# This file was autogenerated by uv via the following command:
#    uv pip compile requirements/test/cuda.in -c requirements/cuda.txt -o requirements/test/cuda.txt --index-strategy unsafe-best-match --torch-backend cu130 --python-platform x86_64-manylinux_2_28 --python-version 3.12
absl-py==2.1.0
    # via rouge-score
accelerate==1.13.0
    # via peft
aiohappyeyeballs==2.6.1
    # via aiohttp
aiohttp==3.13.3
    # via
    #   -c requirements/common.txt
    #   aiohttp-cors
    #   datasets
    #   fsspec
    #   gpt-oss
    #   lm-eval
    #   ray
aiohttp-cors==0.8.1
    # via ray
aiosignal==1.4.0
    # via aiohttp
albumentations==1.4.6
    # via -r requirements/test/cuda.in
alembic==1.16.4
    # via optuna
annotated-doc==0.0.4
    # via fastapi
annotated-types==0.7.0
    # via pydantic
anyio==4.6.2.post1
    # via
    #   httpx
    #   starlette
arctic-inference==0.1.1
    # via -r requirements/test/cuda.in
argcomplete==3.5.1
    # via datamodel-code-generator
arrow==1.3.0
    # via isoduration
attrs==24.2.0
    # via
    #   aiohttp
    #   hypothesis
    #   jsonschema
    #   pytest-subtests
    #   referencing
audioread==3.0.1
    # via librosa
av==16.1.0
    # via -r requirements/test/cuda.in
azure-core==1.38.2
    # via
    #   azure-identity
    #   azure-storage-blob
azure-identity==1.25.2
    # via runai-model-streamer-azure
azure-storage-blob==12.28.0
    # via runai-model-streamer-azure
backoff==2.2.1
    # via
    #   -r requirements/test/cuda.in
    #   schemathesis
bitsandbytes==0.49.2
    # via -r requirements/test/cuda.in
black==24.10.0
    # via datamodel-code-generator
blobfile==3.0.0
    # via -r requirements/test/cuda.in
bm25s==0.2.13
    # via mteb
boto3==1.35.57
    # via
    #   runai-model-streamer-s3
    #   tensorizer
botocore==1.35.57
    # via
    #   boto3
    #   s3transfer
bounded-pool-executor==0.0.3
    # via pqdm
buildkite-test-collector==0.1.9
    # via -r requirements/test/cuda.in
cachetools==5.5.2
    # via google-auth
certifi==2024.8.30
    # via
    #   httpcore
    #   httpx
    #   requests
cffi==2.0.0
    # via
    #   cryptography
    #   soundfile
chardet==5.2.0
    # via mbstrdecoder
charset-normalizer==3.4.0
    # via requests
chz==0.3.0
    # via gpt-oss
click==8.1.7
    # via
    #   black
    #   jiwer
    #   nltk
    #   ray
    #   schemathesis
    #   typer
    #   uvicorn
colorama==0.4.6
    # via
    #   perceptron
    #   sacrebleu
    #   schemathesis
colorful==0.5.6
    # via ray
colorlog==6.10.1
    # via optuna
contourpy==1.3.0
    # via matplotlib
coverage==7.10.6
    # via pytest-cov
cramjam==2.9.0
    # via fastparquet
cryptography==46.0.5
    # via
    #   azure-identity
    #   azure-storage-blob
    #   msal
    #   pyjwt
cuda-bindings==13.0.3
    # via torch
cuda-pathfinder==1.3.3
    # via cuda-bindings
cuda-toolkit==13.0.2
    # via torch
cupy-cuda12x==13.6.0
    # via ray
cycler==0.12.1
    # via matplotlib
datamodel-code-generator==0.26.3
    # via -r requirements/test/cuda.in
dataproperty==1.0.1
    # via
    #   pytablewriter
    #   tabledata
datasets==3.3.0
    # via
    #   -r requirements/test/cuda.in
    #   evaluate
    #   lm-eval
    #   mteb
decorator==5.1.1
    # via librosa
decord==0.6.0
    # via -r requirements/test/cuda.in
dill==0.3.8
    # via
    #   datasets
    #   evaluate
