Contents

torchsummary 1.5.1

0

Model summary in PyTorch similar to `model.summary()` in Keras

Model summary in PyTorch similar to model.summary() in Keras

Stars: 4008, Watchers: 4008, Forks: 413, Open Issues: 138

The sksq96/pytorch-summary repo was created 6 years ago and the last code push was 7 months ago.
The project is very popular with an impressive 4008 github stars!

How to Install torchsummary

You can install torchsummary using pip

pip install torchsummary

or add it to a project with poetry

poetry add torchsummary

Package Details

Author
Shubham Chandel @sksq96
License
Homepage
https://github.com/sksq96/pytorch-summary
PyPi:
https://pypi.org/project/torchsummary/
GitHub Repo:
https://github.com/sksq96/pytorch-summary
No  torchsummary  pypi packages just yet.

Errors

A list of common torchsummary errors.

Code Examples

Here are some torchsummary code examples and snippets.

GitHub Issues

The torchsummary package has 138 open issues on GitHub

  • RuntimeError: Failed to run torchsummary. See above stack traces for more details. Executed layers up to: []
  • Not working on cpu
  • Is not work about 'dict' input?
  • summary error when nn.LSTM(batch_first=True)

See more issues on GitHub

Related Packages & Articles

onnx 1.17.0

Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Currently we focus on the capabilities needed for inferencing (scoring).

livelossplot 0.5.5

Live training loss plot in Jupyter Notebook for Keras, PyTorch and others.

horovod 0.28.1

Horovod is a powerful distributed training framework for Python that allows you to train deep learning models across multiple GPUs and servers quickly and efficiently. It falls under the category of distributed computing libraries. Built on top of TensorFlow, PyTorch, and other popular deep learning frameworks, Horovod simplifies the process of scaling up your model training by handling the complexities of distributed training under the hood.

barbar 0.2.1

Progress bar for deep learning training iterations

pytorch-lightning 2.4.0

PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate.

petastorm 0.12.1

Petastorm is a library enabling the use of Parquet storage from Tensorflow, Pytorch, and other Python-based ML training frameworks.

kornia 0.7.3

Open Source Differentiable Computer Vision Library for PyTorch