معرفی شرکت ها
fastsom-1.0.2
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
A PyTorch and Fastai based implementation of Self-Organizing Maps
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | fastsom-1.0.2 |
| نام | fastsom |
| نسخه کتابخانه | 1.0.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Riccardo Sayn |
| ایمیل نویسنده | riccardo.sayn@kireygroup.com |
| آدرس صفحه اصلی | https://github.com/kireygroup/fastsom |
| آدرس اینترنتی | https://pypi.org/project/fastsom/ |
| مجوز | MIT |
# Fastsom
A PyTorch and Fastai based implementation of Self-Organizing Maps.
You can find documentation and examples [here](https://kireygroup.github.io/fastsom/).
## Contents
- [Fastsom](#fastsom)
- [Contents](#contents)
- [Getting started](#getting-started)
- [Install as a dependency](#install-as-a-dependency)
- [Docker boilerplate](#docker-boilerplate)
- [Prerequisites](#prerequisites)
- [Building the image](#building-the-image)
- [Running the container](#running-the-container)
- [Developing inside the container](#developing-inside-the-container)
- [Documentation setup](#documentation-setup)
- [Documenting the code](#documenting-the-code)
- [Building the docs](#building-the-docs)
- [Deploying the docs on GH Pages](#deploying-the-docs-on-gh-pages)
## Getting started
### Install as a dependency
To install Fastsom, you can use `pip` to install the [PyPi package](https://pypi.org/project/fastsom/):
```bash
pip install fastsom
```
or you can install directly from Github:
```bash
pip install git+ssh://github.com/kireygroup/fastsom
# or
pip install git+https://github.com/kireygroup/fastsom
```
Alternatively, you can clone the repository and then install as follows:
```bash
git clone git@github.com:kireygroup/fastsom
cd fastsom
python setup.py install
```
## Docker boilerplate
This project was bootstrapped with the [cookiecutter-dl-docker](https://github.com/rsayn/cookiecutter-dl-docker) template.
### Prerequisites
To run examples for this project you can either use Docker / Nvidia-Docker or recreate the environment on your local machine by using the provided `requirements.txt`.
Steps for Docker are described below.
### Building the image
An utility script can be found in `bin/build.sh`:
```bash
./bin/build.sh
```
### Running the container
A run script is available:
```bash
./bin/run.sh
```
This will mount the directories `/fastsom` and `/nbs` inside the container, allowing for code changes to be automatically replicated.
Note: if you plan on using Nvidia-Docker, you should use one of the images available on the Nvidia Container Repository.
The container will start a new Jupyter Notebook server on port 8888. Jupyter Lab is also available.
Note that the `fastsom` folder will be mounted inside the container, so any change you make to the source files or notebooks will be replicated on both host and container.
### Developing inside the container
With Visual Studio Code and PyCharm, it is possible to use the container Python interpreter for development.
An SSH server has been configured inside the container to allow connection via PyCharm's remote interpreter feature.
In Visual Studio Code, this can be done via the [Remote - Containers extension](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers).
## Documentation setup
Fastsom's documentation is built with [Sphinx](https://www.sphinx-doc.org/) and deployed to Gihtub Pages via the [`gh-pages` branch](https://github.com/kireygroup/fastsom/tree/gh-pages).
### Documenting the code
We use a Numpy docstring notation (check out [this link](http://www.sphinx-doc.org/en/master/usage/extensions/napoleon.html) for more information about the various docstring styles).
### Building the docs
To generate the static HTML documentation, use the following:
```bash
cd docs
make docs
```
### Deploying the docs on GH Pages
Docs are automatically built from the master branch and pushed to the `gh-pages` branch on each version tag.
نیازمندی
| مقدار | نام |
|---|---|
| >=2.1.5 | fastai |
| - | sklearn |
| - | kmeans-pytorch |
| - | seaborn |
| - | plotly |
| - | fastai-category-encoders |
نحوه نصب
نصب پکیج whl fastsom-1.0.2:
pip install fastsom-1.0.2.whl
نصب پکیج tar.gz fastsom-1.0.2:
pip install fastsom-1.0.2.tar.gz