    #   lm-eval
    #   multiprocess
distlib==0.3.9
    # via virtualenv
dnspython==2.7.0
    # via email-validator
docker==7.1.0
    # via gpt-oss
docopt==0.6.2
    # via num2words
einops==0.8.1
    # via
    #   -r requirements/test/cuda.in
    #   encodec
    #   vector-quantize-pytorch
    #   vocos
einx==0.3.0
    # via vector-quantize-pytorch
email-validator==2.2.0
    # via pydantic
encodec==0.1.1
    # via vocos
et-xmlfile==2.0.0
    # via openpyxl
evaluate==0.4.3
    # via lm-eval
fastapi==0.128.0
    # via
    #   -c requirements/common.txt
    #   gpt-oss
fastparquet==2024.11.0
    # via genai-perf
fastrlock==0.8.2
    # via cupy-cuda12x
fastsafetensors==0.2.2
    # via
    #   -c requirements/cuda.txt
    #   -r requirements/test/cuda.in
filelock==3.16.1
    # via
    #   -c requirements/common.txt
    #   blobfile
    #   datasets
    #   huggingface-hub
    #   ray
    #   torch
    #   virtualenv
fonttools==4.55.0
    # via matplotlib
fqdn==1.5.1
    # via jsonschema
frozendict==2.4.6
    # via einx
frozenlist==1.5.0
    # via
    #   aiohttp
    #   aiosignal
fsspec==2024.12.0
    # via
    #   datasets
    #   evaluate
    #   fastparquet
    #   huggingface-hub
    #   torch
ftfy==6.3.1
    # via open-clip-torch
genai-perf==0.0.16
    # via -r requirements/test/cuda.in
genson==1.3.0
    # via datamodel-code-generator
google-api-core==2.24.2
    # via
    #   google-cloud-core
    #   google-cloud-storage
    #   opencensus
google-auth==2.40.2
    # via
    #   google-api-core
    #   google-cloud-core
    #   google-cloud-storage
    #   runai-model-streamer-gcs
google-cloud-core==2.4.3
    # via google-cloud-storage
google-cloud-storage==3.4.0
    # via runai-model-streamer-gcs
google-crc32c==1.7.1
    # via
    #   google-cloud-storage
    #   google-resumable-media
google-resumable-media==2.7.2
    # via google-cloud-storage
googleapis-common-protos==1.70.0
    # via google-api-core
gpt-oss==0.0.8
    # via -r requirements/test/cuda.in
graphql-core==3.2.6
    # via hypothesis-graphql
greenlet==3.2.3
    # via sqlalchemy
grpcio==1.78.0
    # via
    #   -r requirements/test/cuda.in
    #   grpcio-reflection
    #   ray
grpcio-reflection==1.78.0
    # via -r requirements/test/cuda.in
h11==0.14.0
    # via
    #   httpcore
    #   uvicorn
h2==4.3.0
    # via httpx
harfile==0.3.0
    # via schemathesis
hf-xet==1.4.3
    # via huggingface-hub
hiredis==3.0.0
    # via tensorizer
hpack==4.1.0
    # via h2
html2text==2025.4.15
    # via gpt-oss
httpcore==1.0.6
    # via httpx
httpx==0.27.2
    # via
    #   -r requirements/test/cuda.in
    #   huggingface-hub
    #   perceptron
    #   schemathesis
huggingface-hub==1.10.2
    # via
    #   accelerate
    #   datasets
    #   evaluate
    #   open-clip-torch
    #   peft
    #   segmentation-models-pytorch
    #   sentence-transformers
    #   timm
    #   tokenizers
    #   transformers
    #   vocos
humanize==4.11.0
    # via runai-model-streamer
hyperframe==6.1.0
    # via h2
hypothesis==6.131.0
    # via
    #   hypothesis-graphql
    #   hypothesis-jsonschema
    #   schemathesis
hypothesis-graphql==0.11.1
    # via schemathesis
hypothesis-jsonschema==0.23.1
    # via schemathesis
idna==3.10
    # via
    #   anyio
    #   email-validator
    #   httpx
    #   jsonschema
    #   requests
    #   yarl
