debian | Debian Sid repository

answer found here : https://suay.site/?p=526

in short :

retrieve the key and add the key :

This is a performance issue of the current Numpy implementation. I can also reproduce this problem on Windows (using an Intel Skylake Xeon processor with Numpy 1.20.3). np.logical_and(a, b) executes a very-inefficient scalar assembly code based on slow conditional jumps while np.logical_and(a.view(bool), b.view(bool)) executes relatively-fast SIMD instructions.

Currently, Numpy uses a specific implementation for bool-types. Regarding the compiler used, the general-purpose implementation can be significantly slower if the compiler used to build Numpy failed to automatically vectorize the code which is apparently the case on Windows (and explain why this is not the case on other platforms since the compiler is likely not exactly the same). The Numpy code can be improved for non-bool types. Note that the vectorization of Numpy is an ongoing work and we plan optimize this soon.

Here is the assembly code executed by np.logical_and(a, b):

OK, based on responses in IRC, this does not appear to be possible. One suggested workaround:

Issue resolved by reverting back cypress version to 7.6.0.

Yeah , I had same problem with this from yesterday , I think this is after yesterday's new update in jenkins 2.303.2 Lts .

Just do , apt upgrade , apt update, apt get install jenkins -y .

It worked for me .

The initial error was a failing python Black pipeline. Black failed because it was pinned to an older version which now fails with python3.9.8.

Updating black to the latest version 21.10b0 fixed the error for me.

See also typed_ast issue #169:

For others who may find this in a search, I ran into this problem via black because I had black pinned to an older version. The current version of black appears to no longer use typed-ast and thus won't encounter this issue.

Update:

using the latest typed-ast version >=1.5.0 seem to work as well

e.g. pip install typed-ast --upgrade

It looks like you trying to run the docker daemon inside your build image docker run.

For Linux, you need to make sure that the current user (the one running sbt), has the proper permissions to run docker commands with some post-install steps.

Maybe you could fix your script by running sudo sbt docker:publishLocal instead?

It is more common now to use a service to have a docker daemon already set up for your builds:

The condition number of the matrix that defines the linear system you are solving is at the order of 10⁷. Roughly speaking, this means that after solving this system numerically the last 7 digits will be incorrect. Thus, leaving you with roughly 9 correct digits or an error of around 10⁻⁹. It seems like

I did some investigation, but it does not fully answer the question. I am going to post the results here in case if they help somebody else.

First, if the subprocess fails, there is no traceback. So I added the additional line to display the output of subprocesses. It should be None if no errors occur. The new code: