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+ extras["codecarbon"]
+ extras["accelerate"]
+ extras["video"]
)
extras["docs_specific"] = deps_list(
"docutils",
"myst-parser",
"sphinx",
"sphinx-markdown-tables",
"sphinx-rtd-theme",
"sphinx-copybutton",
"sphinxext-opengraph",
"sphinx-intl",
"sphinx-multiversion",
)
# "docs" needs "all" to resolve all the references
extras["docs"] = extras["all"] + extras["docs_specific"]
extras["dev-torch"] = (
extras["testing"]
+ extras["torch"]
+ extras["sentencepiece"]
+ extras["tokenizers"]
+ extras["torch-speech"]
+ extras["vision"]
+ extras["integrations"]
+ extras["timm"]
+ extras["codecarbon"]
+ extras["quality"]
+ extras["ja"]
+ extras["docs_specific"]
+ extras["sklearn"]
+ extras["modelcreation"]
+ extras["onnxruntime"]
)
extras["dev-tensorflow"] = (
extras["testing"]
+ extras["tf"]
+ extras["sentencepiece"]
+ extras["tokenizers"]
+ extras["vision"]
+ extras["quality"]
+ extras["docs_specific"]
+ extras["sklearn"]
+ extras["modelcreation"]
+ extras["onnx"]
+ extras["tf-speech"]
)
extras["dev"] = (
extras["all"]
+ extras["testing"]
+ extras["quality"]
+ extras["ja"]
+ extras["docs_specific"]
+ extras["sklearn"]
+ extras["modelcreation"]
)
extras["torchhub"] = deps_list(
"filelock",
"huggingface-hub",
"importlib_metadata",
"numpy",
"packaging",
"protobuf",
"regex",
"requests",
"sentencepiece",
"torch",
"tokenizers",
"tqdm",
)
# when modifying the following list, make sure to update src/transformers/dependency_versions_check.py
install_requires = [
deps["importlib_metadata"] + ";python_version<'3.8'", # importlib_metadata for Python versions that don't have it
deps["filelock"], # filesystem locks, e.g., to prevent parallel downloads
deps["huggingface-hub"],
deps["numpy"],
deps["packaging"], # utilities from PyPA to e.g., compare versions
deps["pyyaml"], # used for the model cards metadata
deps["regex"], # for OpenAI GPT
deps["requests"], # for downloading models over HTTPS
deps["tokenizers"],
deps["tqdm"], # progress bars in model download and training scripts
]
setup(
name="adapter-transformers",
version="3.2.1",
author="Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, Hannah Sterz, Leon Engländer, based on work by the HuggingFace team and community",
author_email="pfeiffer@ukp.tu-darmstadt.de",
description="A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models",
long_description=open("README.md", "r", encoding="utf-8").read(),
long_description_content_type="text/markdown",
keywords="NLP deep learning transformer pytorch BERT adapters",
license="Apache",
url="https://github.com/adapter-hub/adapter-transformers",
package_dir={"": "src"},