Hackathon | keep track all issues for the 2020 Hackathon | Frontend Framework library

Normally you don't declare dependency versions when you have defined a dependencyManagement section in your POM where you centralize all of the dependencies used by all of your modules.

Since your POM does not define a dependencyManagement, you will need to provide the version for each dependency. You can check this sample guide project from Spring Boot, where you will notice that they set a parent in the POM:

First, remove align="left" from the img tag in HTML. Then add float: left; to the img ruleset in CSS. Finally, modifying your media query to include the section and img selectors:

The problem is that your read_json(....).text line returns a series, not a dataframe.

Adding a .to_frame() and referencing the column in the following line should fix it:

QuerySet is collection of objects. You should iterate over it to get Admin objects and then access gmail from those objects.

Here's a relatively simple algorithm that should work for all inputs except the most perverse.

1. There are 15 combinations of two timeslots {1, 2, 3, 4, 5, 6}. For each combination construct a bin of participants (so 15 bins). Loop over all participants and add them to each bin that they are compatible with (so each participant can be in multiple bins).

   For each bin also initialize an empty list containing the groups constructed from that bin.

2. Select the bin with the shortest list of groups, and in case of tie that has the least participants in it (ignoring bins with < 3 participants in them). Using any greedy soft-constraint algorithm pick a 'diverse' (in terms of departments/offices) group of 3 participants from this bin.

   Add this group to the list of groups for the selected bin, and remove the selected participants from all bins.

   Repeat this step until all bins have 2 or less members left (or until a constructed group wouldn't be diverse enough, although this risks a higher failure chance).

3. At this point you are left with only a few ungrouped participants. Add them one by one to any compatible size three group in some greedy way (e.g. simply choose the group that maximizes diversity score).

I edited the Code with the new snippet, the link and the script. I left comments on the far left starting with EDITED so you can find where. All you need to do now is create the CSS-Stylesheet that is mentioned in the link in the right folder and you should be good to go.

Thanks to @EdwinCheong for pointing us in the correct direction.

The issue was resolved by basically downloading the Windows 10 SDK and a bunch of c++ -related packages in the Visual Studio Installer before following this linked tutorial: https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/install.html#tf-models-install related to installing object detection. CUDA seems to be required regardless of what the tutorial says

If you need the flexibility then keep the components the size you have them.

Dictionary Jacobian implies that you're not taking advantage of the DirectSolver which is needed to get really good performance for models of your size. This includes the use of the assembled Jacobian, which is also needed for really fast derivatives.

Try setting the DirectSolver to the linear solver at the top of your model like this:

prob.model.linear_solver = om.DirectSolver()

For generality, I should not the following:

• You can only use DirectSolver on a serial group (but that serial group could be part of a larger distributed model).
• You can use a DirectSolver on a sub-group of a model. Depending on model structure, this may be faster (See section 5.3 of this paper)
• DirectSolver works with an assembled jacobian (as opposed to the DictionaryJacobian referenced in question). This is down in the weeds, but in the vast majority of cases you want a sparse assembled jacobian for the direct solver. Very occasionally a dense assembly is better. That is controlled through system option assembled_jac_type which defaults to csc (a sparse format). You might try dense as a test -- but again, csc is very likely to be fastest.

Try giving width and height in watermark image style and if doesn't work then try swapping the position of Image view and Video view