PyTorchText | 1st Place Solution for Zhihu Machine Learning Challenge | Machine Learning library

by chenyuntc Python Version: Current License: MIT

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kandi X-RAY | PyTorchText Summary

PyTorchText is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Bert, Neural Network applications. PyTorchText has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. However PyTorchText has 13 bugs. You can download it from GitHub.

1st Place Solution for Zhihu Machine Learning Challenge . Implementation of various text-classification models.(知乎看山杯第一名解决方案)

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Quality

Security

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PyTorchText has a medium active ecosystem.

It has 1055 star(s) with 370 fork(s). There are 47 watchers for this library.

It had no major release in the last 6 months.

There are 5 open issues and 8 have been closed. On average issues are closed in 10 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of PyTorchText is current.

Quality

PyTorchText has 13 bugs (12 blocker, 0 critical, 1 major, 0 minor) and 225 code smells.

Security

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

PyTorchText code analysis shows 0 unresolved vulnerabilities.

There are 4 security hotspots that need review.

License

PyTorchText 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

PyTorchText 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, examples and code snippets are available.

PyTorchText saves you 1473 person hours of effort in developing the same functionality from scratch.

It has 3287 lines of code, 165 functions and 54 files.

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

Top functions reviewed by kandi - BETA

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

parse options from kwargs
Compute the prediction .
Performs the forward computation .
Estimate the test dataset .
Calculates the score for the prediction .
Merge two files together .
initialize training data
merges two files together
Create a Word2Vec model .
Evaluate a single test .

Get all kandi verified functions for this library.

PyTorchText Key Features

No Key Features are available at this moment for PyTorchText.

PyTorchText Examples and Code Snippets

No Code Snippets are available at this moment for PyTorchText.

Community Discussions

Trending Discussions on PyTorchText

How to make prediction from train Pytorch and PytorchText model?

QUESTION

How to make prediction from train Pytorch and PytorchText model?

Asked 2019-Nov-01 at 07:56

General speaking, after I have successfully trained a text RNN model with Pytorch, using PytorchText to leverage data loading on an origin source, I would like to test with other data sets (a sort of blink test) that are from different sources but the same text format.

First I defined a class to handle the data loading.

...

ANSWER

Answered 2019-Oct-29 at 19:25

What I need are

to keep TEXT in load_data and reuse in load_data_but_error by assigning to class variables
add train=True to object data.BucketIterator on load_data_but_error function

Source https://stackoverflow.com/questions/58613467

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

Vulnerabilities

No vulnerabilities reported

Install PyTorchText

You may need tf.contrib.keras.preprocessing.sequence.pad_sequences for data preprocessing.
install PyTorch from pytorch.org (Python 2, CUDA)
install other depencies: pip2 install -r requirements.txt
start visdom for visualization: python2 -m visdom.server

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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