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docs: update README, remove scripts (#110)
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README.md

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[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
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[![Python 3.11](https://img.shields.io/badge/python-3.11%20%7C%203.12%20%7C%203.13-blue)](https://www.python.org/downloads/release/python-3110/)
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[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit)](https://github.com/pre-commit/pre-commit)
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[![Tests and Linters](https://github.com/instadeepai/mlipaudit/actions/workflows/tests_and_linters.yaml/badge.svg?branch=main)](https://github.com/instadeepai/mlipaudit/actions/workflows/tests_and_linters.yaml)
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![badge](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/mlipbot/e7c79b17c0a9d47bc826100ef880a16f/raw/pytest-coverage-comment.json)
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[![Tests and Linters 🧪](https://github.com/instadeepai/mlipaudit/actions/workflows/tests_and_linters.yaml/badge.svg?branch=main)](https://github.com/instadeepai/mlipaudit/actions/workflows/tests_and_linters.yaml)
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## ⚠️ Disclaimer
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documentation for details on the available functions.
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You can use these functions to build your own benchmarking script and GUI pages for our
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app. For inspiration, we recommend to take a look at the main scripts for
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these tools in this repo, located at `src/mlipaudit/main.py` and
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`src/mlipaudit/app.py`, respectively.
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app. For inspiration, we recommend to take a look at the main script located
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at `src/mlipaudit/main.py` and the implementation of the GUI located at
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`src/mlipaudit/app.py`.
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## 🤗 Data
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To work directly in this repository, run
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```bash
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uv sync --all-groups
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uv sync --extra cuda
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```
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to set up the environment, as this repo uses [uv](https://docs.astral.sh/uv/) for
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package and dependency management.
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This command installs all dependency groups. We recommend to check out
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the `pyproject.toml` file for information on the available groups. Most notably,
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the group `cuda` installs the GPU-ready version of JAX which are strongly recommended.
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If you do not want to install the `cuda` dependency group (for example, because you are
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on MacOS that does not support this standard installation), you can use the
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`--no-group cuda` option in the [uv](https://docs.astral.sh/uv/) command.
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This command installs the main and dev dependency groups. We recommend to check out
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the `pyproject.toml` file for more information. Furthermore,
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the extra `cuda` installs the GPU-ready version of JAX which is strongly recommended.
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If you do not want to install the `cuda` extra (for example, because you are
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on MacOS that does not support this standard installation), you can omit the
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`--extra cuda` option in the [uv](https://docs.astral.sh/uv/) command.
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When adding new benchmarks, make sure that the following key pieces are added
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for each one:
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* The benchmark implementation (with unit tests)
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* The benchmark UI page (add to existing generic unit test for UI pages)
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* The benchmark documentation
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* A function in `scripts/fetch_element_types.py` that yields the list of elements
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required for the benchmark given the benchmark data
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For the documentation, you can run the following to build a version of it locally
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to view your changes:
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More information on adding new benchmarks can be found
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[here](https://instadeepai.github.io/mlipaudit/tutorials/new_benchmark/)
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in our documentation.
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To build a version of the code documentation locally to view your changes, you can run:
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```commandline
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uv run sphinx-build -b html docs/source docs/build/html

pyproject.toml

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"pytest-cov>=6.2.1",
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"sphinx-subfigure>=0.2.4",
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]
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scripts = [
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"requests>=2.32.4",
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]
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# Omitting files related to CLI from test coverage
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[tool.coverage.run]

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