test.txt 24.4 KB
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# This file was autogenerated by uv via the following command:
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#    uv pip compile requirements/test.in -o requirements/test.txt --index-strategy unsafe-best-match --torch-backend cu128 --python-platform x86_64-manylinux_2_28
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absl-py==2.1.0
    # via rouge-score
accelerate==1.0.1
    # via
    #   lm-eval
    #   peft
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aenum==3.1.16
    # via lightly
affine==2.4.0
    # via rasterio
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aiohappyeyeballs==2.4.3
    # via aiohttp
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aiohttp==3.10.11
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    # via
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    #   aiohttp-cors
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    #   datasets
    #   fsspec
    #   lm-eval
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    #   ray
aiohttp-cors==0.8.1
    # via ray
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aiosignal==1.3.1
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    # via aiohttp
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albucore==0.0.16
    # via terratorch
albumentations==1.4.6
    # via terratorch
alembic==1.16.4
    # via mlflow
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annotated-types==0.7.0
    # via pydantic
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antlr4-python3-runtime==4.9.3
    # via
    #   hydra-core
    #   omegaconf
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anyio==4.6.2.post1
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    # via
    #   httpx
    #   starlette
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argcomplete==3.5.1
    # via datamodel-code-generator
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arrow==1.3.0
    # via isoduration
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attrs==24.2.0
    # via
    #   aiohttp
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    #   fiona
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    #   hypothesis
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    #   jsonlines
    #   jsonschema
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    #   pytest-subtests
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    #   rasterio
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    #   referencing
audioread==3.0.1
    # via librosa
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backoff==2.2.1
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    # via
    #   -r requirements/test.in
    #   schemathesis
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bitsandbytes==0.46.1
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    # via
    #   -r requirements/test.in
    #   lightning
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black==24.10.0
    # via datamodel-code-generator
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blinker==1.9.0
    # via flask
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blobfile==3.0.0
    # via -r requirements/test.in
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bm25s==0.2.13
    # via mteb
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boto3==1.35.57
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    # via
    #   runai-model-streamer-s3
    #   tensorizer
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botocore==1.35.57
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    # via
    #   boto3
    #   s3transfer
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bounded-pool-executor==0.0.3
    # via pqdm
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buildkite-test-collector==0.1.9
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    # via -r requirements/test.in
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cachetools==5.5.2
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    # via
    #   google-auth
    #   mlflow-skinny
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certifi==2024.8.30
    # via
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    #   fiona
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    #   httpcore
    #   httpx
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    #   lightly
    #   pyogrio
    #   pyproj
    #   rasterio
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    #   requests
cffi==1.17.1
    # via soundfile
chardet==5.2.0
    # via mbstrdecoder
charset-normalizer==3.4.0
    # via requests
click==8.1.7
    # via
    #   black
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    #   click-plugins
    #   cligj
    #   fiona
    #   flask
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    #   jiwer
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    #   mlflow-skinny
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    #   nltk
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    #   rasterio
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    #   ray
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    #   schemathesis
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    #   typer
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    #   uvicorn
click-plugins==1.1.1.2
    # via
    #   fiona
    #   rasterio
cligj==0.7.2
    # via
    #   fiona
    #   rasterio
cloudpickle==3.1.1
    # via mlflow-skinny
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colorama==0.4.6
    # via
    #   sacrebleu