imagehash==4.3.2
    # via -r requirements/test/cuda.in
imageio==2.37.0
    # via scikit-image
importlib-metadata==8.7.0
    # via opentelemetry-api
inflect==5.6.2
    # via datamodel-code-generator
iniconfig==2.0.0
    # via pytest
instanttensor==0.1.5
    # via -r requirements/test/cuda.in
isodate==0.7.2
    # via azure-storage-blob
isoduration==20.11.0
    # via jsonschema
isort==5.13.2
    # via datamodel-code-generator
jinja2==3.1.6
    # via
    #   datamodel-code-generator
    #   genai-perf
    #   lm-eval
    #   torch
jiwer==3.0.5
    # via -r requirements/test/cuda.in
jmespath==1.0.1
    # via
    #   boto3
    #   botocore
joblib==1.4.2
    # via
    #   librosa
    #   nltk
    #   scikit-learn
jsonpointer==3.0.0
    # via jsonschema
jsonschema==4.23.0
    # via
    #   hypothesis-jsonschema
    #   mistral-common
    #   ray
    #   schemathesis
jsonschema-specifications==2024.10.1
    # via jsonschema
junit-xml==1.9
    # via schemathesis
kaldi-native-fbank==1.22.3
    # via -r requirements/test/cuda.in
kaleido==0.2.1
    # via genai-perf
kiwisolver==1.4.7
    # via matplotlib
lazy-loader==0.4
    # via
    #   librosa
    #   scikit-image
libnacl==2.1.0
    # via tensorizer
librosa==0.10.2.post1
    # via -r requirements/test/cuda.in
llvmlite==0.47.0
    # via numba
lm-eval==0.4.12
    # via -r requirements/test/cuda.in
lxml==5.3.0
    # via
    #   blobfile
    #   gpt-oss
    #   sacrebleu
mako==1.3.10
    # via alembic
markdown-it-py==3.0.0
    # via rich
markupsafe==3.0.1
    # via
    #   jinja2
    #   mako
    #   werkzeug
matplotlib==3.9.2
    # via -r requirements/test/cuda.in
mbstrdecoder==1.1.3
    # via
    #   dataproperty
    #   pytablewriter
    #   typepy
mdurl==0.1.2
    # via markdown-it-py
mistral-common==1.11.2
    # via
    #   -c requirements/common.txt
    #   -r requirements/test/cuda.in
more-itertools==10.5.0
    # via lm-eval
mpmath==1.3.0
    # via sympy
msal==1.34.0
    # via
    #   azure-identity
    #   msal-extensions
msal-extensions==1.3.1
    # via azure-identity
msgpack==1.1.0
    # via
    #   librosa
    #   ray
mteb==2.8.3
    # via -r requirements/test/cuda.in
multidict==6.1.0
    # via
    #   aiohttp
    #   yarl
multiprocess==0.70.16
    # via
    #   datasets
    #   evaluate
mypy-extensions==1.0.0
    # via black
networkx==3.2.1
    # via
    #   scikit-image
    #   torch
nltk==3.9.1
    # via rouge-score
num2words==0.5.14
    # via -r requirements/test/cuda.in
numba==0.65.0
    # via
    #   -c requirements/cuda.txt
    #   -r requirements/test/cuda.in
    #   librosa
numpy==2.2.6
    # via
    #   -r requirements/test/cuda.in
    #   accelerate
    #   albumentations
    #   bitsandbytes
    #   bm25s
    #   contourpy
    #   cupy-cuda12x
    #   datasets
    #   decord
    #   einx
    #   encodec
    #   evaluate
    #   fastparquet
    #   genai-perf
    #   imagehash
    #   imageio
    #   librosa
    #   lm-eval
    #   matplotlib
    #   mistral-common
    #   mteb
    #   numba
    #   opencv-python-headless
    #   optuna
    #   pandas
    #   patsy
    #   peft
    #   perceptron
    #   pywavelets
    #   rouge-score
    #   runai-model-streamer
    #   sacrebleu
    #   scikit-image
    #   scikit-learn
    #   scipy
    #   segmentation-models-pytorch
    #   soxr
    #   statsmodels
