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setup.cfg
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setup.cfg
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[metadata]
name = crfm-helm
version = 0.5.4
author = Stanford CRFM
author_email = [email protected]
description = Benchmark for language models
long_description = file: README.md, docs/tutorial.md
long_description_content_type = text/markdown
keywords = language models benchmarking
license = Apache License 2.0
classifiers =
Programming Language :: Python :: 3
Programming Language :: Python :: 3 :: Only
Programming Language :: Python :: 3.9
Programming Language :: Python :: 3.10
Programming Language :: Python :: 3.11
License :: OSI Approved :: Apache Software License
url = https://github.com/stanford-crfm/helm
[options]
python_requires = >=3.9
package_dir =
=src
packages = find:
zip_safe = False
include_package_data = True
install_requires=
# Common
cattrs~=22.2
dacite~=1.6
importlib-resources~=5.10
Mako~=1.2
numpy~=1.26,<3
pandas~=2.0
pyhocon~=0.3.59
retrying~=1.3
spacy~=3.5
tqdm~=4.64
zstandard~=0.18.0
# sqlitedict==2.0.0 is slow! https://github.com/RaRe-Technologies/sqlitedict/issues/152
# Keep sqlitedict version at 1.7.0.
sqlitedict>=2.1.0,<3.0
bottle~=0.12.23
# Basic Scenarios
datasets~=2.17
pyarrow>=11.0.0 # Pinned transitive dependency for datasets; workaround for #1026
pyarrow-hotfix~=0.6 # Hotfix for CVE-2023-47248
# Basic metrics
nltk~=3.7,!=3.9.0 # Cannot use 3.9.0 due to https://github.com/nltk/nltk/issues/3308
rouge-score~=0.1.2
scipy~=1.10
uncertainty-calibration~=0.1.4
scikit-learn~=1.1
# Models and Metrics Extras
transformers~=4.40 # For anthropic_client, vision_language.huggingface_vlm_client, huggingface_client, huggingface_tokenizer, test_openai_token_cost_estimator, model_summac (via summarization_metrics)
# TODO: Upgrade torch - we need > 2.0.0 for newer versions of transformers
torch>=1.13.1,<3.0.0 # For huggingface_client, yalm_tokenizer, model_summac (via summarization_metrics)
torchvision>=0.14.1,<3.0.0 # For huggingface_client, yalm_tokenizer, model_summac (via summarization_metrics)
[options.extras_require]
proxy-server =
gunicorn>=20.1
human-evaluation =
scaleapi~=2.13.0
surge-api~=1.1.0
scenarios =
gdown~=5.1 # For disinformation_scenario, med_mcqa_scenario, med_qa_scenario: used by ensure_file_downloaded()
sympy~=1.11.1 # For numeracy_scenario
xlrd~=2.0.1 # For ice_scenario: used by pandas.read_excel()
metrics =
google-api-python-client~=2.64 # For perspective_api_client via toxicity_metrics
numba~=0.56 # For copyright_metrics
pytrec_eval==0.5 # For ranking_metrics
sacrebleu~=2.2.1 # For disinformation_metrics, machine_translation_metrics
langdetect~=1.0.9 # For ifeval_metrics
immutabledict~=4.2.0 # For ifeval_metrics
gradio_client~=1.3 # For bigcodebench_metrics
summarization =
summ-eval~=0.892 # For summarization_metrics
plots =
colorcet~=3.0.1
matplotlib~=3.6.0
seaborn~=0.11.0
decodingtrust =
fairlearn~=0.9.0
slurm =
simple-slurm~=0.2.6
cleva =
unidecode~=1.3
pypinyin~=0.49.0
jieba~=0.42.1
opencc~=1.1
langdetect~=1.0
images =
crfm-helm[accelerate]
pillow~=10.2
mongo =
pymongo~=4.2
unitxt =
evaluate~=0.4.1
bhasa =
pythainlp==5.0.0
pyonmttok==1.37.0
sacrebleu~=2.2.1
# Model extras
accelerate =
accelerate~=0.25
aleph-alpha =
aleph-alpha-client~=2.14.0
tokenizers>=0.13.3
allenai =
ai2-olmo~=0.2
amazon =
boto3~=1.28.57
awscli~=1.29.57
botocore~=1.31.57
anthropic =
anthropic~=0.17,<0.39 # TODO(#3212): Limit anthropic to >=0.39 after resolving #3212.
websocket-client~=1.3.2 # For legacy stanford-online-all-v4-s3
cohere =
cohere~=5.3
mistral =
mistralai~=1.1
openai =
openai~=1.52
tiktoken~=0.7
pydantic~=2.0 # For model_dump(mode="json") - openai only requires pydantic>=1.9.0
google =
google-cloud-aiplatform~=1.48
together =
together~=1.1
yandex =
sentencepiece~=0.2.0
models =
crfm-helm[ai21]
crfm-helm[accelerate]
crfm-helm[aleph-alpha]
crfm-helm[allenai]
crfm-helm[amazon]
crfm-helm[anthropic]
crfm-helm[cohere]
crfm-helm[google]
crfm-helm[mistral]
crfm-helm[openai]
crfm-helm[reka]
crfm-helm[together]
crfm-helm[yandex]
crfm-helm[ibm-enterprise-scenarios]
reka =
reka-api~=2.0.0
vlm =
crfm-helm[openai]
# For OpenFlamingo
einops~=0.7.0
einops-exts~=0.0.4
open-clip-torch~=2.24
# For IDEFICS
torch~=2.1
# For Qwen: https://github.com/QwenLM/Qwen-VL/blob/master/requirements.txt
transformers_stream_generator~=0.0.4
scipy~=1.10
torchvision>=0.14.1,<3.0.0
# For Reka AI
crfm-helm[reka]
# VLM scenarios
crfm-helm[images]
crfm-helm[image2struct]
# For metrics
pycocoevalcap~=1.2
ibm-enterprise-scenarios =
openpyxl~=3.1
image2struct =
crfm-helm[images]
