@ wheels = [ [[package]] name = "whisperx" -version = "3.8.5" +version = "3.8.6" source = { editable = "." } dependencies = [ { name = "ctranslate2" }, From 11bc7de48e48cf16d514673d2c63578a80b06a04 Mon Sep 17 00:00:00 2001 From: Deeksha Manjunath Date: Thu, 14 May 2026 22:28:55 -0700 Subject: [PATCH 117/118] Fix Windows CUDA detection: include AMD64 in platform markers (#1357) On Windows, platform.machine() returns 'AMD64' instead of 'x86_64'. The uv source markers only checked for 'x86_64', so Windows users were always routed to the pytorch-cpu index even on CUDA-capable systems. Add 'AMD64' alongside 'x86_64' in the torch and torchaudio source markers so that Windows GPU systems correctly resolve to the CUDA pytorch index. --- pyproject.toml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 0759abbbd..0d10ffd6d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,13 +55,13 @@ exclude-newer = "1 week" [tool.uv.sources] torch = [ { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" }, - { index = "pytorch-cpu", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { index = "pytorch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { index = "pytorch-cpu", marker = "platform_machine != 'x86_64' and platform_machine != 'AMD64' and sys_platform != 'darwin'" }, + { index = "pytorch", marker = "(platform_machine == 'x86_64' or platform_machine == 'AMD64') and sys_platform != 'darwin'" }, ] torchaudio = [ { index = "pytorch-cpu", marker = "sys_platform == 'darwin'" }, - { index = "pytorch-cpu", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { index = "pytorch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { index = "pytorch-cpu", marker = "platform_machine != 'x86_64' and platform_machine != 'AMD64' and sys_platform != 'darwin'" }, + { index = "pytorch", marker = "(platform_machine == 'x86_64' or platform_machine == 'AMD64') and sys_platform != 'darwin'" }, ] triton = [ { index = "pytorch", marker = "sys_platform == 'linux'" }, From 5f2f9d4320dd93a7d12f5ba2495eef7e0a5af963 Mon Sep 17 00:00:00 2001 From: Barabazs <31799121+Barabazs@users.noreply.github.com> Date: Wed, 3 Jun 2026 09:34:46 +0200 Subject: [PATCH 118/118] chore: regenerate uv.lock for AMD64 markers --- uv.lock | 176 ++++++++++++++++++++++++++++++++------------------------ 1 file changed, 100 insertions(+), 76 deletions(-) diff --git a/uv.lock b/uv.lock index c71d72d7d..d95efd3cf 100644 --- a/uv.lock +++ b/uv.lock @@ -3,17 +3,21 @@ revision = 3 requires-python = ">=3.10, <3.14" resolution-markers = [ "python_full_version >= '3.13' and sys_platform == 'darwin'", - "(python_full_version >= '3.13' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version >= '3.13' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version >= '3.13' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and sys_platform == 'darwin'", "python_full_version == '3.11.*' and sys_platform == 'darwin'", "python_full_version < '3.11' and sys_platform == 'darwin'", - "(python_full_version == '3.12.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version == '3.12.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", - "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version == '3.11.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", - "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version < '3.11' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", @@ -163,8 +167,8 @@ source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "numpy" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "typing-extensions" }, ] sdist = { url = "https://files.pythonhosted.org/packages/90/fa/5c2be1f96dc179f83cdd3bb267edbd1f47d08f756785c016d5c2163901a7/asteroid-filterbanks-0.4.0.tar.gz", hash = "sha256:415f89d1dcf2b13b35f03f7a9370968ac4e6fa6800633c522dac992b283409b9", size = 24599, upload-time = "2021-04-09T20:03:07.456Z" } @@ -339,7 +343,8 @@ version = "1.3.2" source = { registry = "https://pypi.org/simple" } resolution-markers = [ "python_full_version < '3.11' and sys_platform == 'darwin'", - "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version < '3.11' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version < '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin'", ] @@ -412,14 +417,17 @@ version = "1.3.3" source = { registry = "https://pypi.org/simple" } resolution-markers = [ "python_full_version >= '3.13' and sys_platform == 'darwin'", - "(python_full_version >= '3.13' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version >= '3.13' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version >= '3.13' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and sys_platform == 'darwin'", "python_full_version == '3.11.*' and sys_platform == 'darwin'", - "(python_full_version == '3.12.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version == '3.12.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", - "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version == '3.11.