pytext | A natural language modeling framework based on PyTorch | Machine Learning library

by facebookresearch Python Version: v0.3.3 License: Non-SPDX

X-Ray Key Features Code Snippets(3)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | pytext Summary

pytext is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. pytext has no bugs, it has no vulnerabilities, it has build file available and it has high support. However pytext has a Non-SPDX License. You can download it from GitHub.

PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We are using PyText in Facebook to iterate quickly on new modeling ideas and then seamlessly ship them at scale.

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Support

pytext has a highly active ecosystem.

It has 6362 star(s) with 825 fork(s). There are 172 watchers for this library.

It had no major release in the last 12 months.

There are 61 open issues and 74 have been closed. On average issues are closed in 113 days. There are 84 open pull requests and 0 closed requests.

It has a positive sentiment in the developer community.

The latest version of pytext is v0.3.3

Quality

pytext has 0 bugs and 0 code smells.

Security

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

pytext code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pytext has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

pytext releases are available to install and integrate.

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

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

Top functions reviewed by kandi - BETA

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

Compute the embedding
Push an action onto the stack
The LSTM output
LSTM output
Make prediction
Destructure a list of clients
Takes a list of client_batch_batch
Export a pytext model
Quantize the model
Computes metrics for multi - label prediction
Loads logits
Create a TensorFlowModel from a ConfigParser
Compute the loss function
Create a KLDefressor from a task configuration
Calculate the Jacobian for each hypothesis
Process QUAD TSV file
Make a batch of examples
Calculate the metric
Forward forward computation
Compute query
Create a Module from a given tensorizer
Convert tensorflow into Tensorboard
Performs the forward computation
Convert tensorflow into Tensor
Format a Config object
Print the metrics

Get all kandi verified functions for this library.

pytext Key Features

No Key Features are available at this moment for pytext.

pytext Examples and Code Snippets

Persian Document Classification,PyText

Python

Lines of Code : 54

License : No License

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{
  "version": 8,
  "task": {
    "DocumentClassificationTask": {
      "data": {
        "source": {
          "TSVDataSource": {
            "field_names": ["label", "slots", "text"],
            "train_filename": "tests/data/train_data_tiny.tsv",

Facebook最新开源工具pytext实战,pytext实践

Python

Lines of Code : 11

License : No License

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git clone https://dev.aminer.cn/qingsong/pytext_clf
cd pytext_clf

python3 -m venv pytext_venv
source pytext_venv/bin/activate
pip install wheel
pip install pytext-nlp

pytext train < config.json

pytext test < config.json

pytext export --outp

文本分类,8. 参考

Python

Lines of Code : 7

License : No License

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Convolutional Methods for Text: https://weibo.com/1402400261/F4nWcmOMi?sudaref=www.google.com&display=0&retcode=6102&type=comment#_rnd1548677150694

Investigating Capsule Networks with Dynamic Routing for Text Classification: 胶囊网络在文本分类中的应

Community Discussions

Trending Discussions on pytext

Why some methods are recalled as self variables?

How to get the line index of the current line

QUESTION

Why some methods are recalled as self variables?

Asked 2021-Oct-04 at 19:56

Probably a dumb question right here.

I'm new to programming, but from my understanding we need to use nameofthemetod() to recall a method.

I don't understand why sometimes, using a class, this rule is not longer valid and instead we recall it using self.nameofthemethod(). Wasn't the self. supposed to work only for variables?

Here is an example:

...

ANSWER

Answered 2021-Oct-03 at 15:25

Since the methods (like class variables) are defined in a class and as part of the class, they must be referenced as such. When calling update_status() outside of StatusBar, it must be called as StatusBar.update_status(), because it is part of the StatusBar class:

Source https://stackoverflow.com/questions/69423307

QUESTION

How to get the line index of the current line

Asked 2020-Dec-13 at 02:14

I'm making a Test Editor from a base that I got from a YouTube tutorial. I was trying to make highlighted the python's statements, but when I write a statement, it colorizes all the lines, and I thought that the problem is the use of indexes I make.

This is the code:

...

ANSWER

Answered 2020-Dec-13 at 02:14

You works with every line separtelly so you get only X. To get Y you need to enumerate lines:

Source https://stackoverflow.com/questions/65249427

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

Vulnerabilities

No vulnerabilities reported

Install pytext

You can download it from GitHub.
You can use pytext like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.