# Latex
# You will need to install LaTeX separately.
# You can run `sudo apt-get install texlive-full` on Ubuntu.
latex~=0.7.0
pdf2image~=1.16.3
# Webpage
# You will need install Jekyll separately.
selenium~=4.17.2
html2text~=2024.2.26
# Metrics
opencv-python>=4.7.0.68,<4.8.2.0
lpips~=0.1.4
imagehash~=4.3.1 # for caching
heim =
# HEIM scenarios
gdown~=5.1
# HEIM models
diffusers~=0.24.0
icetk~=0.0.4
jax~=0.4.13
jaxlib~=0.4.13
crfm-helm[openai]
# For model, kakaobrain/mindall-e
einops~=0.7.0
omegaconf~=2.3.0
pytorch-lightning~=2.0.5
# For model, craiyon/dalle-mini and craiyon/dalle-mega
flax~=0.6.11
ftfy~=6.1.1
Unidecode~=1.3.6
wandb~=0.16
# HEIM perturbations
google-cloud-translate~=3.11.2
# HEIM metrics
autokeras~=1.0.20
clip-anytorch~=2.5.0
google-cloud-storage~=2.9
lpips~=0.1.4
multilingual-clip~=1.0.10
NudeNet~=2.0.9
opencv-python>=4.7.0.68,<4.8.2.0
pytorch-fid~=0.3.0
tensorflow~=2.11
timm~=0.6.12
torch-fidelity~=0.3.0
torchmetrics~=0.11.1
# Transitive dependency of NudeNet
# This needs to be a version that provides wheels for all Python versions
# supported by crfm-helm i.e. Python 3.9, 3.10, 3.11, 3.12
# Disallow version 0.23.* because it has no Python 3.9 wheels.
scikit-image>=0.22,==0.*,!=0.23.*
# Shared image dependencies
crfm-helm[images]
audiolm =
crfm-helm[openai]
crfm-helm[google]
# For HuggingFace audio datasets
soundfile~=0.12
librosa~=0.10
# For LLaMA-Omni
openai-whisper==20240930
# For Qwen2-Audio
transformers~=4.45.1
transformers_stream_generator~=0.0.4
scipy~=1.10
torchvision>=0.14.1,<3.0.0
# For metrics
pycocoevalcap~=1.2
jiwer~=3.0
rapidfuzz~=3.10
jieba~=0.42.1
# Install everything
all =
crfm-helm[proxy-server]
crfm-helm[human-evaluation]
crfm-helm[scenarios]
crfm-helm[metrics]
crfm-helm[plots]
crfm-helm[decodingtrust]
crfm-helm[slurm]
crfm-helm[cleva]
crfm-helm[images]
crfm-helm[models]
crfm-helm[mongo]
crfm-helm[heim]
crfm-helm[vlm]
crfm-helm[audiolm]
# crfm-helm[bhasa] is excluded because pyonmttok does not support Python 3.12
# crfm-helm[dev] is excluded because end-users don't need it.
# crfm-helm[summarize] is excluded because it requires torch<2.0
# TODO(#2280): Add crfm-helm[summarize] back.
# Development only
# Do not include in all
dev =
pytest~=7.2.0
pre-commit~=2.20.0
# Errors produced by type checkers and linters are very version-specific
# so they are pinned to an exact version.
black==24.3.0
mypy==1.5.1
flake8==5.0.4
[options.entry_points]
console_scripts =
helm-run = helm.benchmark.run:main
helm-summarize = helm.benchmark.presentation.summarize:main
helm-server = helm.benchmark.server:main
helm-create-plots = helm.benchmark.presentation.create_plots:main
crfm-proxy-server = helm.proxy.server:main
crfm-proxy-cli = helm.proxy.cli:main
[options.packages.find]
where = src
exclude =
tests*
# Settings for Flake8: Tool For Style Guide Enforcement
[flake8]
max-line-length = 120
exclude =
venv/*
src/helm/clients/image_generation/dalle_mini/*
src/helm/clients/image_generation/mindalle/*
src/helm/clients/vision_language/open_flamingo/*
# Ignore completely:
# E203 - White space before ':', (conflicts with black)
# E231 - Missing whitespace after ',', ';', or ':'
# E731 - do not assign a lambda expression, use a def
# W503 - line break before binary operator, (conflicts with black)
# W605 - invalid escape sequence '\', (causes failures)
ignore = E203,E231,E731,W503,W605
# Settings for Mypy: static type checker for Python 3
[mypy]
ignore_missing_imports = True
check_untyped_defs = True
# TODO: Remove disable_error_code
disable_error_code = annotation-unchecked
# TODO: Change disallow_untyped_defs to True
disallow_untyped_defs = False
exclude = dalle_mini|mindalle|open_flamingo
[tool:pytest]
addopts =
# By default:
# - we don't test models because doing so will
# make real requests and spend real money
# - we don't test scenarios because these will
# download files, which is slow, consumes disk
# space, and increases the chance of spurious
# test failures due to failed downloads.
#
# For more documentation on pytest markers, see:
# - https://docs.pytest.org/en/latest/how-to/mark.html#mark
# - https://docs.pytest.org/en/latest/example/markers.html#mark-examples
-m 'not models and not scenarios'
markers =
# Marker for model tests that make real model requests
models
# Marker for scenario tests that download files
scenarios