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", @@ -940,8 +948,8 @@ version = "0.2.7" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, ] sdist = { url = "https://files.pythonhosted.org/packages/a1/19/c9e1596b5572c786b93428d0904280e964c930fae7e6c9368ed9e1b63922/julius-0.2.7.tar.gz", hash = "sha256:3c0f5f5306d7d6016fcc95196b274cae6f07e2c9596eed314e4e7641554fbb08", size = 59640, upload-time = "2022-09-19T16:13:34.2Z" } @@ -1038,8 +1046,8 @@ dependencies = [ { name = "pytorch-lightning" }, { name = "pyyaml" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "torchmetrics" }, { name = "tqdm" }, { name = "typing-extensions" }, @@ -1336,7 +1344,8 @@ version = "3.4.2" source = { registry = "https://pypi.org/simple" } resolution-markers = [ "python_full_version < '3.11' and sys_platform == 'darwin'", - "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version < '3.11' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version < '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin'", ] @@ -1351,14 +1360,17 @@ version = "3.5" source = { registry = "https://pypi.org/simple" } resolution-markers = [ "python_full_version >= '3.13' and sys_platform == 'darwin'", - "(python_full_version >= '3.13' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version >= '3.13' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version >= '3.13' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and sys_platform == 'darwin'", "python_full_version == '3.11.*' and sys_platform == 'darwin'", - "(python_full_version == '3.12.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version == '3.12.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", - "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version == '3.11.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", @@ -2027,12 +2039,12 @@ dependencies = [ { name = "rich" }, { name = "safetensors" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "torch-audiomentations" }, { name = "torchaudio", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux') or sys_platform == 'darwin'" }, - { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')" }, - { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')" }, + { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "torchcodec", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'" }, { name = "torchmetrics" }, ] @@ -2183,8 +2195,8 @@ dependencies = [ { name = "packaging" }, { name = "pyyaml" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "torchmetrics" }, { name = "tqdm" }, { name = "typing-extensions" }, @@ -2202,8 +2214,8 @@ dependencies = [ { name = "numpy" }, { name = "scikit-learn" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "tqdm" }, ] sdist = { url = "https://files.pythonhosted.org/packages/9b/80/6e61b1a91debf4c1b47d441f9a9d7fe2aabcdd9575ed70b2811474eb95c3/pytorch-metric-learning-2.9.0.tar.gz", hash = "sha256:27a626caf5e2876a0fd666605a78cb67ef7597e25d7a68c18053dd503830701f", size = 84530, upload-time = "2025-08-17T17:11:19.501Z" } @@ -2441,7 +2453,8 @@ version = "1.15.3" source = { registry = "https://pypi.org/simple" } resolution-markers = [ "python_full_version < '3.11' and sys_platform == 'darwin'", - "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version < '3.11' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version < '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin'", ] @@ -2503,14 +2516,17 @@ version = "1.16.2" source = { registry = "https://pypi.org/simple" } resolution-markers = [ "python_full_version >= '3.13' and sys_platform == 'darwin'", - "(python_full_version >= '3.13' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version >= '3.13' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version >= '3.13' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and sys_platform == 'darwin'", "python_full_version == '3.11.*' and sys_platform == 'darwin'", - "(python_full_version == '3.12.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version == '3.12.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", - "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "python_full_version == '3.11.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", @@ -2752,24 +2768,24 @@ name = "torch" version = "2.8.0+cpu" source = { registry = "https://download.pytorch.org/whl/cpu" } resolution-markers = [ - "(python_full_version >= '3.13' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", "python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", - "(python_full_version == '3.12.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", "python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", - "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", - "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'", ] dependencies = [ - { name = "filelock", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "fsspec", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "jinja2", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "networkx", version = "3.4.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "networkx", version = "3.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "setuptools", marker = "python_full_version >= '3.12' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "sympy", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "typing-extensions", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "filelock", marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "fsspec", marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "jinja2", marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "networkx", version = "3.4.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "networkx", version = "3.