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    #   schemathesis
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    #   tqdm-multiprocess
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colorful==0.5.6
    # via ray
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contourpy==1.3.0
    # via matplotlib
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coverage==7.10.6
    # via pytest-cov
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cramjam==2.9.0
    # via fastparquet
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cupy-cuda12x==13.6.0
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    # via ray
cycler==0.12.1
    # via matplotlib
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databricks-sdk==0.59.0
    # via mlflow-skinny
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datamodel-code-generator==0.26.3
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    # via -r requirements/test.in
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dataproperty==1.0.1
    # via
    #   pytablewriter
    #   tabledata
datasets==3.0.2
    # via
    #   evaluate
    #   lm-eval
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    #   mteb
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decorator==5.1.1
    # via librosa
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decord==0.6.0
    # via -r requirements/test.in
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dill==0.3.8
    # via
    #   datasets
    #   evaluate
    #   lm-eval
    #   multiprocess
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distlib==0.3.9
    # via virtualenv
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dnspython==2.7.0
    # via email-validator
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docker==7.1.0
    # via mlflow
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docopt==0.6.2
    # via num2words
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docstring-parser==0.17.0
    # via jsonargparse
efficientnet-pytorch==0.7.1
    # via segmentation-models-pytorch
einops==0.8.1
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    # via
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    #   -r requirements/test.in
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    #   encodec
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    #   terratorch
    #   torchgeo
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    #   vector-quantize-pytorch
    #   vocos
einx==0.3.0
    # via vector-quantize-pytorch
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email-validator==2.2.0
    # via pydantic
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encodec==0.1.1
    # via vocos
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eval-type-backport==0.2.2
    # via mteb
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evaluate==0.4.3
    # via lm-eval
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fastapi==0.116.1
    # via mlflow-skinny
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fastparquet==2024.11.0
    # via genai-perf
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fastrlock==0.8.2
    # via cupy-cuda12x
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fastsafetensors==0.1.10
    # via -r requirements/test.in
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filelock==3.16.1
    # via
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    #   blobfile
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    #   datasets
    #   huggingface-hub
    #   ray
    #   torch
    #   transformers
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    #   virtualenv
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fiona==1.10.1
    # via torchgeo
flask==3.1.1
    # via mlflow
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fonttools==4.55.0
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    # via matplotlib
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fqdn==1.5.1
    # via jsonschema
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frozendict==2.4.6
    # via einx
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frozenlist==1.5.0
    # via
    #   aiohttp
    #   aiosignal
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fsspec==2024.9.0
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    # via
    #   datasets
    #   evaluate
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    #   fastparquet
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    #   huggingface-hub
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    #   lightning
    #   pytorch-lightning
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    #   torch
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ftfy==6.3.1
    # via open-clip-torch
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genai-perf==0.0.8
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    # via -r requirements/test.in
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genson==1.3.0
    # via datamodel-code-generator
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geopandas==1.0.1
    # via terratorch
gitdb==4.0.12
    # via gitpython
gitpython==3.1.44
    # via mlflow-skinny
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google-api-core==2.24.2
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    # via
    #   google-cloud-core
    #   google-cloud-storage
    #   opencensus
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google-auth==2.40.2
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    # via
    #   databricks-sdk
    #   google-api-core
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    #   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
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googleapis-common-protos==1.70.0
    # via google-api-core
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graphene==3.4.3
    # via mlflow
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graphql-core==3.2.6
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    # via
    #   graphene
    #   graphql-relay
    #   hypothesis-graphql
graphql-relay==3.2.0
    # via graphene
greenlet==3.2.3
    # via sqlalchemy
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grpcio==1.71.0
    # via ray
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gunicorn==23.0.0
    # via mlflow
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h11==0.14.0
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    # via
    #   httpcore
    #   uvicorn
h5py==3.13.0
    # via terratorch
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harfile==0.3.0
    # via schemathesis
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hf-xet==1.1.7
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    # via huggingface-hub
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hiredis==3.0.0
    # via tensorizer
httpcore==1.0.6
    # via httpx
httpx==0.27.2
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    # via
    #   -r requirements/test.in
    #   schemathesis
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huggingface-hub==0.34.3
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    # via
    #   accelerate
    #   datasets
    #   evaluate
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    #   open-clip-torch
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    #   peft
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    #   segmentation-models-pytorch
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    #   sentence-transformers
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    #   terratorch
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    #   timm
    #   tokenizers
    #   transformers
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    #   vocos
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humanize==4.11.0
    # via runai-model-streamer
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hydra-core==1.3.2
    # via
    #   lightly
    #   lightning
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hypothesis==6.131.0
    # via
    #   hypothesis-graphql
    #   hypothesis-jsonschema
    #   schemathesis
hypothesis-graphql==0.11.1
    # via schemathesis
hypothesis-jsonschema==0.23.1
    # via schemathesis
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idna==3.10
    # via
    #   anyio
    #   email-validator
    #   httpx
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    #   jsonschema
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    #   requests
    #   yarl
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imageio==2.37.0
    # via scikit-image
importlib-metadata==8.7.0
    # via
    #   mlflow-skinny
    #   opentelemetry-api
importlib-resources==6.5.2
    # via typeshed-client
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inflect==5.6.2
    # via datamodel-code-generator
iniconfig==2.0.0
    # via pytest
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isoduration==20.11.0
    # via jsonschema
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isort==5.13.2
    # via datamodel-code-generator
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itsdangerous==2.2.0
    # via flask
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jinja2==3.1.6
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    # via
    #   datamodel-code-generator
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    #   flask
    #   mlflow
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    #   torch
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jiwer==3.0.5
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    # via -r requirements/test.in
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jmespath==1.0.1
    # via
    #   boto3
    #   botocore
joblib==1.4.2
    # via
    #   librosa
    #   nltk
    #   scikit-learn
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jsonargparse==4.35.0
    # via
    #   lightning
    #   terratorch
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jsonlines==4.0.0
    # via lm-eval
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jsonpointer==3.0.0
    # via jsonschema
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jsonschema==4.23.0
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    # via
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    #   hypothesis-jsonschema
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    #   mistral-common
    #   ray
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    #   schemathesis
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jsonschema-specifications==2024.10.1
    # via jsonschema
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junit-xml==1.9
    # via schemathesis
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kaleido==0.2.1
    # via genai-perf
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kiwisolver==1.4.7
    # via matplotlib
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kornia==0.8.1
    # via torchgeo
kornia-rs==0.1.9
    # via kornia
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lazy-loader==0.4
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    # via
    #   librosa
    #   scikit-image
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libnacl==2.1.0
