TP-Transformer | repository contains the source code | Machine Learning library

by ischlag Python Version: Current License: MIT

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

kandi X-RAY | TP-Transformer Summary

TP-Transformer is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. TP-Transformer has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However TP-Transformer build file is not available. You can download it from GitHub.

This repository contains the source code for the paper Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving. The repository contains all the code necessary to reproduce the performance on the Deepmind Mathematics dataset (dm_math). We provide downloadlinks for the preprocessed dataset and several pretrained models.

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Quality

Security

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Support

TP-Transformer has a low active ecosystem.

It has 32 star(s) with 3 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 3 have been closed. On average issues are closed in 17 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of TP-Transformer is current.

Quality

TP-Transformer has 0 bugs and 0 code smells.

Security

TP-Transformer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

TP-Transformer code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

TP-Transformer 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

TP-Transformer releases are not available. You will need to build from source code and install.

TP-Transformer 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.

It has 1523 lines of code, 101 functions and 10 files.

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

Top functions reviewed by kandi - BETA

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

Train the model
Evaluate the model
Compute accuracy
Save the current state of the optimizer
Evaluate the greedy inference
Calculate the accuracy of the string
Sample the model
Merge all modules
Random merge function
Get a file for writing
Get a list of read streams
Compute the logits
Create masks for the image
Process all modules
Process a module group
Combine two JIT files
Read all files from all subdirectories
Enter a sentence into the network
Decodes the given batch
Reloads the best_eval_model
Loads the model
Performs the forward computation
Setup a logger
Pick a new seed from log folder
Raise AttributeError if given keys exist
Pretty print the arguments

Get all kandi verified functions for this library.

TP-Transformer Key Features

No Key Features are available at this moment for TP-Transformer.

TP-Transformer Examples and Code Snippets

No Code Snippets are available at this moment for TP-Transformer.

Community Discussions

Trending Discussions on TP-Transformer

unable to register jars from local repository as files

QUESTION

unable to register jars from local repository as files

Asked 2019-Jan-14 at 22:20

I'm having the exact same problem as described here:

Jar not found error while while trying to deploy SCDF Stream

app info source:http-transformer says

...

ANSWER

Answered 2019-Jan-13 at 19:29

Shouldn't it be

Source https://stackoverflow.com/questions/54171160

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

Vulnerabilities

No vulnerabilities reported

Install TP-Transformer

Preprocessing the dataset takes a while so you maybe want to download the already preprocessed dataset.

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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