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Rename to Torchhd
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‎.github/workflows/publish.yml‎

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# This workflow will upload a Python Package using Twine when a release is created
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# For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries
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# This workflow uses actions that are not certified by GitHub.
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# They are provided by a third-party and are governed by
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# separate terms of service, privacy policy, and support
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# documentation.
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name: Publish
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on:
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- name: Publish distribution to PyPI
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uses: pypa/gh-action-pypi-publish@master
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with:
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password: ${{ secrets.PYPI_PASSWORD }}
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password: ${{ secrets.PYPI_TOKEN }}
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anaconda:
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runs-on: ubuntu-latest

‎README.md‎

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<p align="center">
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<a href="https://github.com/mikeheddes/hdc-lib/blob/main/LICENSE"><img alt="GitHub license" src="https://img.shields.io/badge/license-MIT-orange.svg?style=flat" /></a>
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<a href="https://pypi.org/project/hdc/"><img alt="pypi version" src="https://img.shields.io/pypi/v/hdc.svg?style=flat&color=orange" /></a>
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<a href="https://anaconda.org/mikeheddes/hdc"><img alt="conda version" src="https://img.shields.io/conda/v/mikeheddes/hdc?label=conda&style=flat&color=orange" /></a>
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<a href="https://github.com/mikeheddes/hdc-lib/actions/workflows/test.yml?query=branch%3Amain"><img alt="tests status" src="https://img.shields.io/github/workflow/status/mikeheddes/hdc-lib/Testing/main?label=tests&style=flat" />
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<a href="https://github.com/hyperdimensional-computing/torchhd/blob/main/LICENSE"><img alt="GitHub license" src="https://img.shields.io/badge/license-MIT-orange.svg?style=flat" /></a>
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<a href="https://pypi.org/project/torchhd/"><img alt="pypi version" src="https://img.shields.io/pypi/v/torchhd.svg?style=flat&color=orange" /></a>
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<a href="https://anaconda.org/torchhd/torchhd"><img alt="conda version" src="https://img.shields.io/conda/v/torchhd/torchhd?label=conda&style=flat&color=orange" /></a>
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<a href="https://github.com/hyperdimensional-computing/torchhd/actions/workflows/test.yml?query=branch%3Amain"><img alt="tests status" src="https://img.shields.io/github/workflow/status/hyperdimensional-computing/torchhd/Test/main?label=tests&style=flat" />
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</a><img alt="PRs Welcome" src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat" />
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</p>
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<div align="center">
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<a href="https://mikeheddes.github.io/hdc-lib">
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<img width="380px" alt="Torchhd logo" src="./resources/torchhd-logo.svg" />
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<a href="https://github.com/hyperdimensional-computing/torchhd">
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<img width="380px" alt="Torchhd logo" src="https://raw.githubusercontent.com/hyperdimensional-computing/torchhd/main/resources/torchhd-logo.svg" />
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</a>
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</div>
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# [Torchhd](https://mikeheddes.github.io/hdc-lib)
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# Torchhd
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Torchhd is a Python library for Hyperdimensional Computing.
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```
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```bash
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conda install -c mikeheddes hdc
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conda install -c torchhd torchhd
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```
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## Documentation
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You can find documentation for Torchhd [on the website](https://mikeheddes.github.io/hdc-lib).
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You can find documentation for Torchhd [on the website](https://hyperdimensional-computing.github.io/torchhd/).
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## Examples
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We have several examples [in the repository](/examples/). Here is a simple one to get you started:
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We have several examples [in the repository](https://github.com/hyperdimensional-computing/torchhd/tree/main/examples). Here is a simple one to get you started:
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```python
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import torch
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### Creating a New Release
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- A GitHub release triggers a GitHub action that builds the library and publishes it to PyPi and Conda in addition to the documentation website.
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- Before creating a new GitHub release, increment the version number in [setup.py](/setup.py) using [semantic versioning](https://semver.org).
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- Before creating a new GitHub release, increment the version number in [setup.py](https://github.com/hyperdimensional-computing/torchhd/blob/main/setup.py) using [semantic versioning](https://semver.org).
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- When creating a new GitHub release, set the tag to be "v{version number}", e.g., v1.5.2, and provide a clear description of the changes.
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### License
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This library is [MIT licensed](./LICENSE).
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This library is [MIT licensed](https://github.com/hyperdimensional-computing/torchhd/blob/main/LICENSE).

