Comments (6)
This gif perfectly describes how I feel right now:
I don't know what I was thinking when I wrote that part of the code, maybe I was hungry and was thinking about eating some pizza (?) 🤦 lol.
Anyway, thanks for reporting this, I should update the documentation and replace "sanction" with "significance", and "sn_m" with "sg_m" (Note: if you have already done it yourself, do not hesitate to create a new Pull Request, it will be appreciated and received with love ❤️ ).
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Nice! \o/
Let me know if you find anything - I'll also have a look into it again later 🔍
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Ah nice 😄
I implemented the changes, however the tests for the latest commit fail for me at Job 1.2 and Job 1.4.
Are you sure this test is implemented correctly? To me it seems odd, that there is no path given...
Could you please help me to understand the problem here?
Btw: Is there a reason that only Job 1.2 and Job 1.4 perform server testing?
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That is really really super duper weird 😮, why failing with Python 3.5 and 3.7, and not 3.6? that is super weird 🤔.
Are you sure this test is implemented correctly? To me it seems odd, that there is no path given...
The path should be given by the mockers
argument:
Line 215 in bc8ec0a
Which is defined here:
Lines 57 to 65 in bc8ec0a
The last two lines above (line 64 and 65) return a mocked version of the "parse_args" which is defined here:
Lines 46 to 54 in bc8ec0a
There, in line 51, the path is being set (
path = dataset_path
). That's the way the path should be given, which explains why it worked for all the other jobs... but why not for those Job 1.2 and Job 1.4? mmm... what I can tell by the error log, somehow the path is (or has become) None
there, would it be caused by the previous "ValueError: the default category must be 'most-probable', 'unknown', or a category name (current value is 'xxxxx')" error? I don't know, in which case I would try removing or commenting out this line:Line 155 in bc8ec0a
But, as I said, it is weird, the server test is not "straightforward" because it has to use threads to run the server multiple times with different arguments sending (handcrafted) HTTP requests from the main test thread to those "server threads", could it be something related to the overlapping of those asynchronous tests, somehow? Anyhow, feel free to perform the Pull Request, we will merge it and then try to locally replicate the error to trace back where this error is originating. Don't worry, before releasing a new version with these patches, we will fix these test errors, what do you think?
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Ah okay now I understand where it gets its arguments from.
I just ran the tests on a plain 18.04 Ubuntu VM and all of them passed...
However ValueError: the default category must be 'most-probable', 'unknown', or a category name (current value is 'xxxxx').
still occurs - guess this doesn't have an impact on our failing tests.
Maybe it's due to the fact, that the Buildagents still use Ubuntu 16.04?
Then lets do the merge and figure out the problem after that :)
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Perfect! Thanks for your contribution!!!
I've merged the changes and updated the Contributions section to add "code" to your contribution types 👍.
Now I'll try to locally replicate the error before releasing the new version containing your patch. 🤞 🤞 🤞
(I've just sent you an invitation to be added as a contributor, so you can get direct access to this repository from now on 😎 )
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Related Issues (20)
- Divison by 0 HOT 4
- Custom metrics for evaluation HOT 5
- Use evaluation and explanation as a standalone package? HOT 2
- Partial learn HOT 10
- Data loading issues while train HOT 4
- [joss] update the changelog HOT 1
- [joss] update entry site of the documentation HOT 1
- [joss] feature request: accessible utility to import a dataset HOT 4
- [joss] software paper comments HOT 1
- [JOSS] comments on the paper
- AttributeError: type object 'Dataset' has no attribute 'load_from_url' HOT 3
- AttributeError: type object 'Dataset' has no attribute 'load_from_url' HOT 3
- PYSS3 support for multi-class classification
- Set custom Confidence Vectors
- Custom preprocessing in Live Test HOT 8
- Multilabel Classification Evaluation HOT 14
- Multilabel Classification Dataset Loading HOT 4
- Change of category name HOT 1
- Multilabel Live Test HOT 3
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