torchtools | A High-Level training API on top of PyTorch | Machine Learning library

by Time1ess Python Version: 0.1.4 License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | torchtools Summary

torchtools is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. torchtools has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install torchtools' or download it from GitHub, PyPI.

torchtools is a High-Level training API on top of PyTorch with many useful features to simplifiy the traing process for users. It was developed based on ideas from tnt, Keras. I wrote this tool just want to release myself, since many different training tasks share same training routine(define dataset, retrieve a batch of samples, forward propagation, backward propagation, ...).

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torchtools has a low active ecosystem.

It has 13 star(s) with 1 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

torchtools has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of torchtools is 0.1.4

Quality

torchtools has 0 bugs and 0 code smells.

Security

torchtools has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

torchtools code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

torchtools is licensed under the BSD-3-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

torchtools releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

torchtools saves you 3032 person hours of effort in developing the same functionality from scratch.

It has 6537 lines of code, 149 functions and 63 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed torchtools and discovered the below as its top functions. This is intended to give you an instant insight into torchtools implemented functionality, and help decide if they suit your requirements.

Train the model
Notify registered hooks
Restore state from checkpoint
Validate the model
Sends metrics to the cache
Log the value of a meter
Sends the data to the cache
Calculate the loss function
Compute histogram of the histogram
Register hooks
Register a hook
Unregisters given hooks
Unregisters a hook
Terminate training
Compute the label accuracy score
Run the test
Convert to Tensor

Get all kandi verified functions for this library.

torchtools Key Features

No Key Features are available at this moment for torchtools.

torchtools Examples and Code Snippets

No Code Snippets are available at this moment for torchtools.

Community Discussions

Trending Discussions on torchtools

Subclass of PyTorch dataset class cannot find dataset files

QUESTION

Subclass of PyTorch dataset class cannot find dataset files

Asked 2021-Apr-03 at 22:07

I'm trying to create a subclass of the PyTorch MNIST dataset class, which I call CustomMNISTDataset, as follows:

...

ANSWER

Answered 2021-Apr-03 at 22:07

This requires some source-diving, but your problem is this function. The path to the dataset is dependant on the name of the class, so when you subclass MNIST the root folder changes to /home/psando/CustomMNISTDataset

So if you rename /home/psando/MNIST to /home/psando/CustomMNISTDataset it works.

Source https://stackoverflow.com/questions/66936111

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install torchtools

torchtools has been tested on Python 2.7+, Python 3.5+.

Support

Please feel free to add more features!. If there are any bugs or feature requests please submit an issue, I'll see what I can do. Any new features or bug fixes please submit a PR in Pull requests. If there are any other problems, please email: youchen.du@gmail.com.

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