semvec/pypi-packages huggingface dataset:
tiny-imagenet-torch 0.1.0
TinyImageNet dataset for PyTorch
Requires Python: >=3.6

# tiny-imagenet-torch

A PyTorch-compatible implementation of the TinyImageNet dataset, following the pattern of torchvision datasets like MNIST, FashionMNIST, and CIFAR-10.

## About TinyImageNet

Tiny ImageNet contains 100000 images of 200 classes (500 for each class) downsized to 64×64 colored images. Each class has 500 training images, 50 validation images and 50 test images. More information can be found here: https://paperswithcode.com/dataset/tiny-imagenet. This implementation ingores the unlabeled test images to match the structure of MNIST, FashionMNIST, and CIFAR-10. 

## Installation

```bash
pip install tiny-imagenet-torch
```

Or install from source:

```bash
git clone https://github.com/ligerlac/tiny-imagenet-torch.git
cd tiny-imagenet-torch
pip install -e .
```

## Usage

```python
import torch
from torch.utils.data import DataLoader
from torchvision import transforms
from tiny_imagenet_torch import TinyImageNet

# Simple transformation - just convert to tensor
transform = transforms.ToTensor()

# Create dataset
train_dataset = TinyImageNet(
    root='./data',
    train=True,
    download=True,
    transform=transform
)

test_dataset = TinyImageNet(
    root='./data',
    train=False,
    download=True,
    transform=transform
)

# Create data loaders
train_loader = DataLoader(train_dataset, batch_size=128, shuffle=True, num_workers=4)
test_loader = DataLoader(test_dataset, batch_size=128, shuffle=False, num_workers=4)

# Usage example
for images, labels in train_loader:
    # Your training code here
    pass
```

## Dataset Details

- 200 classes from ImageNet
- 500 training images per class (100,000 total)
- 50 validation images per class (10,000 total)
- All images are 64×64 color images

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Acknowledgments

- The TinyImageNet dataset was created by Stanford for the CS231N course
- The implementation follows torchvision's dataset pattern
python-jenkins-checkmk-retry-parameter 1.8.3.dev8
Python bindings for the remote Jenkins API, custom package until official release
Requires Python: <4.0.0,>=3.10.4

README
======

Python Jenkins is a python wrapper for the `Jenkins <http://jenkins-ci.org/>`_
REST API which aims to provide a more conventionally pythonic way of controlling
a Jenkins server.  It provides a higher-level API containing a number of
convenience functions.

We like to use python-jenkins to automate our Jenkins servers. Here are some of
the things you can use it for:

* Create new jobs
* Copy existing jobs
* Delete jobs
* Update jobs
* Get a job's build information
* Get Jenkins master version information
* Get Jenkins plugin information
* Start a build on a job
* Create nodes
* Enable/Disable nodes
* Get information on nodes
* Create/delete/reconfig views
* Put server in shutdown mode (quiet down)
* List running builds
* Delete builds
* Wipeout job workspace
* Create/delete/update folders [#f1]_
* Set the next build number [#f2]_
* Install plugins
* and many more..

To install::

    $ sudo python setup.py install

Online documentation:

* http://python-jenkins.readthedocs.org/en/latest/

Developers
----------
Bug report:

* https://bugs.launchpad.net/python-jenkins

Repository:

* https://opendev.org/jjb/python-jenkins

Cloning:

* git clone https://opendev.org/jjb/python-jenkins

Patches are submitted via Gerrit at:

* https://review.opendev.org/#/q/project:jjb/python-jenkins

Please do not submit GitHub pull requests, they will be automatically closed.

The python-jenkins developers communicate in the ``#openstack-jjb`` channel
on Freenode's IRC network.

More details on how you can contribute is available on our wiki at:

* https://docs.opendev.org/opendev/infra-manual/latest/developers.html

Writing a patch
---------------

Be sure that you lint code before created an code review.
The easiest way to do this is to install git pre-commit_ hooks.

Installing without setup.py
---------------------------

Then install the required python packages using pip_::

    $ sudo pip install python-jenkins

.. _tox: https://testrun.org/tox
.. _pip: https://pypi.org/project/pip
.. _pre-commit: https://pre-commit.com/#install


.. rubric:: Footnotes

.. [#f1] The free `Cloudbees Folders Plugin
    <https://wiki.jenkins-ci.org/display/JENKINS/CloudBees+Folders+Plugin>`_
    provides support for a subset of the full folders functionality. For the
    complete capabilities you will need the paid for version of the plugin.

.. [#f2] The `Next Build Number Plugin
   <https://wiki.jenkins-ci.org/display/JENKINS/Next+Build+Number+Plugin>`_
   provides support for setting the next build number.