Reinsert whisper model transcribing
This commit is contained in:
parent
3246469be2
commit
30fd269cd9
6 changed files with 483 additions and 177 deletions
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@ -53,7 +53,7 @@ RUN mkdir -p ${VERBANOTE_OUTPUT_PATH}
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RUN rm "${VIRTUAL_ENV}/bin/python"
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RUN ln -s "/opt/conda/bin/python" "${VIRTUAL_ENV}/bin/python"
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RUN which python
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RUN ltt install --pytorch-computation-backend=cu117 torch torchvision torchaudio
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RUN ltt install --pytorch-computation-backend=cu117 torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1
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COPY ./${APP_NAME} ./${APP_NAME}
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552
poetry.lock
generated
552
poetry.lock
generated
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@ -185,6 +185,7 @@ files = [
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]
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[package.dependencies]
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exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
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idna = ">=2.8"
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sniffio = ">=1.1"
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@ -550,6 +551,35 @@ numpy = "*"
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[package.extras]
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cmawm = ["scipy"]
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[[package]]
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name = "cmake"
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version = "3.27.2"
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description = "CMake is an open-source, cross-platform family of tools designed to build, test and package software"
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optional = false
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python-versions = "*"
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files = [
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{file = "cmake-3.27.2-py2.py3-none-musllinux_1_1_i686.whl", hash = "sha256:294f008734267e0eee1574ad1b911bed137bc907ab19d60a618dab4615aa1fca"},
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{file = "cmake-3.27.2-py2.py3-none-musllinux_1_1_ppc64le.whl", hash = "sha256:197a34dc62ee149ced343545fac67e5a30b93fda65250b065726f86ce92bdada"},
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{file = "cmake-3.27.2-py2.py3-none-musllinux_1_1_s390x.whl", hash = "sha256:afb46ad883b174fb64347802ba5878423551dbd5847bb64669c39a5957c06eb7"},
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{file = "cmake-3.27.2-py2.py3-none-musllinux_1_1_x86_64.whl", hash = "sha256:83611ffd155e270a6b13bbf0cfd4e8688ebda634f448aa2e3734006c745bf33f"},
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{file = "cmake-3.27.2-py2.py3-none-win32.whl", hash = "sha256:53e12deb893da935e236f93accd47dbe2806620cd7654986234dc4487cc49652"},
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{file = "cmake-3.27.2-py2.py3-none-win_amd64.whl", hash = "sha256:611f9722c68c40352d38a6c01960ab038c3d0419e7aee3bf18f95b23031e0dfe"},
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{file = "cmake-3.27.2-py2.py3-none-win_arm64.whl", hash = "sha256:30620326b51ac2ce0d8f476747af6367a7ea21075c4d065fad9443904b07476a"},
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{file = "cmake-3.27.2.tar.gz", hash = "sha256:7cd6e2d7d5a1125f8c26c4f65214f8c942e3f276f98c16cb62ae382c35609f25"},
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]
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[package.extras]
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test = ["coverage (>=4.2)", "flake8 (>=3.0.4)", "path.py (>=11.5.0)", "pytest (>=3.0.3)", "pytest-cov (>=2.4.0)", "pytest-runner (>=2.9)", "pytest-virtualenv (>=1.7.0)", "scikit-build (>=0.10.0)", "setuptools (>=28.0.0)", "virtualenv (>=15.0.3)", "wheel"]
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[[package]]
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name = "colorama"
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version = "0.4.6"
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@ -638,13 +668,13 @@ test-no-images = ["pytest", "pytest-cov", "wurlitzer"]
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[[package]]
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name = "croniter"
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version = "1.3.15"
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version = "1.4.1"
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description = "croniter provides iteration for datetime object with cron like format"
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optional = false
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python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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files = [
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{file = "croniter-1.3.15-py2.py3-none-any.whl", hash = "sha256:f17f877be1d93b9e3191151584a19d8b367b017ab0febc8c5472b9300da61c4c"},
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{file = "croniter-1.3.15.tar.gz", hash = "sha256:924a38fda88f675ec6835667e1d32ac37ff0d65509c2152729d16ff205e32a65"},
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{file = "croniter-1.4.1-py2.py3-none-any.whl", hash = "sha256:9595da48af37ea06ec3a9f899738f1b2c1c13da3c38cea606ef7cd03ea421128"},
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{file = "croniter-1.4.1.tar.gz", hash = "sha256:1a6df60eacec3b7a0aa52a8f2ef251ae3dd2a7c7c8b9874e73e791636d55a361"},
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]
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[package.dependencies]
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@ -760,6 +790,20 @@ files = [
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dnspython = ">=2.0.0"
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idna = ">=2.0.0"
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[[package]]
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name = "exceptiongroup"
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version = "1.1.3"
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description = "Backport of PEP 654 (exception groups)"
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optional = false
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python-versions = ">=3.7"
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files = [
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{file = "exceptiongroup-1.1.3-py3-none-any.whl", hash = "sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3"},
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{file = "exceptiongroup-1.1.3.tar.gz", hash = "sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9"},
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]
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[package.extras]
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test = ["pytest (>=6)"]
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[[package]]
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name = "fastapi"
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version = "0.101.1"
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@ -1463,35 +1507,36 @@ pip = ">=22.3,<23.3"
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[[package]]
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name = "lightning"
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version = "2.0.4"
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description = "Use Lightning Apps to build everything from production-ready, multi-cloud ML systems to simple research demos."
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version = "2.0.7"
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description = "The Deep Learning framework to train, deploy, and ship AI products Lightning fast."
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "lightning-2.0.4-py3-none-any.whl", hash = "sha256:812b3d59d153f4f47db5e4907310412439c5ff2c5899b8413652627372bc9131"},
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{file = "lightning-2.0.4.tar.gz", hash = "sha256:f5f5ed75a657caa8931051590ed000d46bf1b8311ae89bb17a961c3f299dbf33"},
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{file = "lightning-2.0.7-py3-none-any.whl", hash = "sha256:814b371d0715e154b97e3d3108e19d1f96ce1a0f36ef27454f97a3f2f29ac5e7"},
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{file = "lightning-2.0.7.tar.gz", hash = "sha256:f05acd4ba846505d40125b4f9f0bda0804b2b0356e2ad2fd4e4bf7d1c61c8cc6"},
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]
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[package.dependencies]
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arrow = ">=1.2.0,<3.0"
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backoff = ">=2.2.1,<4.0"
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beautifulsoup4 = ">=4.8.0,<6.0"
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click = "<10.0"
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croniter = ">=1.3.0,<1.4.0"
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croniter = ">=1.3.0,<1.5.0"
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dateutils = "<2.0"
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deepdiff = ">=5.7.0,<8.0"
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fastapi = ">=0.92.0,<2.0"
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fsspec = [
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{version = ">=2022.5.0,<2024.0"},
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{version = ">=2022.5.0,<2025.0"},
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{version = ">2021.06.0,<2025.0", extras = ["http"]},
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]
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inquirer = ">=2.10.0,<5.0"
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Jinja2 = "<5.0"
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lightning-cloud = ">=0.5.34"
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lightning-cloud = ">=0.5.37"
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lightning-utilities = ">=0.7.0,<2.0"
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numpy = ">=1.17.2,<3.0"
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packaging = ">=17.1,<25.0"
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psutil = "<7.0"
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pydantic = ">=1.7.4,<4.0"
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pydantic = ">=1.7.4,<2.2.0"
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python-multipart = ">=0.0.5,<2.0"
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pytorch-lightning = "*"
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PyYAML = ">=5.4,<8.0"
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@ -1507,35 +1552,35 @@ typing-extensions = ">=4.0.0,<6.0"
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urllib3 = "<4.0"
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uvicorn = "<2.0"
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websocket-client = "<3.0"
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websockets = "<12.0"
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websockets = "<13.0"
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[package.extras]
