mre | Provisioning framework for FIM2010 / MIM2016

You have some options to do that:

1. You can use interface for that:

You can try using prefetch_related()

For example:

I think you want replace

You already know how to make the author names bold from biblatex: customizing bibliography entry - the same technique can be used for the editorstrg:

This could be the effect of accumulation with a low precision (e.g. FP16) data type.

Which data types are you using? And which algorithms?

From: https://docs.nvidia.com/deeplearning/cudnn/developer-guide/index.html

1. Mixed Precision Numerical Accuracy

When the computation precision and the output precision are not the same, it is possible that the numerical accuracy will vary from one algorithm to the other.

For example, when the computation is performed in FP32 and the output is in FP16, the CUDNN_CONVOLUTION_BWD_FILTER_ALGO_0 (ALGO_0) has lower accuracy compared to the CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1 (ALGO_1). This is because ALGO_0 does not use extra workspace, and is forced to accumulate the intermediate results in FP16, i.e., half precision float, and this reduces the accuracy. The ALGO_1, on the other hand, uses additional workspace to accumulate the intermediate values in FP32, i.e., full precision float.

It is because there is another try / except block inside tkinter code which handled the exception.

When the code is executed, the following exception traceback is shown in the console:

The function will return it last statement. Remove the last semicolon, and you could also remove the internal return statement, the result of the match statement will be returned.

Is there a better way? It looks like you are parsing a string to a enum, the create enum-utils does that. Instead of implementing the parser with boilerplate code you just derive it.

The difference between second and other two LINQ queries (hence the different translation - CAST ... as datetimeoffset) is that the others use DateTime comparisons, while this uses DateTimeOffset comparisons. Because when start type is DateTimeOffset, the expression

Flawr is correct. B[..., k] returns a np.view() into B, but does not actually copy any data. In memory, two neighbouring elements of the view have a distance of B.strides[1], which evaluates to B.shape[-1]*B.itemsize and is greater than B.itemsize. Consequentially, your array is not contiguous.

The best optimization is to vectorize the dotplus loop and write