Skip to main content

pytorch❤️keras

Project description

Pytorch❤️Keras

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

torchkeras ❤️ wandb: https://wandb.ai/lyhue1991/mnist_torchkeras


Open In Kaggle

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()) a metrics_dict parameter is optional.

(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")

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

Besides the basic torchkeras.KerasModel, another powerful class torchkeras.LightModel is created to support pytorch_lightning training style.

The KerasModel is much simpler, and is recommended for beginner users.

The LightModel borrows many features from the library pytorch_lightning and shows a best practice.

Although different, the usage of torchkeras.KerasModel and torchkeras.LightModel is very similar.

features torchkeras.KerasModel 🔥🔥🔥 torchkeras.LightModel
progress bar
early stopping
metrics from torchmetrics
gpu training
multi-gpus training(ddp)
tensorboard callback
pretty wandb callback
other callbacks from pytorch_lightning
simple code

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
Open In Kaggle

②kerasmodel wandb 🔥🔥🔥 torchkeras.KerasModel with wandb demo
Open In Kaggle

③kerasmodel tunning 🔥🔥🔥 torchkeras.KerasModel with wandb sweep demo
Open In Kaggle

④kerasmodel tensorboard torchkeras.KerasModel with tensorboard example
⑤kerasmodel ddp/tpu torchkeras.KerasModel ddp tpu examples
Open In Kaggle

⑥lightmodel basic torchkeras.LightModel example
⑦lightmodel tensorboard torchkeras.LightModel with tensorboard example

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:

算法美食屋

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

torchkeras-3.8.0.tar.gz (7.4 MB view details)

Uploaded Source

Built Distribution

torchkeras-3.8.0-py3-none-any.whl (7.4 MB view details)

Uploaded Python 3

File details

Details for the file torchkeras-3.8.0.tar.gz.

File metadata

  • Download URL: torchkeras-3.8.0.tar.gz
  • Upload date:
  • Size: 7.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.0

File hashes

Hashes for torchkeras-3.8.0.tar.gz
Algorithm Hash digest
SHA256 b7683df9c7fb6bc5798a520006d1568f3df72cfcdc60948de5bf233b852a72a2
MD5 a7a820d71e016b869553a26879351e29
BLAKE2b-256 0f1e1120a5cb0915cc1e81466c940c1227dde91657cfd008c1700ec3e0097649

See more details on using hashes here.

File details

Details for the file torchkeras-3.8.0-py3-none-any.whl.

File metadata

  • Download URL: torchkeras-3.8.0-py3-none-any.whl
  • Upload date:
  • Size: 7.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.0

File hashes

Hashes for torchkeras-3.8.0-py3-none-any.whl
Algorithm Hash digest
SHA256 c71e7c53c9de18bd3bee6f9b20838312945cc2e931522f85866fc9f72466ec0a
MD5 80b8f5368a104856183ddbabe5db2a5e
BLAKE2b-256 49d20cd17f58cae8fbf451a3738290b9b98843e17b6590cc1ab31fb4799cc039

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page