semvec/pypi-packages huggingface dataset:
mnistusps 0.1.0
Revised splits for MNIST-USPS domain adaptation experiments
Requires Python: >=3.6

# Splits for MNIST-USPS domain adaptation experiments

This repository contains the revised split protocol for creating splits for few shot domain adaptation on the MNIST-USPS datasets.

Contrary to often seen splits, we define an independent test split here and only let the train-val split vary according to a user-defined random seed.

## Installation
```bash
pip install mnist-usps
```

## Usage
Getting the splits is a simple as:

```python
from mnistusps import mnistusps

train, val, test = mnistusps(
    source_name = "mnist",
    target_name = "usps",
    seed=1,
    num_source_per_class=200,
    num_target_per_class=3,
    same_to_diff_class_ratio=3,
    image_resize=(240, 240),
    group_in_out=True, # groups data: ((img_s, img_t), (lbl_s, _lbl_t))
    framework_conversion="tensorflow",
    data_path = None, # downloads to "~/data" per default
)
```

The function automatically downloads and unpacks the data using Torchvision internally. It then creates the splits using the [Dataset Ops library](https://github.com/LukasHedegaard/datasetops). 
Depending on your choice of machine learning library, the dataset can be converted to Tensorflow or PyTorch (assuming either is pre-installed) using Dataset Ops.
xlogger 0.0.2
a fast, no dependencies log colorizer. with style formatter.

# Something about xlogger
I'm a python starter, when I learn the logging section, 
I thought that writing the logging format is so 'non-python',
and I have to write the same 'anti-human' codes every where.
Logs are important and should be used more. And in more simple way.

So I checked StackOverflow for some inspiration, and I actually learned some.

Here is the module I made, in fact, it's the first one I wrote that should be
shared at pypi I thought.

Hope you guys enjoy it:)

## Usage
just copy the code, it have no dependencies. this is the way recommended, 
because you can make your own logger customized easily by setting some variables.

or if you want to install
```batch
pip3 install xlogger 
```

then add lines to your code:
```python
from xlogger import xlogger

logger = xlogger.get_my_logger(__name__)
```
and then just use logger as usual.

![](https://github.com/deadlyedge/xlogger/blob/master/static/screenshot1.png)

## Main references
'How can I color Python logging output?'

https://stackoverflow.com/questions/384076/how-can-i-color-python-logging-output

## Thank
Sergey Pleshakov - my code base on your code.