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all = ["aiohttp (>=3.8.0,<4.0)", "deepspeed (>=0.8.2,<1.0)", "docker (>=5.0.0,<7.0)", "gym[classic-control] (>=0.17.0,<1.0)", "hydra-core (>=1.0.5,<2.0)", "ipython[all] (<9.0)", "jsonargparse[signatures] (>=4.18.0,<5.0)", "lightning-api-access (>=0.0.3)", "lightning-fabric (>=1.9.0)", "lightning-utilities (>=0.7.0,<1.0)", "lightning-utilities (>=0.8.0,<1.0)", "matplotlib (>3.1,<4.0)", "omegaconf (>=2.0.5,<3.0)", "panel (>=1.0.0,<2.0)", "pytorch-lightning (>=1.9.0)", "redis (>=4.0.1,<5.0)", "rich (>=12.3.0,<14.0)", "s3fs (>=2022.5.0,<2024.0)", "streamlit (>=1.13.0,<2.0)", "tensorboardX (>=2.2,<3.0)", "torchmetrics (>=0.10.0,<1.0)", "torchvision (>=0.12.0,<1.0)"]
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|
||||
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|
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app-cloud = ["docker (>=5.0.0,<7.0)", "redis (>=4.0.1,<5.0)", "s3fs (>=2022.5.0,<2024.0)"]
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|
||||
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|
||||
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|
||||
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||||
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|
||||
app-test = ["coverage (==7.2.7)", "httpx (==0.24.1)", "playwright (==1.36.0)", "psutil (<6.0)", "pympler", "pytest (==7.4.0)", "pytest-asyncio (==0.21.1)", "pytest-cov (==4.1.0)", "pytest-doctestplus (>=0.9.0)", "pytest-rerunfailures (<12.0)", "pytest-timeout (==2.1.0)", "requests-mock (<2.0)", "setuptools (<69.0)", "trio (<0.22.0)"]
|
||||
app-ui = ["panel (>=1.0.0,<2.0)", "streamlit (>=1.13.0,<2.0)"]
|
||||
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||||
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|
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
pytorch-extra = ["hydra-core (>=1.0.5,<2.0)", "jsonargparse[signatures] (>=4.18.0,<4.23.0)", "matplotlib (>3.1,<4.0)", "omegaconf (>=2.0.5,<3.0)", "rich (>=12.3.0,<14.0)", "tensorboardX (>=2.2,<3.0)"]
|
||||
pytorch-strategies = ["deepspeed (>=0.8.2,<1.0)"]
|
||||
pytorch-test = ["cloudpickle (>=1.3,<3.0)", "coverage (==7.2.5)", "fastapi (<1.0)", "onnx (<2.0)", "onnxruntime (<2.0)", "pandas (>1.0,<3.0)", "protobuf (<=3.20.1)", "psutil (<6.0)", "pytest (==7.3.1)", "pytest-cov (==4.0.0)", "pytest-forked (==1.4.0)", "pytest-rerunfailures (==10.3)", "scikit-learn (>0.22.1,<2.0)", "tensorboard (>=2.9.1,<3.0)", "uvicorn (<1.0)"]
|
||||
pytorch-test = ["cloudpickle (>=1.3,<3.0)", "coverage (==7.2.7)", "fastapi (<1.0)", "onnx (<2.0)", "onnxruntime (<2.0)", "pandas (>1.0,<3.0)", "protobuf (<=3.20.1)", "psutil (<6.0)", "pytest (==7.4.0)", "pytest-cov (==4.1.0)", "pytest-forked (==1.4.0)", "pytest-rerunfailures (==10.3)", "scikit-learn (>0.22.1,<2.0)", "tensorboard (>=2.9.1,<3.0)", "uvicorn (<1.0)"]
|
||||
strategies = ["deepspeed (>=0.8.2,<1.0)"]
|
||||
test = ["click (==8.1.3)", "cloudpickle (>=1.3,<3.0)", "coverage (==7.2.5)", "fastapi (<1.0)", "httpx (==0.24.1)", "onnx (<2.0)", "onnxruntime (<2.0)", "pandas (>1.0,<3.0)", "playwright (==1.35.0)", "protobuf (<=3.20.1)", "psutil", "psutil (<6.0)", "pympler", "pytest (==7.3.1)", "pytest-asyncio (==0.21.0)", "pytest-cov (==4.0.0)", "pytest-doctestplus (>=0.9.0)", "pytest-forked (==1.4.0)", "pytest-rerunfailures (<12.0)", "pytest-rerunfailures (==10.3)", "pytest-timeout (==2.1.0)", "requests-mock", "scikit-learn (>0.22.1,<2.0)", "setuptools (<68.0)", "tensorboard (>=2.9.1,<3.0)", "tensorboardX (>=2.2,<3.0)", "trio (<0.22.0)", "uvicorn (<1.0)"]
|
||||
test = ["click (==8.1.6)", "cloudpickle (>=1.3,<3.0)", "coverage (==7.2.7)", "fastapi (<1.0)", "httpx (==0.24.1)", "onnx (<2.0)", "onnxruntime (<2.0)", "pandas (>1.0,<3.0)", "playwright (==1.36.0)", "protobuf (<=3.20.1)", "psutil (<6.0)", "pympler", "pytest (==7.4.0)", "pytest-asyncio (==0.21.1)", "pytest-cov (==4.1.0)", "pytest-doctestplus (>=0.9.0)", "pytest-forked (==1.4.0)", "pytest-rerunfailures (<12.0)", "pytest-rerunfailures (==10.3)", "pytest-timeout (==2.1.0)", "requests-mock (<2.0)", "scikit-learn (>0.22.1,<2.0)", "setuptools (<69.0)", "tensorboard (>=2.9.1,<3.0)", "tensorboardX (>=2.2,<3.0)", "trio (<0.22.0)", "uvicorn (<1.0)"]
|
||||
ui = ["panel (>=1.0.0,<2.0)", "streamlit (>=1.13.0,<2.0)"]