‎conda/meta.yaml‎

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{% set data = load_setup_py_data() %}
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package:
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name: hdc
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name: torchhd
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version: {{ data['version'] }}
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source:
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test:
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imports:
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- hdc
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- hdc.datasets
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- torchhd
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- torchhd.datasets
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about:
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home: {{ data['url'] }}

‎docs/index.rst‎

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Welcome to hdc's documentation!
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Welcome to the Torchhd documentation!
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===============================
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*hdc* is a Python library dedicated to Hyperdimensional Computing and the operations related to it.
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*Torchhd* is a Python library dedicated to Hyperdimensional Computing and the operations related to it.
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.. toctree::
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:maxdepth: 2

‎hdc/__init__.py‎

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‎hdc/datasets/__init__.py‎

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‎setup.py‎

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from setuptools import setup, find_packages
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setup(
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name="hdc",
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version="0.5.7",
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description="Python library for Hyperdimensional Computing",
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name="torchhd",
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version="0.6.0",
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description="Torchhd is a Python library for Hyperdimensional Computing",
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long_description=open("README.md").read(),
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long_description_content_type="text/markdown",
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url="https://github.com/mikeheddes/hdc-lib",
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url="https://github.com/hyperdimensional-computing/torchhd",
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license="MIT",
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install_requires=open("requirements.txt").readlines(),
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packages=find_packages(exclude=["docs", "hdc.tests", "examples"]),
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packages=find_packages(exclude=["docs", "torchhd.tests", "examples"]),
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python_requires=">=3.6, <4",
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project_urls={
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"Source": "https://github.com/mikeheddes/hdc-lib/",
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"Documentation": "https://mikeheddes.github.io/hdc-lib/",
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"Source": "https://github.com/hyperdimensional-computing/torchhd",
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"Documentation": "https://hyperdimensional-computing.github.io/torchhd/",
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},
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)

‎torchhd/__init__.py‎

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import torchhd.functional as functional
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import torchhd.embeddings as embeddings
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import torchhd.datasets as datasets
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__all__ = [
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"functional",
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"embeddings",
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"datasets",
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]

‎torchhd/datasets/__init__.py‎

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from torchhd.datasets.beijing_air_quality import BeijingAirQuality
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from torchhd.datasets.isolet import ISOLET
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from torchhd.datasets.european_languages import EuropeanLanguages
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from torchhd.datasets.ucihar import UCIHAR
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from torchhd.datasets.airfoil_self_noise import AirfoilSelfNoise
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from torchhd.datasets.emg_hand_gestures import EMGHandGestures
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from torchhd.datasets.pamap import PAMAP
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from torchhd.datasets.ccpp import CyclePowerPlant
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__all__ = [
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"BeijingAirQuality",
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"ISOLET",
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"EuropeanLanguages",
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"UCIHAR",
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"AirfoilSelfNoise",
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"EMGHandGestures",
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"PAMAP",
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"CyclePowerPlant",
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]

‎hdc/datasets/airfoil_self_noise.py‎ renamed to ‎torchhd/datasets/airfoil_self_noise.py‎

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import os
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import os.path
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from typing import Callable, Optional, Tuple, List
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from typing import Callable, Optional, Tuple
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import torch
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import pandas as pd
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from torch.utils import data
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import math
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from .utils import download_file, unzip_file
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import pandas as pd
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from .utils import download_file
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class AirfoilSelfNoise(data.Dataset):

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