    #   tensorizer
    #   tifffile
    #   torchvision
    #   transformers
    #   tritonclient
    #   vocos
nvidia-cublas==13.1.0.3
    # via
    #   cuda-toolkit
    #   nvidia-cudnn-cu13
    #   nvidia-cusolver
nvidia-cuda-cupti==13.0.85
    # via cuda-toolkit
nvidia-cuda-nvrtc==13.0.88
    # via cuda-toolkit
nvidia-cuda-runtime==13.0.96
    # via cuda-toolkit
nvidia-cudnn-cu13==9.19.0.56
    # via torch
nvidia-cufft==12.0.0.61
    # via cuda-toolkit
nvidia-cufile==1.15.1.6
    # via cuda-toolkit
nvidia-curand==10.4.0.35
    # via cuda-toolkit
nvidia-cusolver==12.0.4.66
    # via cuda-toolkit
nvidia-cusparse==12.6.3.3
    # via
    #   cuda-toolkit
    #   nvidia-cusolver
nvidia-cusparselt-cu13==0.8.0
    # via torch
nvidia-nccl-cu13==2.28.9
    # via torch
nvidia-nvjitlink==13.0.88
    # via
    #   cuda-toolkit
    #   nvidia-cufft
    #   nvidia-cusolver
    #   nvidia-cusparse
nvidia-nvshmem-cu13==3.4.5
    # via torch
nvidia-nvtx==13.0.85
    # via cuda-toolkit
open-clip-torch==2.32.0
    # via -r requirements/test/cuda.in
openai-harmony==0.0.4
    # via
    #   -c requirements/common.txt
    #   gpt-oss
opencensus==0.11.4
    # via ray
opencensus-context==0.1.3
    # via opencensus
opencv-python-headless==4.13.0.90
    # via
    #   -c requirements/common.txt
    #   -r requirements/test/cuda.in
    #   albumentations
    #   mistral-common
openpyxl==3.1.5
    # via -r requirements/test/cuda.in
opentelemetry-api==1.35.0
    # via
    #   -c requirements/common.txt
    #   opentelemetry-exporter-prometheus
    #   opentelemetry-sdk
    #   opentelemetry-semantic-conventions
opentelemetry-exporter-prometheus==0.56b0
    # via ray
opentelemetry-proto==1.35.0
    # via ray
opentelemetry-sdk==1.35.0
    # via
    #   -c requirements/common.txt
    #   opentelemetry-exporter-prometheus
    #   ray
opentelemetry-semantic-conventions==0.56b0
    # via opentelemetry-sdk
optuna==3.6.1
    # via genai-perf
orjson==3.11.5
    # via genai-perf
packaging==24.2
    # via
    #   accelerate
    #   bitsandbytes
    #   black
    #   datamodel-code-generator
    #   datasets
    #   evaluate
    #   fastparquet
    #   huggingface-hub
    #   lazy-loader
    #   matplotlib
    #   optuna
    #   peft
    #   plotly
    #   pooch
    #   pytest
    #   pytest-rerunfailures
    #   ray
    #   scikit-image
    #   statsmodels
    #   transformers
    #   typepy
pandas==2.2.3
    # via
    #   datasets
    #   evaluate
    #   fastparquet
    #   genai-perf
    #   statsmodels
pathspec==0.12.1
    # via black
pathvalidate==3.2.1
    # via pytablewriter
patsy==1.0.1
    # via statsmodels
peft==0.18.1
    # via -r requirements/test/cuda.in
perceptron==0.1.4
    # via -r requirements/test/cuda.in
perf-analyzer==0.1.0
    # via genai-perf
pillow==10.4.0
    # via
    #   genai-perf
    #   imagehash
    #   imageio
    #   matplotlib
    #   mistral-common
    #   perceptron
    #   scikit-image
    #   segmentation-models-pytorch
    #   torchvision
platformdirs==4.3.6
    # via
    #   black
    #   pooch
    #   virtualenv
plotly==5.24.1
    # via
    #   -r requirements/test/cuda.in
    #   genai-perf
pluggy==1.5.0
    # via
    #   pytest
    #   pytest-cov
polars==1.29.0
    # via mteb
pooch==1.8.2
    # via librosa
portalocker==2.10.1
    # via sacrebleu
pqdm==0.2.0
