MINERVA: An out-of-the-box GUI tool for offline deep reinforcement learning

Overview

MINERVA: An out-of-the-box GUI tool for offline deep reinforcement learning

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MINERVA is an out-of-the-box GUI tool for offline deep reinforcement learning, designed for everyone including non-programmers to do reinforcement learning as a tool.

Documentation: https://minerva-ui.readthedocs.io

Chat: Gitter

key features

⚡ All You Need Is Dataset

MINERVA only requires datasets to start offline deep reinforcement learning. Any combinations of vector observations and image observations with discrete actions and continuous actions are supported.

đź”° Stunning GUI

MINERVA provides designed with intuitive GUI to let everyone lerverage extremely powerful algorithms without barriers. The GUI is developed as a Single Page Application (SPA) to make it work in the eye-opening speed.

🚀 Powerful Algorithm

MINERVA is powered by d3rlpy, a powerful offline deep reinforcement learning library for Python, to provide extremely powerful algorithms in an out-of-the-box way. The trained policy can be exported as TorchScript and ONNX.

installation

PyPI

$ pip install minerva-ui

Docker

$ docker run -d --gpus all -p 9000:9000 --name minerva takuseno/minerva:latest

update guide

If you update MINERVA, the database schema should be also updated as follows:

$ pip install -U minerva-ui
$ minerva upgrade-db

usage

run server

At the first time, ~/.minerva will be automatically created to store database, uploaded datasets and training metrics.

$ minerva run

By default, you can access to MINERVA interface at http://localhost:9000 . You can change the host and port with --host and --port arguments respectively.

delete data

You can delete entire data (~/.minerva) as follows:

$ minerva clean

contributions

build

$ npm install
$ npm run build

coding style

This repository is fully formatted with yapf and standard. You can format the entire scripts as follows:

$ ./scripts/format

lint

This repository is fully analyzed with Pylint, ESLint and sass-lint. You can run analysis as follows:

$ ./scripts/lint

test

The unit tests are provided as much as possible. This repository is using pytest-cov instead of pytest. You can run the entire tests as follows:

$ ./scripts/test

acknowledgement

This work is supported by Information-technology Promotion Agency, Japan (IPA), Exploratory IT Human Resources Project (MITOU Program) in the fiscal year 2020.

The concept of the GUI software for deep reinforcement learning is inspired by DeepAnalyzer from Ghelia inc. I'm showing the great respect to the team here.

Comments
  • Bump y18n from 4.0.0 to 4.0.3

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    4.0.3 (2021-04-07)

    Bug Fixes

    • release: 4.x.x should not enforce Node 10 (#126) (1e21a53)

    4.0.1 (2020-11-30)

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    dependencies javascript 
    opened by dependabot[bot] 1
  • Bump pillow from 7.1.2 to 8.1.1

    Bump pillow from 7.1.2 to 8.1.1

    Bumps pillow from 7.1.2 to 8.1.1.

    Release notes

    Sourced from pillow's releases.

    8.1.1

    https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html

    8.1.0

    https://pillow.readthedocs.io/en/stable/releasenotes/8.1.0.html

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    Dependencies

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    8.1.1 (2021-03-01)

    • Use more specific regex chars to prevent ReDoS. CVE-2021-25292 [hugovk]

    • Fix OOB Read in TiffDecode.c, and check the tile validity before reading. CVE-2021-25291 [wiredfool]

    • Fix negative size read in TiffDecode.c. CVE-2021-25290 [wiredfool]

    • Fix OOB read in SgiRleDecode.c. CVE-2021-25293 [wiredfool]

    • Incorrect error code checking in TiffDecode.c. CVE-2021-25289 [wiredfool]

    • PyModule_AddObject fix for Python 3.10 #5194 [radarhere]

    8.1.0 (2021-01-02)

    • Fix TIFF OOB Write error. CVE-2020-35654 #5175 [wiredfool]

    • Fix for Read Overflow in PCX Decoding. CVE-2020-35653 #5174 [wiredfool, radarhere]

