[REVIEW]: MLJFlux: Deep learning interface to the MLJ toolbox

whedon commented 3 years ago

Submitting author: @ayush-1506 (Ayush Shridhar) Repository: https://github.com/FluxML/MLJFlux.jl Version: v0.1.10 Editor: @melissawm Reviewer: @krystophny, @morganericsson Archive: Pending

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Review checklist for @krystophny

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

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General checks

[x] Repository: Is the source code for this software available at the repository url?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@ayush-1506) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[ ] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines

Functionality

[ ] Installation: Does installation proceed as outlined in the documentation?
[ ] Functionality: Have the functional claims of the software been confirmed?
[ ] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[ ] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[ ] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[ ] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[ ] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[ ] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[ ] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[ ] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[ ] A statement of need: Does the paper have a section titled 'Statement of Need' that clearly states what problems the software is designed to solve and who the target audience is?
[ ] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[ ] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[ ] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

Review checklist for @morganericsson

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the repository url?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@ayush-1506) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[ ] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[ ] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[ ] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[ ] A statement of need: Does the paper have a section titled 'Statement of Need' that clearly states what problems the software is designed to solve and who the target audience is?
[ ] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[ ] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

whedon commented 3 years ago

Hello human, I'm @whedon, a robot that can help you with some common editorial tasks. @krystophny, @morganericsson it looks like you're currently assigned to review this paper :tada:.

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whedon commented 3 years ago

Software report (experimental):

github.com/AlDanial/cloc v 1.88  T=0.05 s (789.0 files/s, 251607.4 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
TOML                             7            588              3           2702
Julia                           17            491            227           1459
Markdown                         5            226              0            673
Jupyter Notebook                 5              0           5789            409
YAML                             5              1              1            134
TeX                              1              5              0             48
-------------------------------------------------------------------------------
SUM:                            40           1311           6020           5425
-------------------------------------------------------------------------------

Statistical information for the repository '05e80ce591033a54bf7cd49d' was
gathered on 2021/06/15.
No commited files with the specified extensions were found.

whedon commented 3 years ago

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.21105/joss.02704 is OK
- 10.21105/joss.00602 is OK
- 10.1137/141000671 is OK

MISSING DOIs

- None

INVALID DOIs

- None

whedon commented 3 years ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

melissawm commented 3 years ago

👋🏼 @ayush-1506 @morganericsson @krystophny this is the review thread for the paper. All of our communications will happen here from now on.

Both reviewers have checklists at the top of this thread with the JOSS requirements. As you go over the submission, please check any items that you feel have been satisfied. There are also links to the JOSS reviewer guidelines.

The JOSS review is different from most other journals. Our goal is to work with the authors to help them meet our criteria instead of merely passing judgment on the submission. As such, the reviewers are encouraged to submit issues and pull requests on the software repository. When doing so, please mention openjournals/joss-reviews#3375 so that a link is created to this thread (and I can keep an eye on what is happening). Please also feel free to comment and ask questions on this thread. In my experience, it is better to post comments/questions/suggestions as you come across them instead of waiting until you've reviewed the entire package.

We aim for reviews to be completed within about 2-4 weeks. Please let me know if any of you require some more time. We can also use Whedon (our bot) to set automatic reminders if you know you'll be away for a known period of time.

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krystophny commented 3 years ago

@ayush-1506 @melissawm sorry for the delay, I have now finally found time to look at the package in detail. Unfortunately, I have the feeling that this is just a "thin API client" in the sense of the JOSS guidelines.

As far as I understand, the package provides an interface/wrappers between Flux and MLJ. Four types are exported: NeuralNetworkRegressor, MultitargetNeuralNetworkRegressor, NeuralNetworkClassifier and ImageClassifier. In total, those are implemented in less than 600 lines of code (src directory), including some boilerplate. All that is done are translations between two APIs. I wouldn't count his as "substantial scholarly effort". Also, the documentation is quite minimalistic. I acknowledge that there are a number of users, which indicates the usefulness of the package. Still, I don't believe it is extensive enough to justify a publication in JOSS.

melissawm commented 3 years ago

Thank you @krystophny , that is helpful.

@morganericsson is this something you can give your opinion about at this point?

morganericsson commented 3 years ago

@melissawm Yes, I agree with @krystophny . I've reviewed the code and played around with it a bit to get a feel for how it works. It provides a way to wrap Flux models and use them using the MLJ API. There are some nice benefits to this, but these are (mainly) due to MLJ and other underlying packages; most of the code in this package is just wrapping and translating (by design).

I found the documentation sufficient. I was able to define a simple builder (based on a Keras tutorial) and use it in a simple pipeline (even if that is mainly Flux and MLJ). However, I think the paper does a poor job of presenting the package and motivating why it is needed. I found, e.g., https://discourse.julialang.org/t/pros-and-cons-of-using-flux-directly-over-using-mlj-mljflux/59756 to describe the benefits much better (and, in some sense, the need).

whedon commented 3 years ago

:wave: @morganericsson, please update us on how your review is going (this is an automated reminder).

whedon commented 3 years ago

:wave: @krystophny, please update us on how your review is going (this is an automated reminder).

morganericsson commented 3 years ago

@melissawm I think I forgot to accept the invitation (and it has expired), so I cannot edit the checklist. Could you please send a new invitation?

danielskatz commented 3 years ago

@whedon re-invite @morganericsson as reviewer

whedon commented 3 years ago

OK, the reviewer has been re-invited.

@morganericsson please accept the invite by clicking this link: https://github.com/openjournals/joss-reviews/invitations

morganericsson commented 3 years ago

@melissawm I am done with the form now. Below are comments for the boxes I did not tick.

I agree with @krystophny that I would not count this as a "substantial scholarly effort" in the JOSS sense, even if I can see how the package is useful.
I could not find any community guidelines.
I would like to see an improved statement of need / state of the field (these are quite similar in this case in my opinion). For example, I think the discussion on when to use MLJFlux, MLJ, Flux, or FastAI could be improved (as I mentioned in my previous comment).
I think the references could be improved. For example, I am not sure why there is a need to self-reference?

While the documentation and examples are sufficient, I think it would be very helpful to improve these. For example, provided examples (examples/) and the examples in README.md are quite similar. It would have been nice with a few more complicated examples, especially a more complicated builder. But, as I said, they were sufficient to get me started, and I suppose the MLJ and Flux documentation becomes more relevant when you start to do more advanced stuff.

melissawm commented 3 years ago

Thank you both @morganericsson and @krystophny . At this point I'm tagging @openjournals/joss-eics to evaluate next steps.

danielskatz commented 3 years ago

Hi - Sorry this seems to have gotten lost for a bit. But we now see it again, and we'll move it forward very soon.

danielskatz commented 3 years ago

After some discussion between the editors-in-chief, based on the reviewers' comments, we will reject this as not having sufficient scholarly effort. Our apologies to @ayush-1506 for the slow process, and our thanks to @krystophny, @morganericsson for their reviewing work, and to @melissawm for editing.

danielskatz commented 3 years ago

@whedon reject

whedon commented 3 years ago

Paper rejected.

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