* Relax triton requirements for compatibility with pytorch 2.4 and newer
Similar to https://github.com/openai/whisper/pull/1802, but now when pytorch upgrades to 2.4, it requires triton==3.0.0. I am not sure if it makes sense to remove the upper bound version constraints
* Update requirements.txt
* Drop ffmpeg-python dependency and call ffmpeg directly.
The last ffmpeg-python module release was in 2019[1], upstream seem to be
unavailable[2] and the project development seem to have stagnated[3]. As
the features it provide is trivial to replace using the Python native
subprocess module, drop the dependency.
[1] <URL: https://github.com/kkroening/ffmpeg-python/tags >
[2] <URL: https://github.com/kkroening/ffmpeg-python/issues/760 >
[3] <URL: https://openhub.net/p/ffmpeg-python >
* Rewrote to use subprocess.run() instead of subprocess.Popen().
* formatting changes
* formatting update
* isort fix
* Error checking
* isort 🤦🏻
* flake8 fix
* minor spelling changes
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Co-authored-by: Jong Wook Kim <jongwook@openai.com>
* word-level timestamps in `transcribe()`
* moving to `timing.py`
* numba implementation for dtw, replacing dtw-python
* triton implementation for dtw
* add test for dtw implementations
* triton implementation of median_filter
* a simple word-level timestamps test
* add scipy as dev dependency
* installs an older version of Triton if CUDA < 11.4
* fix broken merge
* loosen nvcc version match regex
* find_alignment() function
* miscellaneous improvements
* skip median filtering when the input is too small
* Expose punctuation options in cli and transcribe() (#973)
* fix merge error
* fix merge error 2
* annotating that word_timestamps is experimental
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Co-authored-by: ryanheise <ryan@ryanheise.com>
* fix: more-itertools name in requirements.txt
* feature: minimal environment.yml for conda
* Revert "feature: minimal environment.yml for conda"
This reverts commit 8fd7438b368b0eb5df85f667fea911f293fa5e6d.
Co-authored-by: Jong Wook Kim <jongwook@nyu.edu>
