TorchServant
中文版本 | English Version
TorchServant is still in design and development stage, and more modules may be added. Welcome interested friends to join this project.````
TorchServant is an assembly helping quickly development for PyTorch users. The essential design idea of torchservant is to liberate researchers from tedious repetitions such as save&load checkpoints, make records, manage GPUs, etc. It could help users focus on the core pipelines of design neural networks, including design models, choose hyper-parameters, design loss functions and optimizers, train models, evaluate models, and etc.
Packages
TorchServant contains the following components:
| Package Name | Explaination |
|---|---|
| cfgenator | Configure file generator |
| modelservant | Manage weights files and checkpoints, keep training process continuous. |
| procmonitor | API for visdom and tensorboard, visualize diagrams, illustrations and progresses. |
| stats | Resource statistics on GPUs, memories, cpu, and consumed time. |
| classicmodels | Include AlexNet, VGG, Resnet, Inception, etc. |
| visualfeature | Visualize feature maps during training and evaluation process. |
| weightransfer | An Qt-based visual tool to transfer weights between different models. |
Install
pip install torchservant