    # via tensorizer
librosa==0.10.2.post1
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    # via -r requirements/test.in
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lightly==1.5.20
    # via
    #   terratorch
    #   torchgeo
lightly-utils==0.0.2
    # via lightly
lightning==2.5.1.post0
    # via
    #   terratorch
    #   torchgeo
lightning-utilities==0.14.3
    # via
    #   lightning
    #   pytorch-lightning
    #   torchmetrics
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llvmlite==0.44.0
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    # via numba
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lm-eval @ git+https://github.com/EleutherAI/lm-evaluation-harness.git@206b7722158f58c35b7ffcd53b035fdbdda5126d
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    # via -r requirements/test.in
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lxml==5.3.0
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    # via
    #   blobfile
    #   sacrebleu
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mako==1.3.10
    # via alembic
markdown==3.8.2
    # via mlflow
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markdown-it-py==3.0.0
    # via rich
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markupsafe==3.0.1
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    # via
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    #   flask
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    #   jinja2
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    #   mako
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    #   werkzeug
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matplotlib==3.9.2
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    # via
    #   -r requirements/test.in
    #   lightning
    #   mlflow
    #   pycocotools
    #   torchgeo
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mbstrdecoder==1.1.3
    # via
    #   dataproperty
    #   pytablewriter
    #   typepy
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mdurl==0.1.2
    # via markdown-it-py
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mistral-common==1.8.2
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    # via -r requirements/test.in
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mlflow==2.22.0
    # via terratorch
mlflow-skinny==2.22.0
    # via mlflow
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more-itertools==10.5.0
    # via lm-eval
mpmath==1.3.0
    # via sympy
msgpack==1.1.0
    # via
    #   librosa
    #   ray
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mteb==1.38.11
    # via -r requirements/test.in
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multidict==6.1.0
    # via
    #   aiohttp
    #   yarl
multiprocess==0.70.16
    # via
    #   datasets
    #   evaluate
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munch==4.0.0
    # via pretrainedmodels
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mypy-extensions==1.0.0
    # via black
networkx==3.2.1
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    # via
    #   scikit-image
    #   torch
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nltk==3.9.1
    # via rouge-score
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num2words==0.5.14
    # via -r requirements/test.in
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numba==0.61.2
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    # via
    #   -r requirements/test.in
    #   librosa
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numexpr==2.10.1
    # via lm-eval
numpy==1.26.4
    # via
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    #   -r requirements/test.in
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    #   accelerate
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    #   albucore
    #   albumentations
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    #   bitsandbytes
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    #   bm25s
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    #   contourpy
    #   cupy-cuda12x
    #   datasets
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    #   decord
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    #   einx
    #   encodec
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    #   evaluate
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    #   fastparquet
    #   genai-perf
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    #   geopandas
    #   h5py
    #   imageio
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    #   librosa
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    #   lightly
    #   lightly-utils
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    #   matplotlib
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    #   mistral-common
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    #   mlflow
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    #   mteb
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    #   numba
    #   numexpr
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    #   opencv-python-headless
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    #   pandas
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    #   patsy
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    #   peft
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    #   pycocotools
    #   pyogrio
    #   rasterio
    #   rioxarray
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    #   rouge-score
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    #   runai-model-streamer