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "setuptools", marker = "python_full_version >= '3.12' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "sympy", marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "typing-extensions", marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, ] wheels = [ { url = "https://download-r2.pytorch.org/whl/cpu/torch-2.8.0%2Bcpu-cp310-cp310-linux_s390x.whl", hash = "sha256:5d255d259fbc65439b671580e40fdb8faea4644761b64fed90d6904ffe71bbc1", upload-time = "2025-10-01T23:32:36Z" }, @@ -2801,17 +2817,21 @@ name = "torch" version = "2.8.0+cu128" source = { registry = "https://download.pytorch.org/whl/cu128" } resolution-markers = [ + "python_full_version >= '3.13' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version >= '3.13' and platform_machine == 'x86_64' and sys_platform != 'darwin'", + "python_full_version == '3.12.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", + "python_full_version == '3.11.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", + "python_full_version < '3.11' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version < '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin'", ] dependencies = [ - { name = "filelock", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, - { name = "fsspec", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, - { name = "jinja2", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, - { name = "networkx", version = "3.4.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin'" }, - { name = "networkx", version = "3.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "filelock", marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, + { name = "fsspec", marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, + { name = "jinja2", marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, + { name = "networkx", version = "3.4.2", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version < '3.11' and platform_machine == 'AMD64' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin')" }, + { name = "networkx", version = "3.5", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.11' and platform_machine == 'AMD64' and sys_platform != 'darwin') or (python_full_version >= '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, @@ -2826,10 +2846,10 @@ dependencies = [ { name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "nvidia-nvjitlink-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, { name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "setuptools", marker = "python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform != 'darwin'" }, - { name = "sympy", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "setuptools", marker = "(python_full_version >= '3.12' and platform_machine == 'AMD64' and sys_platform != 'darwin') or (python_full_version >= '3.12' and platform_machine == 'x86_64' and sys_platform != 'darwin')" }, + { name = "sympy", marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" }, - { name = "typing-extensions", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "typing-extensions", marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, ] wheels = [ { url = "https://download-r2.pytorch.org/whl/cu128/torch-2.8.0%2Bcu128-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:0c96999d15cf1f13dd7c913e0b21a9a355538e6cfc10861a17158320292f5954", upload-time = "2025-10-01T23:47:19Z" }, @@ -2851,12 +2871,12 @@ source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "julius" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "torch-pitch-shift" }, { name = "torchaudio", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux') or sys_platform == 'darwin'" }, - { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')" }, - { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')" }, + { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, ] sdist = { url = "https://files.pythonhosted.org/packages/31/8d/2f8fd7e34c75f5ee8de4310c3bd3f22270acd44d1f809e2fe7c12fbf35f8/torch_audiomentations-0.12.0.tar.gz", hash = "sha256:b02d4c5eb86376986a53eb405cca5e34f370ea9284411237508e720c529f7888", size = 52094, upload-time = "2025-01-15T09:07:01.071Z" } wheels = [ @@ -2871,11 +2891,11 @@ dependencies = [ { name = "packaging" }, { name = "primepy" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "torchaudio", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux') or sys_platform == 'darwin'" }, - { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')" }, - { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')" }, + { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, ] sdist = { url = "https://files.pythonhosted.org/packages/79/a6/722a832bca75d5079f6731e005b3d0c2eec7c6c6863d030620952d143d57/torch_pitch_shift-1.2.5.tar.gz", hash = "sha256:6e1c7531f08d0f407a4c55e5ff8385a41355c5c5d27ab7fa08632e51defbd0ed", size = 4725, upload-time = "2024-09-25T19:10:12.922Z" } wheels = [ @@ -2918,13 +2938,13 @@ name = "torchaudio" version = "2.8.0+cpu" source = { registry = "https://download.pytorch.org/whl/cpu" } resolution-markers = [ - "(python_full_version >= '3.13' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", - "(python_full_version == '3.12.