|
||||
|
||||
[[package]]
|
||||
|
@ -1581,6 +1626,16 @@ cli = ["fire"]
|
|||
docs = ["requests (>=2.0.0)"]
|
||||
typing = ["mypy (>=1.0.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "lit"
|
||||
version = "16.0.6"
|
||||
description = "A Software Testing Tool"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "lit-16.0.6.tar.gz", hash = "sha256:84623c9c23b6b14763d637f4e63e6b721b3446ada40bf7001d8fee70b8e77a9a"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "llvmlite"
|
||||
version = "0.40.1"
|
||||
|
@ -1788,6 +1843,17 @@ files = [
|
|||
{file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "more-itertools"
|
||||
version = "10.1.0"
|
||||
description = "More routines for operating on iterables, beyond itertools"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "more-itertools-10.1.0.tar.gz", hash = "sha256:626c369fa0eb37bac0291bce8259b332fd59ac792fa5497b59837309cd5b114a"},
|
||||
{file = "more_itertools-10.1.0-py3-none-any.whl", hash = "sha256:64e0735fcfdc6f3464ea133afe8ea4483b1c5fe3a3d69852e6503b43a0b222e6"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "mpmath"
|
||||
version = "1.3.0"
|
||||
|
@ -2067,6 +2133,33 @@ files = [
|
|||
antlr4-python3-runtime = "==4.9.*"
|
||||
PyYAML = ">=5.1.0"
|
||||
|
||||
[[package]]
|
||||
name = "openai-whisper"
|
||||
version = "20230314"
|
||||
description = "Robust Speech Recognition via Large-Scale Weak Supervision"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = []
|
||||
develop = false
|
||||
|
||||
[package.dependencies]
|
||||
more-itertools = "*"
|
||||
numba = "*"
|
||||
numpy = "*"
|
||||
tiktoken = "0.3.3"
|
||||
torch = "*"
|
||||
tqdm = "*"
|
||||
triton = "2.0.0"
|
||||
|
||||
[package.extras]
|
||||
dev = ["black", "flake8", "isort", "pytest", "scipy"]
|
||||
|
||||
[package.source]
|
||||
type = "git"
|
||||
url = "https://github.com/openai/whisper.git"
|
||||
reference = "HEAD"
|
||||
resolved_reference = "e8622f9afc4eba139bf796c210f5c01081000472"
|
||||
|
||||
[[package]]
|
||||
name = "optuna"
|
||||
version = "3.3.0"
|
||||
|
@ -2588,18 +2681,18 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "pydantic"
|
||||
version = "2.2.1"
|
||||
version = "2.1.1"
|
||||
description = "Data validation using Python type hints"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
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||||
{file = "pydantic-2.2.1-py3-none-any.whl", hash = "sha256:0c88bd2b63ed7a5109c75ab180d55f58f80a4b559682406812d0684d3f4b9192"},
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{file = "pydantic-2.2.1.tar.gz", hash = "sha256:31b5cada74b2320999fb2577e6df80332a200ff92e7775a52448b6b036fce24a"},
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|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
annotated-types = ">=0.4.0"
|
||||
pydantic-core = "2.6.1"
|
||||
pydantic-core = "2.4.0"
|
||||
typing-extensions = ">=4.6.1"
|
||||
|
||||
[package.extras]
|
||||
|
@ -2607,117 +2700,112 @@ email = ["email-validator (>=2.0.0)"]
|
|||
|
||||
[[package]]
|
||||
name = "pydantic-core"
|
||||
version = "2.6.1"
|
||||
version = "2.4.0"
|
||||
description = ""
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||||
optional = false
|
||||
python-versions = ">=3.7"
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||||
files = [
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]
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[package.dependencies]
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|
@ -2993,6 +3081,103 @@ files = [
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|||
[package.dependencies]
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setuptools = ">=41.0"
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[[package]]
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name = "regex"
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version = "2023.8.8"
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description = "Alternative regular expression module, to replace re."
