Text-Classification-Pytorch | Text classification using deep learning models in Pytorch | Natural Language Processing library

by prakashpandey9 Python Version: Current License: MIT

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kandi X-RAY | Text-Classification-Pytorch Summary

Text-Classification-Pytorch is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch, Tensorflow, Neural Network applications. Text-Classification-Pytorch has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However Text-Classification-Pytorch build file is not available. You can download it from GitHub.

This repository contains the implmentation of various text classification models like RNN, LSTM, Attention, CNN, etc in PyTorch deep learning framework along with a detailed documentation of each of the model. Text Classification is one of the basic and most important task of Natural Language Processing. In this repository, I am focussing on one such text classification task and that is Sentiment Analysis. So far I have covered following six different models in this repo.

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Text-Classification-Pytorch has a medium active ecosystem.

It has 783 star(s) with 235 fork(s). There are 20 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 9 have been closed. On average issues are closed in 116 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Text-Classification-Pytorch is current.

Quality

Text-Classification-Pytorch has 0 bugs and 0 code smells.

Security

Text-Classification-Pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Text-Classification-Pytorch code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Text-Classification-Pytorch is licensed under the MIT License. This license is Permissive.

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

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Text-Classification-Pytorch releases are not available. You will need to build from source code and install.

Text-Classification-Pytorch has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

Text-Classification-Pytorch saves you 166 person hours of effort in developing the same functionality from scratch.

It has 413 lines of code, 19 functions and 8 files.

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

Top functions reviewed by kandi - BETA

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

Performs the forward computation
Computes the attention layer
Loads a dataset
Perform the forward computation
Convolution block
Train a model
Clips gradients with clip_value
Compute the LSTM
Compute the attention layer
Evaluate the given model

Get all kandi verified functions for this library.

Text-Classification-Pytorch Key Features

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Text-Classification-Pytorch Examples and Code Snippets

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Community Discussions

Trending Discussions on Text-Classification-Pytorch

Use of PyTorch permute in RCNN

QUESTION

Use of PyTorch permute in RCNN

Asked 2021-Jan-14 at 21:57

I am looking at an implementation of RCNN for text classification using PyTorch. Full Code. There are two points where the dimensions of tensors are permuted using the permute function. The first is after the LSTM layer and before tanh. The second is after a linear layer and before a max pooling layer.

Could you please explain why the permutation is necessary or useful?

Relevant Code

...

ANSWER

Answered 2021-Jan-05 at 05:11

What permute function does is rearranges the original tensor according to the desired ordering, note permute is different from reshape function, because when apply permute, the elements in tensor follow the index you provide where in reshape it's not.

Example code:

Source https://stackoverflow.com/questions/65571264

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

Vulnerabilities

No vulnerabilities reported

Install Text-Classification-Pytorch

Once you clone this repo, run the main.py file to process the dataset and to train the model.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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