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    #   sacrebleu
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    #   scikit-image
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    #   scikit-learn
    #   scipy
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    #   segmentation-models-pytorch
    #   shapely
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    #   soxr
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    #   statsmodels
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    #   tensorboardx
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    #   tensorizer
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    #   tifffile
    #   torchgeo
    #   torchmetrics
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    #   torchvision
    #   transformers
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    #   tritonclient
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    #   vocos
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    #   xarray
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nvidia-cublas-cu12==12.8.4.1
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    # via
    #   nvidia-cudnn-cu12
    #   nvidia-cusolver-cu12
    #   torch
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nvidia-cuda-cupti-cu12==12.8.90
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    # via torch
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nvidia-cuda-nvrtc-cu12==12.8.93
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    # via torch
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nvidia-cuda-runtime-cu12==12.8.90
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    # via torch
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nvidia-cudnn-cu12==9.10.2.21
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    # via torch
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nvidia-cufft-cu12==11.3.3.83
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    # via torch
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nvidia-cufile-cu12==1.13.1.3
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    # via torch
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nvidia-curand-cu12==10.3.9.90
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    # via torch
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nvidia-cusolver-cu12==11.7.3.90
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    # via torch
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nvidia-cusparse-cu12==12.5.8.93
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    # via
    #   nvidia-cusolver-cu12
    #   torch
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nvidia-cusparselt-cu12==0.7.1
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    # via torch
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nvidia-nccl-cu12==2.27.3
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    # via torch
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nvidia-nvjitlink-cu12==12.8.93
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    # via
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    #   nvidia-cufft-cu12
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    #   nvidia-cusolver-cu12
    #   nvidia-cusparse-cu12
    #   torch
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nvidia-nvtx-cu12==12.8.90
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    # via torch
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omegaconf==2.3.0
    # via
    #   hydra-core
    #   lightning
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open-clip-torch==2.32.0
    # via -r requirements/test.in
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opencensus==0.11.4
    # via ray
opencensus-context==0.1.3
    # via opencensus
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opencv-python-headless==4.11.0.86
    # via
    #   -r requirements/test.in
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    #   albucore
    #   albumentations
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    #   mistral-common
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opentelemetry-api==1.35.0
    # via
    #   mlflow-skinny
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    #   opentelemetry-exporter-prometheus
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    #   opentelemetry-sdk
    #   opentelemetry-semantic-conventions
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opentelemetry-exporter-prometheus==0.56b0
    # via ray
opentelemetry-proto==1.36.0
    # via ray
627
opentelemetry-sdk==1.35.0
Rui Qiao's avatar
Rui Qiao committed
628
629
630
631
    # via
    #   mlflow-skinny
    #   opentelemetry-exporter-prometheus
    #   ray
632
633
opentelemetry-semantic-conventions==0.56b0
    # via opentelemetry-sdk
634
packaging==24.2
635
636
637
638
639
640
    # via
    #   accelerate
    #   black
    #   datamodel-code-generator
    #   datasets
    #   evaluate
641
    #   fastparquet
642
643
    #   geopandas
    #   gunicorn
644
    #   huggingface-hub
645
646
    #   hydra-core
    #   kornia
647
    #   lazy-loader
648
649
    #   lightning
    #   lightning-utilities
650
    #   matplotlib
651
    #   mlflow-skinny
652
    #   peft
653
    #   plotly
654
    #   pooch
655
    #   pyogrio
656
657
    #   pytest
    #   pytest-rerunfailures
658
    #   pytorch-lightning
659
    #   ray
660
661
    #   rioxarray
    #   scikit-image
662
    #   statsmodels
663
664
    #   tensorboardx
    #   torchmetrics
665
666
    #   transformers
    #   typepy
667
    #   xarray
668
669
670
671
pandas==2.2.3