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optional = false
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python-versions = ">=3.6"
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||||
{file = "regex-2023.8.8-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:96979d753b1dc3b2169003e1854dc67bfc86edf93c01e84757927f810b8c3c93"},
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||||
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|
||||
{file = "regex-2023.8.8-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:83215147121e15d5f3a45d99abeed9cf1fe16869d5c233b08c56cdf75f43a504"},
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||||
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|
||||
{file = "regex-2023.8.8-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:f0640913d2c1044d97e30d7c41728195fc37e54d190c5385eacb52115127b882"},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
{file = "regex-2023.8.8-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4b694430b3f00eb02c594ff5a16db30e054c1b9589a043fe9174584c6efa8033"},
|
||||
{file = "regex-2023.8.8-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:b2aeab3895d778155054abea5238d0eb9a72e9242bd4b43f42fd911ef9a13470"},
|
||||
{file = "regex-2023.8.8-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:988631b9d78b546e284478c2ec15c8a85960e262e247b35ca5eaf7ee22f6050a"},
|
||||
{file = "regex-2023.8.8-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:67ecd894e56a0c6108ec5ab1d8fa8418ec0cff45844a855966b875d1039a2e34"},
|
||||
{file = "regex-2023.8.8-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:14898830f0a0eb67cae2bbbc787c1a7d6e34ecc06fbd39d3af5fe29a4468e2c9"},
|
||||
{file = "regex-2023.8.8-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:f2200e00b62568cfd920127782c61bc1c546062a879cdc741cfcc6976668dfcf"},
|
||||
{file = "regex-2023.8.8-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:9691a549c19c22d26a4f3b948071e93517bdf86e41b81d8c6ac8a964bb71e5a6"},
|
||||
{file = "regex-2023.8.8-cp39-cp39-win32.whl", hash = "sha256:6ab2ed84bf0137927846b37e882745a827458689eb969028af8032b1b3dac78e"},
|
||||
{file = "regex-2023.8.8-cp39-cp39-win_amd64.whl", hash = "sha256:5543c055d8ec7801901e1193a51570643d6a6ab8751b1f7dd9af71af467538bb"},
|
||||
{file = "regex-2023.8.8.tar.gz", hash = "sha256:fcbdc5f2b0f1cd0f6a56cdb46fe41d2cce1e644e3b68832f3eeebc5fb0f7712e"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.31.0"
|
||||
|
@ -3628,6 +3813,51 @@ files = [
|
|||
{file = "threadpoolctl-3.2.0.tar.gz", hash = "sha256:c96a0ba3bdddeaca37dc4cc7344aafad41cdb8c313f74fdfe387a867bba93355"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "tiktoken"
|
||||
version = "0.3.3"
|
||||
description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "tiktoken-0.3.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d1f37fa75ba70c1bc7806641e8ccea1fba667d23e6341a1591ea333914c226a9"},
|
||||
{file = "tiktoken-0.3.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3d7296c38392a943c2ccc0b61323086b8550cef08dcf6855de9949890dbc1fd3"},
|
||||
{file = "tiktoken-0.3.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3c84491965e139a905280ac28b74baaa13445b3678e07f96767089ad1ef5ee7b"},
|
||||
{file = "tiktoken-0.3.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65970d77ea85ce6c7fce45131da9258cd58a802ffb29ead8f5552e331c025b2b"},
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||||
{file = "tiktoken-0.3.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:bd3f72d0ba7312c25c1652292121a24c8f1711207b63c6d8dab21afe4be0bf04"},
|
||||
{file = "tiktoken-0.3.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:719c9e13432602dc496b24f13e3c3ad3ec0d2fbdb9aace84abfb95e9c3a425a4"},
|
||||
{file = "tiktoken-0.3.3-cp310-cp310-win_amd64.whl", hash = "sha256:dc00772284c94e65045b984ed7e9f95d000034f6b2411df252011b069bd36217"},
|
||||
{file = "tiktoken-0.3.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4db2c40f79f8f7a21a9fdbf1c6dee32dea77b0d7402355dc584a3083251d2e15"},
|
||||
{file = "tiktoken-0.3.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:e3c0f2231aa3829a1a431a882201dc27858634fd9989898e0f7d991dbc6bcc9d"},
|
||||
{file = "tiktoken-0.3.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:48c13186a479de16cfa2c72bb0631fa9c518350a5b7569e4d77590f7fee96be9"},
|
||||
{file = "tiktoken-0.3.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6674e4e37ab225020135cd66a392589623d5164c6456ba28cc27505abed10d9e"},
|
||||
{file = "tiktoken-0.3.3-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4a0c1357f6191211c544f935d5aa3cb9d7abd118c8f3c7124196d5ecd029b4af"},