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", - "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", - "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "(python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "(python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", + "(python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')", ] dependencies = [ - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')" }, ] wheels = [ { url = "https://download-r2.pytorch.org/whl/cpu/torchaudio-2.8.0%2Bcpu-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:c955835e470ebbde03d7d54ca5d8ba5722138bbfd66cfb86845234b3a5b9f9fa", upload-time = "2025-08-05T20:12:02Z" }, @@ -2944,13 +2964,17 @@ name = "torchaudio" version = "2.8.0+cu128" source = { registry = "https://download.pytorch.org/whl/cu128" } resolution-markers = [ + "python_full_version >= '3.13' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version >= '3.13' and platform_machine == 'x86_64' and sys_platform != 'darwin'", + "python_full_version == '3.12.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", + "python_full_version == '3.11.*' and platform_machine == 'AMD64' and sys_platform != 'darwin'", + "python_full_version < '3.11' and platform_machine == 'AMD64' and sys_platform != 'darwin'", "python_full_version == '3.12.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'x86_64' and sys_platform != 'darwin'", "python_full_version < '3.11' and platform_machine == 'x86_64' and sys_platform != 'darwin'", ] dependencies = [ - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, ] wheels = [ { url = "https://download-r2.pytorch.org/whl/cu128/torchaudio-2.8.0%2Bcu128-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:a0161e95285a0b716de210fee0392151d601e7da3cc86595008d826abff48a8c", upload-time = "2025-08-05T20:12:07Z" }, @@ -2993,8 +3017,8 @@ dependencies = [ { name = "numpy" }, { name = "packaging" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, ] sdist = { url = "https://files.pythonhosted.org/packages/85/2e/48a887a59ecc4a10ce9e8b35b3e3c5cef29d902c4eac143378526e7485cb/torchmetrics-1.8.2.tar.gz", hash = "sha256:cf64a901036bf107f17a524009eea7781c9c5315d130713aeca5747a686fe7a5", size = 580679, upload-time = "2025-09-03T14:00:54.077Z" } wheels = [ @@ -3009,8 +3033,8 @@ dependencies = [ { name = "numpy" }, { name = "pillow" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, ] wheels = [ { url = "https://files.pythonhosted.org/packages/4d/49/5ad5c3ff4920be0adee9eb4339b4fb3b023a0fc55b9ed8dbc73df92946b8/torchvision-0.23.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:7266871daca00ad46d1c073e55d972179d12a58fa5c9adec9a3db9bbed71284a", size = 1856885, upload-time = "2025-08-06T14:57:55.024Z" }, @@ -3124,11 +3148,11 @@ dependencies = [ { name = "pandas" }, { name = "pyannote-audio" }, { name = "torch", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "sys_platform == 'darwin'" }, - { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'" }, - { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'" }, + { name = "torch", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "torchaudio", version = "2.8.0", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux') or sys_platform == 'darwin'" }, - { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux') or (platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux')" }, - { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'" }, + { name = "torchaudio", version = "2.8.0+cpu", source = { registry = "https://download.pytorch.org/whl/cpu" }, marker = "(platform_machine != 'AMD64' and platform_machine != 'aarch64' and platform_machine != 'x86_64' and sys_platform == 'linux') or (platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin' and sys_platform != 'linux') or (platform_machine == 'aarch64' and platform_python_implementation != 'CPython' and sys_platform == 'linux')" }, + { name = "torchaudio", version = "2.8.0+cu128", source = { registry = "https://download.pytorch.org/whl/cu128" }, marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')" }, { name = "torchcodec", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'" }, { name = "torchvision" }, { name = "transformers" }, @@ -3152,11 +3176,11 @@ requires-dist = [ { name = "pyannote-audio", specifier = ">=4.0.0" }, { name = "pytest", marker = "extra == 'dev'" }, { name = "torch", marker = "sys_platform == 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torch", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torch", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" }, + { name = "torch", marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torch", marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" }, { name = "torchaudio", marker = "sys_platform == 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torchaudio", marker = "platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, - { name = "torchaudio", marker = "platform_machine == 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" }, + { name = "torchaudio", marker = "platform_machine != 'AMD64' and platform_machine != 'x86_64' and sys_platform != 'darwin'", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cpu" }, + { name = "torchaudio", marker = "(platform_machine == 'AMD64' and sys_platform != 'darwin') or (platform_machine == 'x86_64' and sys_platform != 'darwin')", specifier = "~=2.8.0", index = "https://download.pytorch.org/whl/cu128" }, { name = "torchcodec", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin' or sys_platform == 'win32'", specifier = ">=0.6.0,<0.8.0" }, { name = "torchvision", specifier = "~=0.23.0" }, { name = "transformers", specifier = ">=4.48.0" },