    # via -r requirements/test/cuda.in
prometheus-client==0.22.0
    # via
    #   -c requirements/common.txt
    #   opentelemetry-exporter-prometheus
    #   ray
propcache==0.2.0
    # via
    #   aiohttp
    #   yarl
proto-plus==1.26.1
    # via google-api-core
protobuf==6.33.6
    # via
    #   -c requirements/common.txt
    #   google-api-core
    #   googleapis-common-protos
    #   grpcio-reflection
    #   opentelemetry-proto
    #   proto-plus
    #   ray
    #   tensorizer
psutil==6.1.0
    # via
    #   accelerate
    #   peft
    #   tensorizer
py==1.11.0
    # via pytest-forked
py-spy==0.4.0
    # via ray
pyarrow==23.0.0
    # via
    #   datasets
    #   genai-perf
pyasn1==0.6.1
    # via
    #   pyasn1-modules
    #   rsa
pyasn1-modules==0.4.2
    # via google-auth
pycountry==24.6.1
    # via pydantic-extra-types
pycparser==2.22
    # via cffi
pycryptodomex==3.22.0
    # via blobfile
pydantic==2.12.0
    # via
    #   -c requirements/common.txt
    #   -r requirements/test/cuda.in
    #   albumentations
    #   datamodel-code-generator
    #   fastapi
    #   gpt-oss
    #   mistral-common
    #   mteb
    #   openai-harmony
    #   pydantic-extra-types
    #   ray
pydantic-core==2.41.1
    # via pydantic
pydantic-extra-types==2.10.5
    # via mistral-common
pygments==2.18.0
    # via rich
pyjwt==2.11.0
    # via msal
pyparsing==3.2.0
    # via matplotlib
pyrate-limiter==3.7.0
    # via schemathesis
pystemmer==3.0.0
    # via mteb
pytablewriter==1.2.0
    # via lm-eval
pytest==8.3.5
    # via
    #   -r requirements/test/cuda.in
    #   buildkite-test-collector
    #   genai-perf
    #   pytest-asyncio
    #   pytest-cov
    #   pytest-forked
    #   pytest-mock
    #   pytest-rerunfailures
    #   pytest-shard
    #   pytest-subtests
    #   pytest-timeout
    #   schemathesis
pytest-asyncio==0.24.0
    # via -r requirements/test/cuda.in
pytest-cov==6.3.0
    # via -r requirements/test/cuda.in
pytest-forked==1.6.0
    # via -r requirements/test/cuda.in
pytest-mock==3.14.0
    # via genai-perf
pytest-rerunfailures==14.0
    # via -r requirements/test/cuda.in
pytest-shard==0.1.2
    # via -r requirements/test/cuda.in
pytest-subtests==0.14.1
    # via schemathesis
pytest-timeout==2.3.1
    # via -r requirements/test/cuda.in
python-dateutil==2.9.0.post0
    # via
    #   arrow
    #   botocore
    #   matplotlib
    #   pandas
    #   typepy
python-rapidjson==1.20
    # via tritonclient
pytrec-eval-terrier==0.5.7
    # via mteb
pytz==2024.2
    # via
    #   pandas
    #   typepy
pywavelets==1.9.0
    # via imagehash
pyyaml==6.0.2
    # via
    #   accelerate
    #   albumentations
    #   datamodel-code-generator
    #   datasets
    #   genai-perf
    #   huggingface-hub
    #   optuna
    #   peft
    #   ray
    #   responses
    #   schemathesis
    #   timm
    #   transformers
    #   vocos
rapidfuzz==3.12.1
    # via jiwer
ray==2.48.0
    # via -r requirements/test/cuda.in
redis==5.2.0
    # via tensorizer
referencing==0.35.1
    # via
    #   jsonschema
    #   jsonschema-specifications
regex==2026.2.28
    # via
    #   nltk
    #   open-clip-torch
    #   sacrebleu
    #   tiktoken
    #   transformers
requests==2.32.3
    # via
    #   -c requirements/common.txt
    #   azure-core
    #   buildkite-test-collector
    #   datasets
    #   docker
