semvec/pypi-packages huggingface dataset:
tensorboard-projects 0.0.1rc10
Tensorboard Projects: A management UI for Tensorboard runs
License: MIT
Requires Python: >=2.7,!= 3.0.*,!= 3.1.*,!= 3.2.*,!= 3.3.*,!= 3.4.*,!= 3.5.*

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# TensorBoard Projects


**Management UI for Tensorboard Dashboards**

[![GitHub license](https://img.shields.io/github/license/jverre/tensorboard-projects)](https://img.shields.io/github/license/jverre/tensorboard-projects)
![](https://github.com/jverre/tensorboard-projects/workflows/CI/badge.svg)


</div>

---

TensorBoard is a powerful visualization tool when building machine learning models. However it can quickly become quite unwieldy as the number of model versions and runs increases.


## What is TensorBoard Projects
TensorBoard Projects provides a UI to manage Tensorboard runs and allows you to easily:
* Visualize runs for a given model
* Archive Runs
* Delete Runs
* Add metadata to individual runss
* Start TensorBoard dashboard for a subset of model runs
* Write documentation for a model

As the project is still very much in development, please report any issues or features you would like to see added !

![Demo](https://raw.githubusercontent.com/jverre/tensorboard-projects/main/docs/tensorboard_projects_demo_v2.gif)

## What TensorBoard Projects isn't
**TensorBoard projects is not an experiment tracking solution**, it simply allows you to better manage TensorBoard runs.

If you are looking for a fully fledgeed experiment tracking solution, you can look into:
* [ClearML](https://www.clear.ml/)
* [Comet](https://www.comet.ml/site/)
* [MLFlow](https://www.mlflow.org/)
* [Weights and Biases](https://wandb.ai/site)
and others

## Using TensorBoard Projects
Tensorboard Projects can be installed from PyPI using `pip install tensorboard-projects`.

Once Tensorboard Projects is installed, you can start the UI using:
```
tensorboard-projects ui
```

In order to assist with running this on a remote machine, the following arguments are supported:
* `--backend-store-uri`: Storage location of metadata, defaults to `~/.tensorboard_projects`
* `--ip`: Host for the API, use 0.0.0.0 to access from a remote machine
* `--port`: Port to run UI on
remote machien
Abjad 3.2
Abjad is a Python API for building LilyPond files.
License: MIT
Keywords: music,music composition,music notation,lilypond

Abjad 3.2
=========

Abjad helps composers build up complex pieces of music notation in iterative and incremental ways. Use Abjad to create a symbolic representation of all the notes, rests, chords, tuplets, beams and slurs in any score. Because Abjad extends the Python programming language, you can use Abjad to make systematic changes to music as you work. Because Abjad wraps the LilyPond music notation package, you can use Abjad to control the typographic detail of symbols on the page.

..  image:: https://img.shields.io/travis/Abjad/abjad/master.svg?style=flat-square
    :target: https://travis-ci.org/Abjad/abjad

..  image:: https://img.shields.io/pypi/v/abjad.svg?style=flat-square
    :target: https://pypi.python.org/pypi/abjad

..  image:: https://img.shields.io/pypi/dm/abjad.svg?style=flat-square
    :target: https://pypi.python.org/pypi/abjad

..  image:: https://img.shields.io/badge/code%20style-black-000000.svg
    :target: https://github.com/ambv/black

----

Abjad's documentation is available here: https://abjad.github.io

Abjad's install instructions are tested on macOS and Linux.

Abjad requires Python 3.6 or later:

..  code-block::

    ~$ python --version
    Python 3.9.0

Make sure LilyPond is installed: http://lilypond.org/development.html

Make sure LilyPond is callable from the commandline:

..  code-block::

    $ lilypond --version
    GNU LilyPond 2.21.82

    Copyright (c) 1996--2020 by
    Han-Wen Nienhuys <hanwen@xs4all.nl>
    Jan Nieuwenhuizen <janneke@gnu.org>
    and others.

    This program is free software.  It is covered by the GNU General Public
    License and you are welcome to change it and/or distribute copies of it
    under certain conditions.  Invoke as `lilypond --warranty' for more
    information.

Create a Python 3 virtual environment for Abjad: https://docs.python.org/3/tutorial/venv.html

Activate the virtual environment and then use pip to install Abjad:

..  code-block::

    ~$ python -m pip install abjad

Start Python, import Abjad, start making music notation:

..  code-block::

    ~$ python
    Python 3.9.0 (v3.9.0:9cf6752276, Oct  5 2020, 11:29:23) 
    [Clang 6.0 (clang-600.0.57)] on darwin
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import abjad
    >>> note = abjad.Note("c'4")
    >>> abjad.show(note)

..  image:: hello.png

----

Join the Abjad community: https://abjad.github.io/appendices/community.html