    # via
    #   datasets
    #   evaluate
672
673
    #   fastparquet
    #   genai-perf
674
675
    #   geopandas
    #   mlflow
676
    #   statsmodels
677
678
    #   torchgeo
    #   xarray
679
680
681
682
pathspec==0.12.1
    # via black
pathvalidate==3.2.1
    # via pytablewriter
683
684
patsy==1.0.1
    # via statsmodels
685
peft==0.16.0
686
    # via
687
    #   -r requirements/test.in
688
    #   lm-eval
689
pillow==10.4.0
690
    # via
691
    #   genai-perf
692
693
    #   imageio
    #   lightly-utils
694
    #   matplotlib
695
    #   mistral-common
696
697
    #   scikit-image
    #   segmentation-models-pytorch
698
    #   sentence-transformers
699
    #   torchgeo
700
701
702
703
704
    #   torchvision
platformdirs==4.3.6
    # via
    #   black
    #   pooch
Rui Qiao's avatar
Rui Qiao committed
705
    #   virtualenv
706
707
plotly==5.24.1
    # via genai-perf
708
pluggy==1.5.0
709
710
711
    # via
    #   pytest
    #   pytest-cov
712
713
polars==1.29.0
    # via mteb
714
715
716
717
pooch==1.8.2
    # via librosa
portalocker==2.10.1
    # via sacrebleu
718
pqdm==0.2.0
719
    # via -r requirements/test.in
720
721
pretrainedmodels==0.7.4
    # via segmentation-models-pytorch
Rui Qiao's avatar
Rui Qiao committed
722
prometheus-client==0.22.0
Rui Qiao's avatar
Rui Qiao committed
723
724
725
    # via
    #   opentelemetry-exporter-prometheus
    #   ray
726
727
propcache==0.2.0
    # via yarl
Rui Qiao's avatar
Rui Qiao committed
728
729
proto-plus==1.26.1
    # via google-api-core
730
731
protobuf==5.28.3
    # via
Rui Qiao's avatar
Rui Qiao committed
732
733
    #   google-api-core
    #   googleapis-common-protos
734
    #   mlflow-skinny
Rui Qiao's avatar
Rui Qiao committed
735
    #   opentelemetry-proto
Rui Qiao's avatar
Rui Qiao committed
736
    #   proto-plus
737
    #   ray
738
    #   tensorboardx
739
740
741
742
743
744
745
746
    #   tensorizer
psutil==6.1.0
    # via
    #   accelerate
    #   peft
    #   tensorizer
py==1.11.0
    # via pytest-forked
Rui Qiao's avatar
Rui Qiao committed
747
748
py-spy==0.4.0
    # via ray
749
pyarrow==18.0.0
750
751
752
    # via
    #   datasets
    #   genai-perf
753
    #   mlflow
Rui Qiao's avatar
Rui Qiao committed
754
755
756
757
758
759
pyasn1==0.6.1
    # via
    #   pyasn1-modules
    #   rsa
pyasn1-modules==0.4.2
    # via google-auth
760
761
pybind11==2.13.6
    # via lm-eval
762
763
pycocotools==2.0.8
    # via terratorch
Patrick von Platen's avatar
Patrick von Platen committed
764
765
pycountry==24.6.1
    # via pydantic-extra-types
766
767
pycparser==2.22
    # via cffi
768
769
pycryptodomex==3.22.0
    # via blobfile
770
pydantic==2.11.7
771
    # via
772
    #   -r requirements/test.in
773
    #   albumentations
774
    #   datamodel-code-generator
775
776
    #   fastapi
    #   lightly
777
    #   mistral-common
778
    #   mlflow-skinny
779
    #   mteb
Patrick von Platen's avatar
Patrick von Platen committed
780
    #   pydantic-extra-types
Rui Qiao's avatar
Rui Qiao committed
781
    #   ray
782
pydantic-core==2.33.2
783
    # via pydantic
Patrick von Platen's avatar
Patrick von Platen committed
784
785
pydantic-extra-types==2.10.5
    # via mistral-common
786
787
pygments==2.18.0
    # via rich
788
789
pyogrio==0.11.0
    # via geopandas
790
pyparsing==3.2.0
791
792
793
794
795
796
797
798
    # via
    #   matplotlib
    #   rasterio
pyproj==3.7.1
    # via
    #   geopandas
    #   rioxarray
    #   torchgeo
799
800
pyrate-limiter==3.7.0
    # via schemathesis
801
802
pystemmer==3.0.0
    # via mteb
803
804
pytablewriter==1.2.0
    # via lm-eval
805
pytest==8.3.5
806
    # via
807
    #   -r requirements/test.in
808
    #   buildkite-test-collector
809
    #   genai-perf
810
    #   pytest-asyncio
811
    #   pytest-cov
812
    #   pytest-forked
813
    #   pytest-mock
814
815
    #   pytest-rerunfailures
    #   pytest-shard
816
    #   pytest-subtests
817
    #   pytest-timeout
818
    #   schemathesis
819
    #   terratorch
820
pytest-asyncio==0.24.0
821
    # via -r requirements/test.in
822
823
pytest-cov==6.3.0
    # via -r requirements/test.in
824
pytest-forked==1.6.0
825
    # via -r requirements/test.in
826
827
pytest-mock==3.14.0
    # via genai-perf
828
pytest-rerunfailures==14.0
829
    # via -r requirements/test.in
830
pytest-shard==0.1.2
831
    # via -r requirements/test.in
832
833
pytest-subtests==0.14.1
    # via schemathesis
834
835
pytest-timeout==2.3.1
    # via -r requirements/test.in
836
837
python-box==7.3.2
    # via terratorch
838
839
python-dateutil==2.9.0.post0
    # via
840
    #   arrow
841
    #   botocore
842
843
    #   graphene
    #   lightly
844
845
846
    #   matplotlib
    #   pandas
    #   typepy
847
848
python-rapidjson==1.20
    # via tritonclient
849
850
851
852
pytorch-lightning==2.5.2
    # via
    #   lightly
    #   lightning
853
854
pytrec-eval-terrier==0.5.7
    # via mteb
855
856
857
858
859
860
861
pytz==2024.2
    # via
    #   pandas
    #   typepy
pyyaml==6.0.2
    # via
    #   accelerate
862
    #   albumentations
863
864
    #   datamodel-code-generator
    #   datasets
865
    #   genai-perf
866
    #   huggingface-hub
867
868
869
870
    #   jsonargparse
    #   lightning
    #   mlflow-skinny
    #   omegaconf
871
    #   peft
872
    #   pytorch-lightning
873
    #   ray
874
    #   responses
875
    #   schemathesis
876
877
    #   timm
    #   transformers
878
    #   vocos
879
880
rapidfuzz==3.12.1
    # via jiwer
881
882
883
884
885
rasterio==1.4.3
    # via
    #   rioxarray
    #   terratorch
    #   torchgeo
Rui Qiao's avatar
Rui Qiao committed
886
ray==2.48.0
887