|
||||
{file = "tiktoken-0.3.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:2e948d167fc3b04483cbc33426766fd742e7cefe5346cd62b0cbd7279ef59539"},
|
||||
{file = "tiktoken-0.3.3-cp311-cp311-win_amd64.whl", hash = "sha256:5dca434c8680b987eacde2dbc449e9ea4526574dbf9f3d8938665f638095be82"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:984758ebc07cd8c557345697c234f1f221bd730b388f4340dd08dffa50213a01"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:891012f29e159a989541ae47259234fb29ff88c22e1097567316e27ad33a3734"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:210f8602228e4c5d706deeb389da5a152b214966a5aa558eec87b57a1969ced5"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dd783564f80d4dc44ff0a64b13756ded8390ed2548549aefadbe156af9188307"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:03f64bde9b4eb8338bf49c8532bfb4c3578f6a9a6979fc176d939f9e6f68b408"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:1ac369367b6f5e5bd80e8f9a7766ac2a9c65eda2aa856d5f3c556d924ff82986"},
|
||||
{file = "tiktoken-0.3.3-cp38-cp38-win_amd64.whl", hash = "sha256:94600798891f78db780e5aa9321456cf355e54a4719fbd554147a628de1f163f"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:e59db6fca8d5ccea302fe2888917364446d6f4201a25272a1a1c44975c65406a"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:19340d8ba4d6fd729b2e3a096a547ded85f71012843008f97475f9db484869ee"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:542686cbc9225540e3a10f472f82fa2e1bebafce2233a211dee8459e95821cfd"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a43612b2a09f4787c050163a216bf51123851859e9ab128ad03d2729826cde9"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:a11674f0275fa75fb59941b703650998bd4acb295adbd16fc8af17051aaed19d"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:65fc0a449630bab28c30b4adec257442a4706d79cffc2337c1d9df3e91825cdd"},
|
||||
{file = "tiktoken-0.3.3-cp39-cp39-win_amd64.whl", hash = "sha256:0b9a7a9a8b781a50ee9289e85e28771d7e113cc0c656eadfb6fc6d3a106ff9bb"},
|
||||
{file = "tiktoken-0.3.3.tar.gz", hash = "sha256:97b58b7bfda945791ec855e53d166e8ec20c6378942b93851a6c919ddf9d0496"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
regex = ">=2022.1.18"
|
||||
requests = ">=2.26.0"
|
||||
|
||||
[package.extras]
|
||||
blobfile = ["blobfile (>=2)"]
|
||||
|
||||
[[package]]
|
||||
name = "tomli"
|
||||
version = "2.0.1"
|
||||
|
@ -3826,6 +4056,43 @@ files = [
|
|||
docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
|
||||
test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"]
|
||||
|
||||
[[package]]
|
||||
name = "triton"
|
||||
version = "2.0.0"
|
||||
description = "A language and compiler for custom Deep Learning operations"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "triton-2.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:38806ee9663f4b0f7cd64790e96c579374089e58f49aac4a6608121aa55e2505"},
|
||||
{file = "triton-2.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:226941c7b8595219ddef59a1fdb821e8c744289a132415ddd584facedeb475b1"},
|
||||
{file = "triton-2.0.0-1-cp36-cp36m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4c9fc8c89874bc48eb7e7b2107a9b8d2c0bf139778637be5bfccb09191685cfd"},
|
||||
{file = "triton-2.0.0-1-cp37-cp37m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d2684b6a60b9f174f447f36f933e9a45f31db96cb723723ecd2dcfd1c57b778b"},
|
||||
{file = "triton-2.0.0-1-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9d4978298b74fcf59a75fe71e535c092b023088933b2f1df933ec32615e4beef"},
|
||||
{file = "triton-2.0.0-1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:74f118c12b437fb2ca25e1a04759173b517582fcf4c7be11913316c764213656"},
|
||||
{file = "triton-2.0.0-1-pp37-pypy37_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9618815a8da1d9157514f08f855d9e9ff92e329cd81c0305003eb9ec25cc5add"},
|
||||
{file = "triton-2.0.0-1-pp38-pypy38_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:1aca3303629cd3136375b82cb9921727f804e47ebee27b2677fef23005c3851a"},
|
||||
{file = "triton-2.0.0-1-pp39-pypy39_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e3e13aa8b527c9b642e3a9defcc0fbd8ffbe1c80d8ac8c15a01692478dc64d8a"},
|
||||
{file = "triton-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8f05a7e64e4ca0565535e3d5d3405d7e49f9d308505bb7773d21fb26a4c008c2"},
|
||||
{file = "triton-2.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb4b99ca3c6844066e516658541d876c28a5f6e3a852286bbc97ad57134827fd"},
|
||||
{file = "triton-2.0.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47b4d70dc92fb40af553b4460492c31dc7d3a114a979ffb7a5cdedb7eb546c08"},
