GitLocker: The Coding Marketplace

Description:

pytorchmodules 0.3.5

# pytorch_modules
## Introduction
A neural network toolkit built on pytorch/opencv/numpy that includes neural network layers, modules, loss functions, optimizers, data loaders, data augmentation, etc.
## Features

Advanced neural network modules/loss functions/optimizers
Ultra-efficient trainer and dataloader that allows you to take full advantage of GPU

## Installation

sudo pip3 install pytorch_modules

or

sudo python3 setup.py install

## Usage
### pytorch_modules.utils
Includes a variety of utils for pytorch model training.
See [woodsgao/pytorch_segmentation](https://github.com/woodsgao/pytorch_segmentation) as a tutorial.
### pytorch_modules.nn
This module contains a variety of neural network layers, modules and loss functions.

import torch
from pytorch_modules.nn import ResBlock
# NCHW tensor
inputs = torch.ones([8, 8, 224, 224])
block = ResBlock(8, 16)
outputs = block(inputs)

### pytorch_modules.backbones
This module includes a series of modified backbone networks.

import torch
from pytorch_modules.backbones import ResNet
# NCHW tensor
inputs = torch.ones([8, 8, 224, 224])
model = ResNet(32)
outputs = model.stages[0](inputs)

### pytorch_modules.datasets
This module includes a series of dataset classes integrated from pytorch_modules.datasets.BasicDataset which is integrated from torch.utils.data.Dataset .
The loading method of pytorch_modules.datasets.BasicDataset is modified to cache data with LMDB to speed up data loading. This allows your gpu to be fully used for model training without spending a lot of time on data loading and data augmentation.
Please see the corresponding repository for detailed usage.