https://github.com/stupidcucumber/robustprinter
Printing package for easy handling data printing 🧑💻
https://github.com/stupidcucumber/robustprinter
deep-learning logging printing python3 training
Last synced: over 1 year ago
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Printing package for easy handling data printing 🧑💻
- Host: GitHub
- URL: https://github.com/stupidcucumber/robustprinter
- Owner: stupidcucumber
- License: mit
- Created: 2024-03-05T19:04:11.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-03-06T07:59:55.000Z (over 2 years ago)
- Last Synced: 2025-02-19T12:53:43.042Z (over 1 year ago)
- Topics: deep-learning, logging, printing, python3, training
- Language: Python
- Homepage:
- Size: 43.9 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
## Prerequisites
To run this package `python3.10` is reccomended. On early stages of developing this project this might not be important, but all further dependencies can require 3.10 version only.
## How to install?
Installing this is simple, just write to the terminal:
```
pip install robustprinter
```
# About
## History
This package was born in desparate search for the tool to conveniently print training information to the console. Altough Tensorflow has its own pre-built printer, which is quite nice, pytorch doesn't have such luxuary. Most of my applications depend on torch and I was tired of tedious print statements around my code that was hard to make beautiful.
Main idea is to incapsulate functionality that I may use across different other applications in one package.
## Usage
Main classes are `Printer` and `Formatter`. Printer regulates what, when and where something must be printed and Formatter regulates how it must be printed. For now package has only `DefaultFormatter` class – child of `Formatter`, and all it does is prints beautifully training info.
To see package in work try this code:
```py
import time
import numpy as np
from robustprinter import Printer, formatter
from robustprinter.formatter import DefaultFormatter
class TestFormatter(formatter.Formatter):
def __init__(self) -> None:
super(TestFormatter, self).__init__()
def format(self, data) -> str:
return data
metrics_list = [
'precision', 'recall', 'mAP50', 'mAP50-95', 'accuracy',
'FID', 'loss'
]
def generate_random_metrics(metrics: list) -> dict:
result = dict()
for metric in metrics:
result[metric] = np.random.rand()
return result
if __name__ == '__main__':
print('Start test.')
max_steps = 10
rformatter = DefaultFormatter(max_columns=2)
rprinter = Printer(formatter=rformatter)
rprinter.start()
data = dict()
for epoch in range(3):
data['epoch'] = epoch
for step in range(max_steps):
data['step'] = step + 1
data['max_steps'] = 10
data['partition'] = 'train'
data['metrics'] = generate_random_metrics(metrics=metrics_list)
rprinter.print(data=data)
time.sleep(1)
rprinter.break_loop()
```
# Examples
## DefaultFormatter
# Contribution
This repository is about designing new formatters and printers. If you have an idea and want to share it – you are welcome!