|
||||
{file = "triton-2.0.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fedce6a381901b1547e0e7e1f2546e4f65dca6d91e2d8a7305a2d1f5551895be"},
|
||||
{file = "triton-2.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75834f27926eab6c7f00ce73aaf1ab5bfb9bec6eb57ab7c0bfc0a23fac803b4c"},
|
||||
{file = "triton-2.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0117722f8c2b579cd429e0bee80f7731ae05f63fe8e9414acd9a679885fcbf42"},
|
||||
{file = "triton-2.0.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bcd9be5d0c2e45d2b7e6ddc6da20112b6862d69741576f9c3dbaf941d745ecae"},
|
||||
{file = "triton-2.0.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:42a0d2c3fc2eab4ba71384f2e785fbfd47aa41ae05fa58bf12cb31dcbd0aeceb"},
|
||||
{file = "triton-2.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:52c47b72c72693198163ece9d90a721299e4fb3b8e24fd13141e384ad952724f"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
cmake = "*"
|
||||
filelock = "*"
|
||||
lit = "*"
|
||||
torch = "*"
|
||||
|
||||
[package.extras]
|
||||
tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)"]
|
||||
tutorials = ["matplotlib", "pandas", "tabulate"]
|
||||
|
||||
[[package]]
|
||||
name = "typer"
|
||||
version = "0.9.0"
|
||||
|
@ -3976,6 +4243,7 @@ h11 = ">=0.8"
|
|||
httptools = {version = ">=0.5.0", optional = true, markers = "extra == \"standard\""}
|
||||
python-dotenv = {version = ">=0.13", optional = true, markers = "extra == \"standard\""}
|
||||
pyyaml = {version = ">=5.1", optional = true, markers = "extra == \"standard\""}
|
||||
typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
|
||||
uvloop = {version = ">=0.14.0,<0.15.0 || >0.15.0,<0.15.1 || >0.15.1", optional = true, markers = "(sys_platform != \"win32\" and sys_platform != \"cygwin\") and platform_python_implementation != \"PyPy\" and extra == \"standard\""}
|
||||
watchfiles = {version = ">=0.13", optional = true, markers = "extra == \"standard\""}
|
||||
websockets = {version = ">=10.4", optional = true, markers = "extra == \"standard\""}
|
||||
|
@ -4074,17 +4342,17 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "websocket-client"
|
||||
version = "1.6.1"
|
||||
version = "1.6.2"
|
||||
description = "WebSocket client for Python with low level API options"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "websocket-client-1.6.1.tar.gz", hash = "sha256:c951af98631d24f8df89ab1019fc365f2227c0892f12fd150e935607c79dd0dd"},
|
||||
{file = "websocket_client-1.6.1-py3-none-any.whl", hash = "sha256:f1f9f2ad5291f0225a49efad77abf9e700b6fef553900623060dad6e26503b9d"},
|
||||
{file = "websocket-client-1.6.2.tar.gz", hash = "sha256:53e95c826bf800c4c465f50093a8c4ff091c7327023b10bfaff40cf1ef170eaa"},
|
||||
{file = "websocket_client-1.6.2-py3-none-any.whl", hash = "sha256:ce54f419dfae71f4bdba69ebe65bf7f0a93fe71bc009ad3a010aacc3eebad537"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"]
|
||||
docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
|
||||
optional = ["python-socks", "wsaccel"]
|
||||
test = ["websockets"]
|
||||
|
||||
|
@ -4256,5 +4524,5 @@ multidict = ">=4.0"
|
|||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.11"
|
||||
content-hash = "abe4e81cd59988f91e16746d9cc05c4d4f49c53957a682d03356ce2270950661"
|
||||
python-versions = "^3.10"
|
||||
content-hash = "78450781b9a79630d7889c4c7561068d194f35d1ed5f90455ad2eb4fc4a937a2"
|
||||
|
|
|
@ -15,7 +15,7 @@ pydub = "^0.25.1"
|
|||
light-the-torch = "^0.7.5"
|
||||
hmmlearn = {git = "https://github.com/hmmlearn/hmmlearn.git"}
|
||||
pyannote-audio = {git = "https://github.com/pyannote/pyannote-audio.git", rev = "develop"}
|
||||
#openai-whisper = { git = "https://github.com/openai/whisper.git" }
|
||||
openai-whisper = { git = "https://github.com/openai/whisper.git" }
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
|
|
|
@ -1,11 +1,12 @@
|
|||
import locale
|
||||
from pathlib import Path
|
||||
# from whisper import Whisper
|
||||
from whisper import Whisper, load_model
|
||||
from pyannote.audio import Pipeline
|
||||
import torch
|
||||
import static_ffmpeg
|
||||
import file_operations
|
||||
|
||||
|
||||
def prep() -> None:
|
||||
locale.getpreferredencoding = lambda: "UTF-8"
|
||||
# download and add ffmpeg to env
|
||||
|
@ -26,8 +27,8 @@ def diarization(access_token: str | None) -> Pipeline:
|
|||
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
|
||||
return pipeline.to(device)
|
||||
|
||||
#
|
||||
# def whisper() -> Whisper:
|
||||
# # LOAD MODEL INTO VRAM
|
||||
