Metadata-Version: 2.1
Name: pytorch-argus
Version: 1.0.0
Summary: Argus is a lightweight library for training neural networks in PyTorch.
Home-page: https://github.com/lRomul/argus
Author: Ruslan Baikulov
Author-email: ruslan1123@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

<div align="center">

![argus-logo](https://raw.githubusercontent.com/lRomul/argus/master/assets/logo/argus_logo_white.png)

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</div>

Argus is a lightweight library for training neural networks in PyTorch.

## Documentation

https://pytorch-argus.readthedocs.io

## Installation

Requirements: 
* torch>=1.1.0

From pip:

```bash
pip install pytorch-argus
```

From source:

```bash
pip install -U git+https://github.com/lRomul/argus.git
```

## Example

Simple image classification example with `create_model` from [pytorch-image-models](https://github.com/rwightman/pytorch-image-models):

```python
from torchvision.datasets import MNIST
from torch.utils.data import DataLoader
from torchvision.transforms import Compose, ToTensor, Normalize

import timm

import argus
from argus.callbacks import MonitorCheckpoint, EarlyStopping, ReduceLROnPlateau


def get_data_loaders(batch_size):
    data_transform = Compose([ToTensor(), Normalize((0.1307,), (0.3081,))])
    train_mnist_dataset = MNIST(download=True, root="mnist_data",
                                transform=data_transform, train=True)
    val_mnist_dataset = MNIST(download=False, root="mnist_data",
                              transform=data_transform, train=False)
    train_loader = DataLoader(train_mnist_dataset,
                              batch_size=batch_size, shuffle=True)
    val_loader = DataLoader(val_mnist_dataset,
                            batch_size=batch_size * 2, shuffle=False)
    return train_loader, val_loader


class TimmModel(argus.Model):
    nn_module = timm.create_model


if __name__ == "__main__":
    train_loader, val_loader = get_data_loaders(batch_size=256)

    params = {
        'nn_module': {
            'model_name': 'tf_efficientnet_b0_ns',
            'pretrained': False,
            'num_classes': 10,
            'in_chans': 1,
            'drop_rate': 0.2,
            'drop_path_rate': 0.2
        },
        'optimizer': ('Adam', {'lr': 0.01}),
        'loss': 'CrossEntropyLoss',
        'device': 'cuda'
    }

    model = TimmModel(params)

    callbacks = [
        MonitorCheckpoint(dir_path='mnist', monitor='val_accuracy', max_saves=3),
        EarlyStopping(monitor='val_accuracy', patience=9),
        ReduceLROnPlateau(monitor='val_accuracy', factor=0.5, patience=3)
    ]

    model.fit(train_loader,
              val_loader=val_loader,
              num_epochs=50,
              metrics=['accuracy'],
              callbacks=callbacks,
              metrics_on_train=True)
```

More examples you can find [here](https://pytorch-argus.readthedocs.io/en/latest/examples.html).


## Why this name, Argus?

The library name is a reference to a planet from World of Warcraft. 
Argus is the original homeworld of the eredar (a race of supremely talented magic-wielders), now located within the Twisting Nether. 
It was once described as a utopian world whose inhabitants were both vastly intelligent and highly gifted in magic. 
It has since been twisted by demonic, chaotic energies and became the stronghold and homeworld of the Burning Legion.