    #   evaluate
    #   google-api-core
    #   google-cloud-storage
    #   gpt-oss
    #   lm-eval
    #   mistral-common
    #   msal
    #   mteb
    #   pooch
    #   ray
    #   responses
    #   schemathesis
    #   starlette-testclient
    #   tiktoken
responses==0.25.3
    # via genai-perf
rfc3339-validator==0.1.4
    # via jsonschema
rfc3987==1.3.8
    # via jsonschema
rich==13.9.4
    # via
    #   genai-perf
    #   mteb
    #   perceptron
    #   typer
rouge-score==0.1.2
    # via lm-eval
rpds-py==0.20.1
    # via
    #   jsonschema
    #   referencing
rsa==4.9.1
    # via google-auth
runai-model-streamer==0.15.7
    # via -r requirements/test/cuda.in
runai-model-streamer-azure==0.15.7
    # via runai-model-streamer
runai-model-streamer-gcs==0.15.7
    # via runai-model-streamer
runai-model-streamer-s3==0.15.7
    # via runai-model-streamer
s3transfer==0.10.3
    # via boto3
sacrebleu==2.4.3
    # via lm-eval
safetensors==0.7.0
    # via
    #   -c requirements/common.txt
    #   accelerate
    #   open-clip-torch
    #   peft
    #   segmentation-models-pytorch
    #   timm
    #   transformers
schemathesis==3.39.15
    # via -r requirements/test/cuda.in
scikit-image==0.25.2
    # via albumentations
scikit-learn==1.5.2
    # via
    #   albumentations
    #   librosa
    #   lm-eval
    #   mteb
    #   sentence-transformers
scipy==1.13.1
    # via
    #   albumentations
    #   bm25s
    #   imagehash
    #   librosa
    #   mteb
    #   scikit-image
    #   scikit-learn
    #   sentence-transformers
    #   statsmodels
    #   vocos
segmentation-models-pytorch==0.5.0
    # via -r requirements/test/cuda.in
sentence-transformers==5.2.0
    # via
    #   -r requirements/test/cuda.in
    #   mteb
setuptools==77.0.3
    # via
    #   -c requirements/common.txt
    #   pytablewriter
    #   torch
shellingham==1.5.4
    # via
    #   perceptron
    #   typer
six==1.16.0
    # via
    #   -c requirements/common.txt
    #   junit-xml
    #   opencensus
    #   python-dateutil
    #   rfc3339-validator
    #   rouge-score
smart-open==7.1.0
    # via ray
sniffio==1.3.1
    # via
    #   anyio
    #   httpx
sortedcontainers==2.4.0
    # via hypothesis
soundfile==0.12.1
    # via
    #   -r requirements/test/cuda.in
    #   genai-perf
    #   librosa
    #   mistral-common
soxr==0.5.0.post1
    # via
    #   librosa
    #   mistral-common
sqlalchemy==2.0.41
    # via
    #   alembic
    #   optuna
sqlitedict==2.1.0
    # via lm-eval
starlette==0.50.0
    # via
    #   fastapi
    #   schemathesis
    #   starlette-testclient
starlette-testclient==0.4.1
    # via schemathesis
statsmodels==0.14.4
    # via genai-perf
structlog==25.4.0
    # via gpt-oss
sympy==1.13.3
    # via
    #   einx
    #   torch
tabledata==1.3.3
    # via pytablewriter
tabulate==0.9.0
    # via sacrebleu
tblib==3.1.0
    # via -r requirements/test/cuda.in
tcolorpy==0.1.6
    # via pytablewriter
tenacity==9.1.2
    # via
    #   gpt-oss
    #   lm-eval
    #   plotly
tensorizer==2.10.1
    # via -r requirements/test/cuda.in
termcolor==3.1.0
    # via gpt-oss
threadpoolctl==3.5.0
    # via scikit-learn
tifffile==2025.3.30
    # via scikit-image
tiktoken==0.12.0
    # via
    #   -c requirements/common.txt
    #   gpt-oss
    #   lm-eval
    #   mistral-common
timm==1.0.17
    # via