# device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
|
||||
# return whisper.load_model("large", device=device)
|
||||
|
||||
def whispermodel() -> Whisper:
|
||||
# LOAD MODEL INTO VRAM
|
||||
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
|
||||
return load_model("large", device=device)
|
||||
|
|
|
@ -4,7 +4,7 @@ import json
|
|||
from pathlib import Path
|
||||
from pyannote.audio import Pipeline
|
||||
from pydub import AudioSegment
|
||||
# from whisper import Whisper
|
||||
from whisper import Whisper
|
||||
|
||||
MILLISECONDS_TO_SPACE = 2000
|
||||
|
||||
|
@ -25,22 +25,53 @@ def diarize(audiofile: Path, pipeline: Pipeline, output_path: Path) -> Path:
|
|||
return out_file
|
||||
|
||||
|
||||
# def transcribe(
|
||||
# model: Whisper,
|
||||
# diarized_groups: list,
|
||||
# output_path: Path,
|
||||
# lang: str = "en",
|
||||
# word_timestamps: bool = True,
|
||||
# ):
|
||||
# for i in range(len(diarized_groups)):
|
||||
# f = {Path.joinpath(output_path, str(i))}
|
||||
# audio_f = f"{f}.wav"
|
||||
# json_f = f"{f}.json"
|
||||
# result = model.transcribe(
|
||||
# audio=audio_f, language=lang, word_timestamps=word_timestamps
|
||||
# )
|
||||
# with open(json_f, "w") as outfile:
|
||||
# json.dump(result, outfile, indent=4)
|
||||
def transcribe(
|
||||
model: Whisper,
|
||||
diarized_groups: list,
|
||||
output_path: Path,
|
||||
lang: str = "en",
|
||||
word_timestamps: bool = True,
|
||||
) -> None:
|
||||
for i in range(len(diarized_groups)):
|
||||
f = {Path.joinpath(output_path, str(i))}
|
||||
audio_f = f"{f}.wav"
|
||||
json_f = f"{f}.json"
|
||||
result = model.transcribe(
|
||||
audio=audio_f, language=lang, word_timestamps=word_timestamps
|
||||
)
|
||||
with open(json_f, "w") as outfile:
|
||||
json.dump(result, outfile, indent=4)
|
||||
|
||||
|
||||
# TODO clean up this mess
|
||||
def output_txt(diarized_groups: list, transcription_path: Path) -> str:
|
||||
txt = list("")
|
||||
gidx = -1
|
||||
for g in diarized_groups:
|
||||
shift = re.findall(r"[0-9]+:[0-9]+:[0-9]+\.[0-9]+", string=g[0])[0]
|
||||
shift = (
|
||||
_millisec(shift) - MILLISECONDS_TO_SPACE
|
||||
) # the start time in the original video
|
||||
shift = max(shift, 0)
|
||||
|
||||
gidx += 1
|
||||
|
||||
with open(f"{Path.joinpath(transcription_path, str(gidx))}.json") as f:
|
||||
captions = json.load(f)["segments"]
|
||||
|
||||
if captions:
|
||||
speaker = g[0].split()[-1]
|
||||
|
||||
for c in captions:
|
||||
txt.append(f"[{speaker}] {c['text']}\n")
|
||||
txt.append("\n")
|
||||
|
||||
output = "".join(txt)
|
||||
with open(
|
||||
Path.joinpath(transcription_path, "capspeaker.txt"), "w", encoding="utf-8"
|
||||
) as file:
|
||||
file.write(output)
|
||||
return output
|
||||
|
||||
|
||||
def save_diarized_audio_files(
|
||||
|
|
|
@ -16,12 +16,14 @@ access_token: str = os.environ.get("VERBANOTE_HF_TOKEN", "")
|
|||
|
||||
loaders.prep()
|
||||
diarize_pipeline = loaders.diarization(access_token)
|
||||
# whisper_model = loaders.whisper()
|
||||
whisper_model = loaders.whispermodel()
|
||||
|
||||
|
||||
def handler(job):
|
||||
input: dict = job["input"]
|
||||
url: str | None = input.get("url")
|
||||
lang: str | None = input.get("lang")
|
||||
word_timestamps: str | None = input.get("word_timestamps")
|
||||
|
||||
if not url:
|
||||
return {"error": "no file link provided"}
|
||||
|
@ -35,17 +37,21 @@ def handler(job):
|
|||
diarized_groups = process.save_diarized_audio_files(
|
||||
diarized, audiofile, output_path
|
||||
)
|
||||
uploaded_file: str = file_operations.upload_to_oxo(file=diarized, expires=1)
|
||||
# process.transcribe(
|
||||
# model=whisper_model, diarized_groups=diarized_groups, output_path=output_path
|
||||
# )
|
||||
uploaded_diarization: str = file_operations.upload_to_oxo(file=diarized, expires=1)
|
||||
process.transcribe(
|
||||
model=whisper_model,
|
||||
diarized_groups=diarized_groups,
|
||||
output_path=output_path,
|
||||
lang=lang or "fr",
|
||||
word_timestamps=word_timestamps or True,
|
||||
)
|
||||
transcription = process.output_txt(diarized_groups, output_path)
|
||||
|
||||
return {
|
||||
"speaker_timings": "s3-address-to-speakers",
|
||||
"transcription_text": "s3-address-to-transcription",
|
||||
"transcription_page": "web-address-to-deployment",
|
||||
"audiofile_path": str(audiofile),
|
||||
"audio_url": uploaded_file,
|
||||
"audiofile": str(audiofile),
|
||||
"diarization_url": uploaded_diarization,
|
||||
"diarization": diarized_groups,
|
||||
"transcription_text": transcription,
|
||||
}
|
||||
|
||||
|
||||
|
|
Loading…
Reference in a new issue