Text-Classification-PyTorch | Text classification tutorial by PyTorch | Machine Learning library

by WiseDoge Python Version: Current License: MIT

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

kandi X-RAY | Text-Classification-PyTorch Summary

Text-Classification-PyTorch is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. Text-Classification-PyTorch has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Text classification tutorial by PyTorch.

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Text-Classification-PyTorch has a low active ecosystem.

It has 6 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

Text-Classification-PyTorch has no issues reported. 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.

Reuse

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

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

Installation instructions are available. Examples and code snippets are not available.

It has 571 lines of code, 56 functions and 8 files.

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

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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

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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

Install all the required package. Download pre-trained word vectors(Optional).
Install all the required package. $ cd Text-Classification-PyTorch $ pip install -r requirements.txt
Download dataset. $ wget http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz $ tar -zxvf aclImdb_v1.tar.gz
Download pre-trained word vectors(Optional). $ wget http://nlp.stanford.edu/data/glove.6B.zip $ unzip glove.6B.zip -d glove
Initialize data. $ python initialize.py Or use $ python initialize.py -h for help.
Train. $ python train.py Or use $ python train.py -h for help.
Evaluation. $ python eval.py Or use $ python eval.py -h for help.
Check evaluation results. Open --name file to view PR curve.

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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