    #   -r requirements/test/cuda.in
    #   open-clip-torch
    #   segmentation-models-pytorch
tokenizers==0.22.2
    # via
    #   -c requirements/common.txt
    #   -r requirements/test/cuda.in
    #   transformers
tomli==2.2.1
    # via schemathesis
tomli-w==1.2.0
    # via schemathesis
torch==2.11.0+cu130
    # via
    #   -c requirements/cuda.txt
    #   -r requirements/test/cuda.in
    #   accelerate
    #   bitsandbytes
    #   encodec
    #   instanttensor
    #   mteb
    #   open-clip-torch
    #   peft
    #   runai-model-streamer
    #   segmentation-models-pytorch
    #   sentence-transformers
    #   tensorizer
    #   timm
    #   torchvision
    #   vector-quantize-pytorch
    #   vocos
torchaudio==2.11.0+cu130
    # via
    #   -c requirements/cuda.txt
    #   -r requirements/test/cuda.in
    #   encodec
    #   vocos
torchvision==0.26.0+cu130
    # via
    #   -c requirements/cuda.txt
    #   -r requirements/test/cuda.in
    #   open-clip-torch
    #   segmentation-models-pytorch
    #   timm
tqdm==4.67.3
    # via
    #   datasets
    #   evaluate
    #   huggingface-hub
    #   lm-eval
    #   mteb
    #   nltk
    #   open-clip-torch
    #   optuna
    #   peft
    #   pqdm
    #   segmentation-models-pytorch
    #   sentence-transformers
    #   transformers
transformers==5.5.3
    # via
    #   -c requirements/common.txt
    #   -r requirements/test/cuda.in
    #   genai-perf
    #   peft
    #   sentence-transformers
    #   transformers-stream-generator
transformers-stream-generator==0.0.5
    # via -r requirements/test/cuda.in
triton==3.6.0
    # via torch
tritonclient==2.64.0
    # via -r requirements/test/cuda.in
typepy==1.3.2
    # via
    #   dataproperty
    #   pytablewriter
    #   tabledata
typer==0.15.2
    # via
    #   fastsafetensors
    #   huggingface-hub
    #   perceptron
    #   transformers
types-python-dateutil==2.9.0.20241206
    # via arrow
typing-extensions==4.15.0
    # via
    #   -c requirements/common.txt
    #   aiosignal
    #   albumentations
    #   alembic
    #   azure-core
    #   azure-identity
    #   azure-storage-blob
    #   chz
    #   fastapi
    #   grpcio
    #   huggingface-hub
    #   librosa
    #   lm-eval
    #   mistral-common
    #   mteb
    #   opentelemetry-api
    #   opentelemetry-sdk
    #   opentelemetry-semantic-conventions
    #   pqdm
    #   pydantic
    #   pydantic-core
    #   pydantic-extra-types
    #   sentence-transformers
    #   sqlalchemy
    #   starlette
    #   torch
    #   typer
    #   typing-inspection
typing-inspection==0.4.2
    # via pydantic
tzdata==2024.2
    # via pandas
uri-template==1.3.0
    # via jsonschema
urllib3==2.2.3
    # via
    #   blobfile
    #   botocore
    #   docker
    #   requests
    #   responses
    #   tritonclient
uvicorn==0.35.0
    # via gpt-oss
vector-quantize-pytorch==1.21.2
    # via -r requirements/test/cuda.in
virtualenv==20.31.2
    # via ray
vocos==0.1.0
    # via -r requirements/test/cuda.in
wcwidth==0.2.13
    # via ftfy
webcolors==24.11.1
    # via jsonschema
werkzeug==3.1.3
    # via schemathesis
word2number==1.1
    # via lm-eval
wrapt==1.17.2
    # via smart-open
xxhash==3.5.0
    # via
    #   datasets
    #   evaluate
yarl==1.17.1
    # via
    #   aiohttp
    #   schemathesis
zipp==3.23.0
    # via importlib-metadata
