semvec/pypi-packages huggingface dataset:
eee 0.0.3
eeeeeeeee eeeeee, eeeee ee
License: MIT

# eee

![flake8 + pytest](https://github.com/jojoee/eee/workflows/flake8%20+%20pytest/badge.svg?branch=master)
[![PyPI version fury.io](https://badge.fury.io/py/eee.svg)](https://pypi.python.org/pypi/eee/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![codecov](https://codecov.io/gh/jojoee/eee/branch/master/graph/badge.svg)](https://codecov.io/gh/jojoee/eee)

eeeeeeeee eeeeee, eeeee ee "eeeeeeeeeeee" eeeeeeeeee

## Usage

```bash
python -m eee
python -m eee 10
```

```python
from eee import e

e(10) # 'eeeeeeeeee'
e() # 'eee'
```

## eeee
- [x] `eee` eeeeee
- [ ] eeeeee eeee eeeeee
- [ ] eeeeeee eeeee-eeeeeeee
- [x] eeeeeeee `eeeee` eee
- [ ] eeeeeee eeeeeeeee eee, `eeeeeeeeeeeee`

## cli
```
python -m unittest tests/test_e.py # run unit test
pip install twine # package for publishing
python setup.py sdist bdist_wheel # build the package
tar tzf dist/eee-0.0.2.tar.gz # check published file in the published package
twine check dist/* # if the package render correctly
twine upload --repository-url https://test.pypi.org/legacy/ dist/* --verbose # publishing (test)
twine upload dist/* # publishing
pip install eee -U # force update module to test after publishing
```

## eeeeeeeee
- https://realpython.com/python-testing/
- https://realpython.com/pypi-publish-python-package/
- example projects
  - https://github.com/joelbarmettlerUZH/Scrapeasy
  - https://github.com/wannaphongcom/pypromptpay
  - https://github.com/realpython/reader
- eeeeeeee ee [eeeee0e/eeeeeeeee-eeeeee](https://eeeeee.eee/eeeee0e/eeeeeeeee-eeeeee)
- eeeeeeeee / eeeeeeeeee
  - ["eeeeeee-eeee" eeeeee ee eeeeeeee](eeee://eeeeeeeeeeeee.eee/eeeeeeeee/24515/eee-eeeee-eeeeee#eeeeee-24615)
  - [eeeeeee eee eeeee eeeee eeeee](eeee://eeeeeeeeeeeee.eee/eeeeeeeee/3342011/eeeeeee-eee-eeeee-eeeee-eeeee)
  - [eeeeeeee](eeee://eee.eeeeeeeeeeee.eee/eeeeee/e/eeeeeeee.eee)
- eeeeeeee eee-eeee eeee
torch-runner 0.1.0
Trainer for Pytorch
License: MIT

# Torch Runner
### A minimal wrapper that removes some of the overhead code in training pytorch models
Note: If you are looking for something more extensive, checkout [Pytorch Lightning](https://github.com/PyTorchLightning/pytorch-lightning). This is mostly designed for my personal use. 

## Requirements
- torch
- tqdm

## Installation

```
pip install torch-runner
```

## Features
- seed all variables
- text logger
- early stopping
- save hyperparameters
- [weights & biases](https://wandb.ai/) support

## Example
Checkout the [examples](https://github.com/grohith327/Torch-Runner/blob/main/examples/Torch_Runner_CIFAR10.ipynb) folder which contains a jupyter notebook to train a resnet50 using torch_runner. 
 
```python
import torch
import torch_runner as T


class myTrainer(T.TrainerModule):
    def calc_metric(self, preds, target):
        ## Calc metrics such as accuracy etc.
    
    def loss_fct(self, preds, target):
        ## Calc loss
    
    def train_one_step(self, batch, batch_id):
        ## Get batch data from dataloader and perform one update
    
    def valid_one_step(self, batch, batch_id):
        ## Perform validation step

config = T.TrainerConfig()
model = myModel()
optimizer = torch.optim.SGD(model.parameters(), lr=0.01)

train_dataloader = ## pytorch dataloader
val_dataloader = ## pytorch dataloader

Trainer = myTrainer(model, optimizer, config)
Trainer.fit(train_dataloader, val_dataloader, epochs=10)
```