    • Fix for SGI Decode buffer overrun. CVE-2020-35655 #5173 [wiredfool, radarhere]

    • Fix OOB Read when saving GIF of xsize=1 #5149 [wiredfool]

    • Makefile updates #5159 [wiredfool, radarhere]

    • Add support for PySide6 #5161 [hugovk]

    • Use disposal settings from previous frame in APNG #5126 [radarhere]

    • Added exception explaining that repr_png saves to PNG #5139 [radarhere]

    • Use previous disposal method in GIF load_end #5125 [radarhere]

    ... (truncated)

    Commits
    • 741d874 8.1.1 version bump
    • 179cd1c Added 8.1.1 release notes to index
    • 7d29665 Update CHANGES.rst [ci skip]
    • d25036f Credits
    • 973a4c3 Release notes for 8.1.1
    • 521dab9 Use more specific regex chars to prevent ReDoS
    • 8b8076b Fix for CVE-2021-25291
    • e25be1e Fix negative size read in TiffDecode.c
    • f891baa Fix OOB read in SgiRleDecode.c
    • cbfdde7 Incorrect error code checking in TiffDecode.c
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    dependencies python 
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  • Bump ini from 1.3.5 to 1.3.8

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    dependencies 
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  • Bump axios from 0.19.2 to 0.21.1

    Bump axios from 0.19.2 to 0.21.1

    Bumps axios from 0.19.2 to 0.21.1.

    Release notes

    Sourced from axios's releases.

    v0.21.1

    0.21.1 (December 21, 2020)

    Fixes and Functionality:

    • Hotfix: Prevent SSRF (#3410)
    • Protocol not parsed when setting proxy config from env vars (#3070)
    • Updating axios in types to be lower case (#2797)
    • Adding a type guard for AxiosError (#2949)

    Internal and Tests:

    • Remove the skipping of the socket http test (#3364)
    • Use different socket for Win32 test (#3375)

    Huge thanks to everyone who contributed to this release via code (authors listed below) or via reviews and triaging on GitHub:

    v0.21.0

    0.21.0 (October 23, 2020)

    Fixes and Functionality:

    • Fixing requestHeaders.Authorization (#3287)
    • Fixing node types (#3237)
    • Fixing axios.delete ignores config.data (#3282)
    • Revert "Fixing overwrite Blob/File type as Content-Type in browser. (#1773)" (#3289)
    • Fixing an issue that type 'null' and 'undefined' is not assignable to validateStatus when typescript strict option is enabled (#3200)

    Internal and Tests:

    • Lock travis to not use node v15 (#3361)

    Documentation:

    • Fixing simple typo, existant -> existent (#3252)
    • Fixing typos (#3309)

    Huge thanks to everyone who contributed to this release via code (authors listed below) or via reviews and triaging on GitHub:

    ... (truncated)

    Changelog

    Sourced from axios's changelog.

    0.21.1 (December 21, 2020)

    Fixes and Functionality:

    • Hotfix: Prevent SSRF (#3410)
    • Protocol not parsed when setting proxy config from env vars (#3070)
    • Updating axios in types to be lower case (#2797)
    • Adding a type guard for AxiosError (#2949)

    Internal and Tests:

    • Remove the skipping of the socket http test (#3364)
    • Use different socket for Win32 test (#3375)

    Huge thanks to everyone who contributed to this release via code (authors listed below) or via reviews and triaging on GitHub:

    0.21.0 (October 23, 2020)

    Fixes and Functionality:

    • Fixing requestHeaders.Authorization (#3287)
    • Fixing node types (#3237)
    • Fixing axios.delete ignores config.data (#3282)
    • Revert "Fixing overwrite Blob/File type as Content-Type in browser. (#1773)" (#3289)
    • Fixing an issue that type 'null' and 'undefined' is not assignable to validateStatus when typescript strict option is enabled (#3200)

    Internal and Tests:

    • Lock travis to not use node v15 (#3361)

    Documentation:

    • Fixing simple typo, existant -> existent (#3252)
    • Fixing typos (#3309)

    Huge thanks to everyone who contributed to this release via code (authors listed below) or via reviews and triaging on GitHub:

    ... (truncated)

    Commits

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    dependencies 
    opened by dependabot[bot] 0
  • What does Eposide id correspond to in a recommendation dataset

    What does Eposide id correspond to in a recommendation dataset

    I have a recommender dataset where I have userID, user_feature1,user_featureX...., ItemID,Item_feature1...Item_featureY.., reward(sales amount),datetime.. how should I restructure this data to be used/tested in Minerva? In the tutorial, https://minerva-ui.readthedocs.io/en/v0.40/getting_started.html, I am unable to correlate what will be the eposide ID in my dataset.

    opened by ayush488 0
  • ERROR: (sqlite3.OperationalError) unable to open database file.

    ERROR: (sqlite3.OperationalError) unable to open database file.

    Hi,

    I just installed the Minerva. However when I execute minerva run command I receive following error:

    sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) unable to open database file (Background on this error at: http://sqlalche.me/e/14/e3q8)

    Can you please tell me what is causing this error and how can I fix it? Thanks in advance.

    bug 
    opened by Zaharah 3
Releases(v0.40)
  • v0.40(May 29, 2021)

    Support d3rlpy v0.90!

    MINERVA now supports d3rlpy v0.90 and there are the highlights for MINERVA.

    • more precise CQL and BEAR implementations
    • predict_value is fixed for unscaled actions
    • CRR algorithm is available
    Source code(tar.gz)
    Source code(zip)
  • v0.32(Mar 6, 2021)

    a way to upload images is changed

    Previously, the image files are uploaded via selecting the directory that contains all the files. However this is an easy way, the browser limits the number of files due to the efficiency issue. So, from this version, you can upload zipped file that contains the image files. This is the more efficient and fast way. image

    Source code(tar.gz)
    Source code(zip)
  • v0.31(Mar 6, 2021)

  • v0.30(Mar 5, 2021)

    Support d3rlpy v0.70!

    MINERVA now supports d3rlpy v0.70, which has a lot of progress from the v0.41 that is the previous dependency.

    These are some highlights related to MINERVA.

    • the continuous action is automatically normalized based on the dataset statistics
    • discrete action option has been removed since the action-space is automatically detected
    • many other internal enhancements
    Source code(tar.gz)
    Source code(zip)
  • v0.20(Dec 21, 2020)

    Support d3rlpy v0.41!

    MINERVA now supports d3rlpy v0.41, which has a lot of progress from the v0.23 that is the previous dependency.

    These are the some highlights related to MINERVA.

    • extremely fast mini-batch creation
    • extremely fast frame stacking for image observation
    • extremely fast N-step TD calculation
    • new metrics
    • etc

    Algorithm Selection

    MINERVA now provides many many algorithms for both discrete and continuous control datasets. You can choose an algorithm at the project creation dialog.

    discrete algorithms

    • DQN
    • Double DQN
    • AWR
    • CQL
    • BCQ
    • SAC

    continuous algorithms

    • DDPG
    • TD3
    • SAC
    • BCQ
    • BEAR
    • CQL
    • AWR
    • AWAC
    • PLAS

    Of course, there is the Q function option to incorporate arbitrary algorithms with the powerful distributional Q functions.

    Q functions

    • mean
    • Quantile Regression
    • Implicit Quantile Network
    • Fully parameterized Quantile Function
    Source code(tar.gz)
    Source code(zip)
  • v0.12(Sep 9, 2020)

  • v0.11(Sep 9, 2020)

    Dataset Dashboard

    • upload datasets
      • discrete/continuous action-space
      • vector/image observations

    Project Dashboard

    • train with CQL with detailed configurations.

    Export Policy

    • Support TorchScript and ONNX.
    Source code(tar.gz)
    Source code(zip)
Owner
Takuma Seno
Machine learning engineer at Sony AI / Ph.D CS student at Keio University.
Takuma Seno
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