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Using re.sub on the pattern \b\d+(?:\.\d+)?s\b should work here:

You can pivot() into the expected output:

According to the AWS documentation IP addresses per network interface per instance type the t2.micro only has 2 Network Interfaces and 2 IPv4 addresses per interface.

https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-eni.html#AvailableIpPerENI

There is limitation on AWS EKS to schedule the pod : https://github.com/awslabs/amazon-eks-ami/blob/master/files/eni-max-pods.txt

you can remove this limit if want : https://medium.com/@swazza85/dealing-with-pod-density-limitations-on-eks-worker-nodes-137a12c8b218

FABRIC_CFG_PATH setting is wrong. Currently, your error is a phrase that occurs when there is a problem with the syntax in the configtx.yaml file or when the file path is wrong and cannot be found.

For configtxgen, refer to the configtx.yaml file under FABRIC_CFG_PATH.

In the tutorial you provided, configtx.yaml is not found under configFiles directory and it exists under artifacts directory.

I'll suggest two of the easiest solutions out of many.

• move artifacts/configtx.yaml to configFiles/configtx.yaml

It is possible to keep the text unflipped, but you probably do not want that. Be that as it may, you can keep a part of a figure grouped and transformed independently. In the example below, I added a group (g) with id="noflip". You can then undo the transformation in that group. But in that case, it is not aligned with the rest. For the effect I believe you want, you also need to skew it:

It's not a GCC 8 problem (you should undo the GCC 8 installation changes).

The error message "gcc: internal compiler error: Killed (program cc1plus)" indicates that the compiler crashed. Most likely, this is because it ran out of memory (RAM).

If the build was using multiple cores to compile, then compiling with less concurrency should help. Try bazel build //... -j 1, perhaps. If that helps, you could put that into a dotfile via https://docs.bazel.build/versions/master/guide.html#bazelrc-the-bazel-configuration-file so that jobs are always limited when building on that machine.

However, if only one file is being compiled at a time and you still run of memory, then you'll probably need to increase the memory allocation of the virtual machine.

Thanks for the question. Looking at the source code, we don't include Pendingpods when calculating the current number of executing tasks. It may be something else is going on. 1) Could you run kubectl describe pod on a pod when it's in this state and post the result? (status details). 2) Is the deployer configured to create a job for each task? (false by default).

tensorflow does not support CUDA 11.1, use CUDA 11.0 instead and move the ptxas.exe from the CUDA 11.1 directory to your 11.0 directory.

I took a quick look at the code. In it there is this line: