hybridize-functions-refactoring

Refactorings for optimizing imperative TensorFlow clients for greater efficiency.

https://github.com/ponder-lab/hybridize-functions-refactoring

Science Score: 67.0%

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CITATION.cff file
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Found codemeta.json file
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DOI references
Found 3 DOI reference(s) in README
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Academic publication links
Links to: acm.org, zenodo.org
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Scientific vocabulary similarity
Low similarity (12.0%) to scientific vocabulary

Keywords

hybridization

Last synced: 6 months ago · JSON representation ·

Repository

Refactorings for optimizing imperative TensorFlow clients for greater efficiency.

Basic Info

Host: GitHub
Owner: ponder-lab
License: epl-2.0
Language: Java
Default Branch: main
Homepage:
Size: 42.9 MB

Statistics

Stars: 0
Watchers: 1
Forks: 1
Open Issues: 56
Releases: 1

Topics

hybridization

Created almost 4 years ago · Last pushed 8 months ago

Metadata Files

Readme Contributing License Citation Codeowners

Hybridize-Functions-Refactoring

Introduction

Imperative Deep Learning programming is a promising paradigm for creating reliable and efficient Deep Learning programs. However, it is challenging to write correct and efficient imperative Deep Learning programs in TensorFlow (v2), a popular Deep Learning framework. TensorFlow provides a high-level API (@tf.function) that allows users to execute computational graphs using nature, imperative programming. However, writing efficient imperative TensorFlow programs requires careful consideration.

This tool consists of automated refactoring research prototype plug-ins for Eclipse PyDev that assists developers in writing optimal imperative Deep Learning code in a semantics-preserving fashion. Refactoring preconditions and transformations for automatically determining when it is safe and potentially advantageous to migrate an eager function to hybrid and improve upon already hybrid Python functions are included. The approach utilizes the WALA Ariadne static analysis framework that has been modernized to TensorFlow 2 and extended to work with modern Python constructs and whole projects. The tool also features a side-effect analysis that is used to determine if a Python function is safe to hybridize.

Screenshot

Usage

The tool is designed to be used in the Eclipse IDE with the PyDev plug-in. Thus, the tool is designed to operate on Python files contained within PyDev projects, as that is where it obtains metadata from the projects such as PYTHONPATH. However, currently, the tool is only compatible only with our PyDev 9.3 development branch. That means that you will have to have our version of PyDev installed in your Eclipse instance before using this plug-in. Thus, if you have a version of PyDev previously installed, you will need to uninstall it before installing our tool. Integration with the standard PyDev version is being tracked by #152. Installation via our update site should install the necessary PyDev version automatically.

Once the plug-in and dependencies are installed, the refactoring can be run in two different ways:

As a command.
1. Select a Python code entity.
2. Select "Hybridize function..." from the "Quick Access" dialog (CTRL-3).
As a menu item.
1. Right-click on a Python code entity.
2. Under "Refactor," choose "Hybridize function..."

Currently, the refactoring works only via the package explorer and the outline views. You can either select a code entity to optimize or select multiple entities. In each case, the tool will find functions in the enclosing entity to refactor.

Update

Due to https://github.com/ponder-lab/Hybridize-Functions-Refactoring/issues/370, only the "command" is working.

Installation

The tool has been tested on Eclipse IDE for RCP and RAP Developers Version: 2023-03 (4.27.0), Build id: 20230309-1520 under Java 17.

Update Site

An alpha version of our tool is available via an Eclipse update site at:

https://raw.githubusercontent.com/ponder-lab/Hybridize-Functions-Refactoring/main/edu.cuny.hunter.hybridize.updatesite

Please choose the latest version.

Eclipse Marketplace

Coming soon!

Dependencies

The refactoring has several dependencies as listed below. If you experience any trouble installing the plug-in using the above update site, you can manually install the dependencies. The latest version of the plug-ins should be installed:

Dependency | Update Site --- | --- Common Eclipse Refactoring Framework | https://raw.githubusercontent.com/ponder-lab/Common-Eclipse-Java-Refactoring-Framework/master/edu.cuny.citytech.refactoring.common.updatesite PyDev | https://raw.githubusercontent.com/ponder-lab/Pydev/pydev93/org.python.pydev.updatesite WALA | https://raw.githubusercontent.com/ponder-lab/WALA/v1.6/com.ibm.wala-repository

Contributing

For information on contributing, see CONTRIBUTING.md.

Further Information

See the wiki for further information.

Owner

Name: PONDER
Login: ponder-lab
Kind: organization
Email: ponder@hunter.cuny.edu
Location: New York, NY

Website: http://ponder-lab.github.io
Repositories: 146
Profile: https://github.com/ponder-lab

The PrOgramming laNguages anD software Engineering Research (PONDER) Lab at CUNY.

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Khatchadourian
    given-names: Raffi
    orcid: https://orcid.org/0000-0002-7930-0182
  - family-names: Castro Vélez
    given-names: Tatiana
    orcid: https://orcid.org/0000-0002-6122-269X
title: "Hybridize Functions Refactoring"
version: v1.4.0
date-released: 2025-03-18
type: software
doi: 10.5281/zenodo.15045769
repository-code: "http://github.com/ponder-lab/Hybridize-Functions-Refactoring"
preferred-citation:
  authors:
    - family-names: Khatchadourian
      given-names: Raffi
      orcid: https://orcid.org/0000-0002-7930-0182
    - family-names: Castro Vélez
      given-names: Tatiana
      orcid: https://orcid.org/0000-0002-6122-269X
    - family-names: Bagherzadeh
      given-names: Mehdi
      orcid: https://orcid.org/0000-0003-1549-881X
    - family-names: Jia
      given-names: Nan
      orcid: https://orcid.org/0000-0002-6122-269X
    - family-names: Raja
      given-names: Anita
      orcid: https://orcid.org/0000-0002-0735-7358
  title: "Hybridize Functions: A Tool for Automatically Refactoring Imperative Deep Learning Programs to Graph Execution"
  abstract: "Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code---supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the ``best of both worlds,'' using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution---avoiding performance bottlenecks and semantically inequivalent results. We discuss the engineering aspects of a refactoring tool that automatically determines when it is safe and potentially advantageous to migrate imperative DL code to graph execution and vice-versa."
  type: conference-paper
  date-released: 2025-05-01
  doi: 10.1007/978-3-031-90900-9_5
  keywords:
    - "deep learning"
    - "refactoring"
    - "imperative programs"
    - "graphs"
  conference:
    date-end: "2025-05-08"
    name: "FASE 2025"

GitHub Events

Total

Create event: 35
Release event: 1
Issues event: 5
Delete event: 31
Issue comment event: 30
Push event: 123
Gollum event: 1
Pull request review event: 40
Pull request event: 55
Fork event: 1

Last Year

Create event: 35
Release event: 1
Issues event: 5
Delete event: 31
Issue comment event: 30
Push event: 123
Gollum event: 1
Pull request review event: 40
Pull request event: 55
Fork event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 2
Total pull requests: 21
Average time to close issues: N/A
Average time to close pull requests: 29 days
Total issue authors: 1
Total pull request authors: 2
Average comments per issue: 0.0
Average comments per pull request: 0.38
Merged pull requests: 6
Bot issues: 0
Bot pull requests: 18

Past Year

Issues: 2
Pull requests: 21
Average time to close issues: N/A
Average time to close pull requests: 29 days
Issue authors: 1
Pull request authors: 2
Average comments per issue: 0.0
Average comments per pull request: 0.38
Merged pull requests: 6
Bot issues: 0
Bot pull requests: 18

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Top Authors

Issue Authors

khatchad (5)

Pull Request Authors

dependabot[bot] (30)
khatchad (4)

Top Labels

Issue Labels

enhancement (3) java (2) preconditions (2) question (1) side-effects (1) performance (1) testing (1)

Pull Request Labels

dependencies (30) java (27) python (3)

Dependencies

.github/workflows/dependabot-auto-approve.yml actions

dependabot/fetch-metadata v1.1.1 composite

.github/workflows/dependabot-auto-merge.yml actions

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actions/checkout v4 composite
actions/setup-java v4 composite
advanced-security/maven-dependency-submission-action 571e99aab1055c2e71a1e2309b9691de18d6b7d6 composite

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edu.cuny.hunter.hybridize.eval/pom.xml maven

edu.cuny.hunter.hybridize.tests/pom.xml maven

edu.cuny.hunter.hybridize.tests.report/pom.xml maven

edu.cuny.hunter.hybridize:edu.cuny.hunter.hybridize.core 1.0.0-SNAPSHOT compile
edu.cuny.hunter.hybridize:edu.cuny.hunter.hybridize.ui 1.0.0-SNAPSHOT compile
edu.cuny.hunter.hybridize:edu.cuny.hunter.hybridize.tests 1.0.0-SNAPSHOT test

edu.cuny.hunter.hybridize.ui/pom.xml maven

pom.xml maven

edu.cuny.hunter.hybridize.tests/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testAbs/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testAbs2/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testAddN/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testAddN2/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testAddN3/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testAddN4/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testAmbiguousDefinition/in/requirements.txt pypi

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testAutoEncoder/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testBooleanMask/in/requirements.txt pypi

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tensorflow ==2.9.3 test

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edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testBooleanParameter3/in/requirements.txt pypi

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edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testCallback/in/requirements.txt pypi

tensorflow ==2.9.3 test

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matplotlib ==3.8.2 test
numpy ==1.23.4 test
tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testClassInDifferentFile2/in/requirements.txt pypi

matplotlib ==3.8.2 test
numpy ==1.23.4 test
tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testClassInDifferentFile3/in/requirements.txt pypi

matplotlib ==3.8.2 test
numpy ==1.23.4 test
tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testClassInDifferentFile4/in/requirements.txt pypi

matplotlib ==3.8.2 test
numpy ==1.23.4 test
tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testClassInDifferentFile5/in/requirements.txt pypi

matplotlib ==3.8.2 test
numpy ==1.23.4 test
tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testClassInDifferentFile6/in/requirements.txt pypi

matplotlib ==3.8.2 test
numpy ==1.23.4 test
tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters10/in/requirements.txt pypi

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters11/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters12/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters2/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters3/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters4/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters5/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters6/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters7/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testComputeParameters8/in/requirements.txt pypi

tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testCustomGradient/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset/in/requirements.txt pypi

tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset11/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset12/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset13/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset14/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset15/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset16/in/requirements.txt pypi

tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset3/in/requirements.txt pypi

tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset5/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset6/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset7/in/requirements.txt pypi

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edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDataset8/in/requirements.txt pypi

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edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDatasetEnumeration/in/requirements.txt pypi

tensorflow ==2.9.3 test

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edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDifferentFileSameName/in/requirements.txt pypi

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDifferentFileSameName10/in/requirements.txt pypi

tensorflow ==2.9.3 test

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edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDifferentFileSameName3/in/requirements.txt pypi

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDifferentFileSameName4/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testDifferentFileSameName5/in/requirements.txt pypi

tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testEinSum/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testEqual/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testEqual2/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testEqual3/in/requirements.txt pypi

tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testExp2/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testExtractPatches/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testFunctionEquality/in/requirements.txt pypi

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testFunctionEquality2/in/requirements.txt pypi

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testFunctionEquality3/in/requirements.txt pypi

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testGPModel/in/requirements.txt pypi

tensorflow ==2.9.3 test

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tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testGPModel3/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testGetDecoratorFQN/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testGetDecoratorFQN2/in/requirements.txt pypi

tensorflow ==2.9.3 test

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testHasLikelyTensorParameter/in/requirements.txt pypi

hybridize-functions-refactoring

Science Score: 67.0%

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Hybridize-Functions-Refactoring

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