42 | A demonstration of improper use of the C preprocessor | Reflection library

I'm making a POC with Lumen and Vue.JS. For now it just has to send a "hello world" message from the Lumen back-end to the Vue.JS front-end (which works). I have made an event which is triggered upon loading the page like this:

I'm trying to import compose sample projects, but I'm facing this error:

I have a t.test function and I want to loop over myvec <- c("am", "vs"). any help will e appreciated, many thanks in advance.

I have two grid setup's

1. Local grid setup (hub and nodes are running in my local machine) and my local machine connected to network#1

2. VM grid setup (hub and nodes are running in my virtual machine) and my virtual machine connected to network#2

When I execute the scripts I need to pass the IP address as a parameter. Here, I can run my scripts successfully in local machine(code is available in local machine) by passing the network#1 IP address but if I pass the network#2 IP address (VM IP address) to local machine then I am getting below exception,

org.openqa.selenium.remote.UnreachableBrowserException: Could not start a new session. Possible causes are invalid address of the remote server or browser start-up failure.

As per my knowledge, hub and nodes should be connected to same network. Cannot we run the scripts by passing the VM IP address to local machine?

Trace:

In my iOS app "Progression" there is rarely a crash (1 crash in ~1000+ Sessions) I am currently not able to fix. The message is

Progression: protocol witness for TrainingSetSessionManager.update(object:weight:reps:) in conformance TrainingSetSessionDataManager + 40

This crash points me to the following method:

Machine Setting:

• GPU: GeForce RTX 3060

• Driver Version: 460.73.01

• CUDA Driver Veresion: 11.2

• Tensorflow: tensorflow-gpu 1.14.0

• CUDA Runtime Version: 10.0

• cudnn: 7.4.1

Note:

1. CUDA Runtime and cudnn version fits the guide from Tensorflow official documentation.
2. I've also tried for TensorFlow-gpu = 2.0, still the same problem.

Problem:

I am using Tensorflow for an objection detection task. My situation is that the program will stuck at

2021-06-05 12:16:54.099778: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10

for several minutes.

And then stuck at next loading process

2021-06-05 12:21:22.212818: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7

for even longer time. You may check log.txt for log details.

After waiting for around 30 mins, the program will start to running and WORK WELL.

However, whenever program invoke self.session.run(...), it will load the same two library related to cuda (libcublas and libcudnn) again, which is time-wasted and annoying.

I am confused that where the problem comes from and how to resolve it. Anyone could help?

Discussion Issue on Github

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Update

After @talonmies 's help, the problem was resolved by resetting the environment with correct version matching among GPU, CUDA, cudnn and tensorflow. Now it works smoothly.

I have a dataframe that contains two columns with dates astype Timestamps. I would like to plot a figure where the time between those dates is 1 and the time outside those dates is 0: kinda like an 'active on/off' binary situation. I have discretised and indexed the whole day in intervals of 1 minute. After that, I am checking if the index is between time1 and time2, if it is then I am putting 1 to a new column else 0. This works but I think it's an overkill

I want to round numbers so that two numbers are used after the last zero, or decimal if the number is greater than 1. I've looked up the documentation for round, but can't seem to find this feature.

If I use round, it always round to n decimals places regardless.

This is the output I'm looking for:

I have a df as below: