torchkeras 3.8.5

pytorch❤️keras

Pytorch❤️Keras

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The torchkeras library is a simple tool for training neural network in pytorch jusk in a keras style. 😋😋

1, Introduction

With torchkeras, You need not to write your training loop with many lines of code, all you need to do is just

like these two steps as below:

(i) create your network and wrap it and the loss_fn together with torchkeras.KerasModel like this: model = torchkeras.KerasModel(net,loss_fn=nn.BCEWithLogitsLoss()).

(ii) fit your model with the training data and validate data.

The main code of use torchkeras is like below.

import torch 
import torchkeras

#use torchkeras.KerasModel 
model = torchkeras.KerasModel(net,
                              loss_fn = nn.BCEWithLogitsLoss(),
                              optimizer= torch.optim.Adam(net.parameters(),lr = 0.001),
                              metrics_dict = {"acc":torchmetrics.Accuracy(task='binary')}
                             )
dfhistory=model.fit(train_data=dl_train, 
                    val_data=dl_val, 
                    epochs=20, 
                    patience=3, 
                    ckpt_path='checkpoint.pt',
                    monitor="val_acc",
                    mode="max",
                    plot = True
                   )

This project seems somehow powerful, but the source code is very simple.

Actually, only about 200 lines of Python code.

If you want to understand or modify some details of this project, feel free to read and change the source code!!!

2, Features

The main features supported by torchkeras are listed below.

Versions when these features are introduced and the libraries which they used or inspired from are given.

features	supported from version	used or inspired by library
✅ training progress bar	3.0.0	use tqdm,inspired by keras
✅ training metrics	3.0.0	inspired by pytorch_lightning
✅ notebook visualization in traning	3.8.0	inspired by fastai
✅ early stopping	3.0.0	inspired by keras
✅ gpu training	3.0.0	use accelerate
✅ multi-gpus training(ddp)	3.6.0	use accelerate
✅ fp16/bf16 training	3.6.0	use accelerate
✅ tensorboard callback	3.7.0	use tensorboard
✅ wandb callback	3.7.0	use wandb

3, Basic Examples

You can follow these full examples to get started with torchkeras.

Have fun!😋😋

example	read notebook code	run example in kaggle
①kerasmodel basic 🔥🔥	torchkeras.KerasModel example
②kerasmodel wandb 🔥🔥🔥	torchkeras.KerasModel with wandb demo
③kerasmodel tunning 🔥🔥🔥	torchkeras.KerasModel with wandb sweep demo
④kerasmodel tensorboard	torchkeras.KerasModel with tensorboard example
⑤kerasmodel ddp/tpu	torchkeras.KerasModel ddp tpu examples

If you want to understand or modify some details of this project, feel free to read and change the source code!!!

Any other questions, you can contact the author form the wechat official account below:

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