    # via -r requirements/test.in
888
889
890
891
892
893
894
895
896
redis==5.2.0
    # via tensorizer
referencing==0.35.1
    # via
    #   jsonschema
    #   jsonschema-specifications
regex==2024.9.11
    # via
    #   nltk
897
    #   open-clip-torch
898
899
900
901
902
903
    #   sacrebleu
    #   tiktoken
    #   transformers
requests==2.32.3
    # via
    #   buildkite-test-collector
904
    #   databricks-sdk
905
    #   datasets
906
    #   docker
907
    #   evaluate
Rui Qiao's avatar
Rui Qiao committed
908
    #   google-api-core
909
    #   google-cloud-storage
910
    #   huggingface-hub
911
    #   lightly
912
    #   lm-eval
913
    #   mistral-common
914
    #   mlflow-skinny
915
    #   mteb
916
917
    #   pooch
    #   ray
918
    #   responses
919
920
    #   schemathesis
    #   starlette-testclient
921
922
    #   tiktoken
    #   transformers
923
924
responses==0.25.3
    # via genai-perf
925
926
927
928
rfc3339-validator==0.1.4
    # via jsonschema
rfc3987==1.3.8
    # via jsonschema
929
rich==13.9.4
930
931
    # via
    #   genai-perf
932
    #   lightning
933
    #   mteb
934
    #   typer
935
936
rioxarray==0.19.0
    # via terratorch
937
938
rouge-score==0.1.2
    # via lm-eval
939
rpds-py==0.20.1
940
941
942
    # via
    #   jsonschema
    #   referencing
Rui Qiao's avatar
Rui Qiao committed
943
944
rsa==4.9.1
    # via google-auth
945
946
rtree==1.4.0
    # via torchgeo
947
runai-model-streamer==0.14.0
948
    # via -r requirements/test.in
949
950
runai-model-streamer-gcs==0.14.0
    # via runai-model-streamer
951
952
runai-model-streamer-s3==0.14.0
    # via runai-model-streamer
953
s3transfer==0.10.3
954
    # via boto3
955
956
957
958
959
sacrebleu==2.4.3
    # via lm-eval
safetensors==0.4.5
    # via
    #   accelerate
960
    #   open-clip-torch
961
962
963
    #   peft
    #   timm
    #   transformers
964
965
schemathesis==3.39.15
    # via -r requirements/test.in
966
967
scikit-image==0.25.2
    # via albumentations
968
969
scikit-learn==1.5.2
    # via
970
    #   albumentations
971
972
    #   librosa
    #   lm-eval
973
    #   mlflow
974
    #   mteb
975
976
977
    #   sentence-transformers
scipy==1.13.1
    # via
978
    #   albumentations
979
    #   bm25s
980
    #   librosa
981
    #   mlflow
982
    #   mteb
983
    #   scikit-image
984
985
    #   scikit-learn
    #   sentence-transformers
986
    #   statsmodels
987
    #   vocos
988
989
990
991
segmentation-models-pytorch==0.4.0
    # via
    #   terratorch
    #   torchgeo
992
sentence-transformers==3.2.1
993
994
995
    # via
    #   -r requirements/test.in
    #   mteb
996
997
sentencepiece==0.2.0
    # via mistral-common
998
setuptools==77.0.3
999
    # via
1000
    #   lightning-utilities
1001
1002
    #   pytablewriter
    #   torch
Huy Do's avatar
Huy Do committed
1003
    #   triton
1004
1005
1006
1007
shapely==2.1.1
    # via
    #   geopandas
    #   torchgeo
1008
1009
shellingham==1.5.4
    # via typer
1010
1011
six==1.16.0
    # via
1012
    #   junit-xml
1013
    #   lightly
Rui Qiao's avatar
Rui Qiao committed
1014
    #   opencensus
1015
    #   python-dateutil
1016
    #   rfc3339-validator
1017
    #   rouge-score
1018
    #   segmentation-models-pytorch
Rui Qiao's avatar
Rui Qiao committed
1019
1020
smart-open==7.1.0
    # via ray
1021
1022
smmap==5.0.2
    # via gitdb
1023
1024
1025
1026
sniffio==1.3.1
    # via
    #   anyio
    #   httpx
1027
1028
sortedcontainers==2.4.0
    # via hypothesis
1029
1030
soundfile==0.12.1
    # via
1031
    #   -r requirements/test.in
1032
    #   librosa
Julien Denize's avatar
Julien Denize committed
1033
    #   mistral-common
1034
soxr==0.5.0.post1
Julien Denize's avatar
Julien Denize committed
1035
1036
1037
    # via
    #   librosa
    #   mistral-common
1038
1039
1040
1041
sqlalchemy==2.0.41
    # via
    #   alembic
    #   mlflow
1042
1043
sqlitedict==2.1.0
    # via lm-eval
1044
1045
sqlparse==0.5.3
    # via mlflow-skinny
1046
1047
starlette==0.46.2
    # via
1048
    #   fastapi
1049
1050
1051
1052
    #   schemathesis
    #   starlette-testclient
starlette-testclient==0.4.1
    # via schemathesis
1053
1054
statsmodels==0.14.4
    # via genai-perf
Huy Do's avatar
Huy Do committed
1055
sympy==1.13.3
1056
1057
1058
    # via
    #   einx
    #   torch
1059
1060
1061
1062
tabledata==1.3.3
    # via pytablewriter
tabulate==0.9.0
    # via sacrebleu
1063
1064
tblib==3.1.0
    # via -r requirements/test.in
1065
1066
1067
tcolorpy==0.1.6
    # via pytablewriter
tenacity==9.0.0
1068
1069
1070
    # via
    #   lm-eval
    #   plotly
1071
1072
tensorboardx==2.6.4
    # via lightning
1073
tensorizer==2.10.1
1074
    # via -r requirements/test.in
1075
terratorch @ git+https://github.com/IBM/terratorch.git@07184fcf91a1324f831ff521dd238d97fe350e3e
1076
    # via -r requirements/test.in
1077
1078
threadpoolctl==3.5.0
    # via scikit-learn
1079
1080
1081
1082
tifffile==2025.3.30
    # via
    #   scikit-image
    #   terratorch
1083
1084
1085
1086
tiktoken==0.7.0
    # via
    #   lm-eval
    #   mistral-common
Nicolò Lucchesi's avatar
Nicolò Lucchesi committed
1087
timm==1.0.17
1088
1089
1090
    # via
    #   -r requirements/test.in
    #   open-clip-torch
1091
1092
1093
    #   segmentation-models-pytorch
    #   terratorch
    #   torchgeo
1094
tokenizers==0.22.0
1095
1096
1097
    # via
    #   -r requirements/test.in
    #   transformers
1098
1099
1100
1101
tomli==2.2.1
    # via schemathesis
tomli-w==1.2.0
    # via schemathesis
Huy Do's avatar
Huy Do committed
1102
torch==2.8.0+cu128
1103
    # via
1104
    #   -r requirements/test.in
1105
1106
    #   accelerate
    #   bitsandbytes
1107
    #   efficientnet-pytorch
1108
    #   encodec
1109
    #   fastsafetensors
1110
1111
1112
    #   kornia
    #   lightly
    #   lightning
1113
    #   lm-eval
1114
    #   mteb
1115
    #   open-clip-torch
1116
    #   peft
1117
1118
    #   pretrainedmodels
    #   pytorch-lightning
1119
    #   runai-model-streamer
1120
    #   segmentation-models-pytorch
1121
1122
    #   sentence-transformers
    #   tensorizer
1123
    #   terratorch
1124
    #   timm
1125
    #   torchaudio
1126
1127
    #   torchgeo
    #   torchmetrics
1128
    #   torchvision
1129
1130
    #   vector-quantize-pytorch
    #   vocos
Huy Do's avatar
Huy Do committed
1131
torchaudio==2.8.0+cu128
1132
    # via
1133
    #   -r requirements/test.in
1134
1135
    #   encodec
    #   vocos
1136
1137
1138
1139
1140
1141
1142
1143
torchgeo==0.7.0
    # via terratorch
torchmetrics==1.7.4
    # via
    #   lightning
    #   pytorch-lightning
    #   terratorch
    #   torchgeo
Huy Do's avatar
Huy Do committed
1144
torchvision==0.23.0+cu128
Michael Goin's avatar
Michael Goin committed
1145
1146
    # via
    #   -r requirements/test.in
1147
    #   lightly
1148
    #   open-clip-torch
1149
1150
1151
    #   pretrainedmodels
    #   segmentation-models-pytorch
    #   terratorch
Michael Goin's avatar
Michael Goin committed
1152
    #   timm
1153
    #   torchgeo
1154
1155
1156
1157
1158
tqdm==4.66.6
    # via
    #   datasets
    #   evaluate
    #   huggingface-hub
1159
1160
    #   lightly
    #   lightning
1161
    #   lm-eval
1162
    #   mteb
1163
    #   nltk
1164
    #   open-clip-torch
1165
    #   peft
1166
    #   pqdm
1167
1168
1169
    #   pretrainedmodels
    #   pytorch-lightning
    #   segmentation-models-pytorch
1170
1171
1172
1173
1174
    #   sentence-transformers
    #   tqdm-multiprocess
    #   transformers
tqdm-multiprocess==0.0.11
    # via lm-eval
1175
transformers==4.56.2
1176
    # via
1177
    #   -r requirements/test.in
1178
    #   genai-perf
1179
1180
1181
1182
1183
    #   lm-eval
    #   peft
    #   sentence-transformers
    #   transformers-stream-generator
transformers-stream-generator==0.0.5
1184
    # via -r requirements/test.in
Huy Do's avatar
Huy Do committed
1185
triton==3.4.0
1186
    # via torch
1187
1188
tritonclient==2.51.0
    # via
1189
    #   -r requirements/test.in
1190
    #   genai-perf
1191
typepy==1.3.2
1192
1193
1194
1195
    # via
    #   dataproperty
    #   pytablewriter
    #   tabledata
1196
1197
typer==0.15.2
    # via fastsafetensors
1198
1199
types-python-dateutil==2.9.0.20241206
    # via arrow
1200
1201
typeshed-client==2.8.2
    # via jsonargparse
1202
1203
typing-extensions==4.12.2
    # via
1204
1205
1206
1207
    #   albumentations
    #   alembic
    #   fastapi
    #   graphene
1208
1209
    #   huggingface-hub
    #   librosa
1210
1211
    #   lightning
    #   lightning-utilities
1212
    #   mistral-common
1213
    #   mlflow-skinny
1214
    #   mteb
1215
1216
1217
    #   opentelemetry-api
    #   opentelemetry-sdk
    #   opentelemetry-semantic-conventions
1218
    #   pqdm
1219
1220
    #   pydantic
    #   pydantic-core
Patrick von Platen's avatar
Patrick von Platen committed
1221
    #   pydantic-extra-types
1222
1223
    #   pytorch-lightning
    #   sqlalchemy
1224
    #   torch
1225
    #   torchgeo
1226
    #   typer
1227
    #   typeshed-client
1228
1229
1230
    #   typing-inspection
typing-inspection==0.4.1
    # via pydantic
1231
1232
tzdata==2024.2
    # via pandas
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uri-template==1.3.0
    # via jsonschema
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urllib3==2.2.3
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    # via
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    #   blobfile
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    #   botocore
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    #   docker
    #   lightly
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    #   requests
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    #   responses
    #   tritonclient
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uvicorn==0.35.0
    # via mlflow-skinny
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vector-quantize-pytorch==1.21.2
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    # via -r requirements/test.in
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virtualenv==20.31.2
    # via ray
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vocos==0.1.0
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    # via -r requirements/test.in
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wcwidth==0.2.13
    # via ftfy
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webcolors==24.11.1
    # via jsonschema
werkzeug==3.1.3
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    # via
    #   flask
    #   schemathesis
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word2number==1.1
    # via lm-eval
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wrapt==1.17.2
    # via smart-open
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xarray==2025.7.1
    # via rioxarray
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xxhash==3.5.0
    # via
    #   datasets
    #   evaluate
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yarl==1.17.1
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    # via
    #   aiohttp
    #   schemathesis
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zipp==3.23.0
    # via importlib-metadata
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zstandard==0.23.0
    # via lm-eval