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توضیحات

A package for building and training quantized and binary neural networks with Pytorch

ویژگی	مقدار
سیستم عامل	-
نام فایل	bitorch-0.3.0.dev1
نام	bitorch
نسخه کتابخانه	0.3.0.dev1
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Hasso Plattner Institute
ایمیل نویسنده	fb10-xnor@hpi.de
آدرس صفحه اصلی	https://github.com/hpi-xnor/bitorch
آدرس اینترنتی	https://pypi.org/project/bitorch/
مجوز	-

# BITorch BITorch is a library currently under development to simplify building quantized and binary neural networks with [PyTorch](https://pytorch.org/). This is an early preview version of the library. If you wish to use it and encounter any problems, please create an issue. Our current roadmap contains: - Extending the model zoo with pre-trained models of state-of-the-art approaches - Adding examples for advanced training methods with multiple stages, knowledge distillation, etc. All changes are tracked in the [changelog](https://github.com/hpi-xnor/bitorch/blob/main/CHANGELOG.md). Please refer to [our wiki](https://bitorch.readthedocs.io/en/latest/) for a comprehensive introduction into the library or use the introduction notebook in `examples/notebooks`. ## Installation Similar to recent versions of [torchvision](https://github.com/pytorch/vision), you should be using Python 3.8 or newer. Currently, the only supported installation is pip (a conda package is planned in the future). ### Pip If you wish to use a _specific version_ of PyTorch for compatibility with certain devices or CUDA versions, we advise on installing the corresponding versions of `pytorch` and `torchvision` first (or afterwards), please consult [pytorch's getting started guide](https://pytorch.org/get-started/locally/). Otherwise, simply run: ```bash pip install bitorch ``` Note, that you can also request a specific PyTorch version directly, e.g. for CUDA 11.3: ```bash pip install bitorch --extra-index-url https://download.pytorch.org/whl/cu113 ``` If you want to run the examples install the optional dependencies as well: ```bash pip install "bitorch[opt]" ``` #### Local and Development Install Options The package can also be installed locally for editing and development. First, clone the [repository](https://github.com/hpi-xnor/bitorch), then run: ```bash pip install -e . # without optional dependencies pip install -e ".[opt]" # with optional dependencies ``` ### Dali Preprocessing If you want to use the [Nvidia dali preprocessing library](https://github.com/NVIDIA/DALI), e.g. with CUDA 11.x, (currently only supported for imagenet) you need to install the `nvidia-dali-cuda110` package by running the following command: ``` pip install --extra-index-url https://developer.download.nvidia.com/compute/redist --upgrade nvidia-dali-cuda110 ``` ## Development Install the package and _dev_ requirements locally for development: ```bash pip install -e ".[dev]" ``` ### Tests The tests can be run with [pytest](https://docs.pytest.org/): ```bash pytest ``` ### Code formatting and typing For conveniently checking whether your code suites the required style (more details below), run ```bash ./check-codestyle.sh ``` New code should be compatible with Python 3.X versions and be compliant with PEP8. To check the codebase, please run ```bash flake8 ``` The codebase has type annotations, please make sure to add type hints if required. We use `mypy` for type checking: ```bash mypy --config-file mypy.ini ``` For code formatting we use `black`: ```bash black . --check --verbose --diff --color # check what changes the formatter would do black . # apply the formatter ``` In order to automatically apply the code formatting with every commit, you can also install pre-commit and use the pre-commit hook: ```bash pre-commit install ``` ### Documentation We use [Google's Python Docstring Format](https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html) to document our code. Documentation can be generated with ```bash sphinx-build -b html docs/source/ docs/build/ -a ```

نیازمندی

مقدار	نام
>=1.9.0	torch
>=0.10.0	torchvision
-	matplotlib
-	numpy
-	pandas
-	black
-	build
==4.13.0	importlib-metadata
-	flake8
-	flake8-docstrings
<5	importlib-metadata
~=0.920	mypy
-	myst-nb
==0.5.13	nbclient
==1.3.0	nbsphinx-link
==0.8.8	nbsphinx
-	pep8-naming
-	pre-commit
-	pytest
-	pytest-cov
-	sphinx
-	twine
-	fvbitcore
>=1.8.1	pytorch-lightning
-	sklearn
~=0.12.0	wandb
-	bitorch
-	bitorch-engine

زبان مورد نیاز

مقدار	نام
>=3.7	Python

نحوه نصب

نصب پکیج whl bitorch-0.3.0.dev1:

pip install bitorch-0.3.0.dev1.whl

نصب پکیج tar.gz bitorch-0.3.0.dev1:

pip install bitorch-0.3.0.dev1.tar.gz