jhp | php-like syntax on top of nodejs | Runtime Evironment library

you have to use implicit wait for driver to wait until element found Write the following code and then fit into your cucumber model

Initially set branches = null;

Instead of performing API call in ngOnInIt try in ** ngAfterViewInit** - place where DOM is rendered

You could take an object as hash table for the wanted order and use that object for sorting.

default contains a huge value Infinity to sort unknown types to the end.

For someone who wants to know the answer right away, here it is as suggested by @Mark at the comment section of my question:

1. First open the "search in files" field using Ctrl+Shift+F
2. Turn on the Regex function (right-most button of the input field)
3. Put the following regex:

   ^\s*sys.log

or this regex also works

^[^/\n](?:/[^/\n]+)*sys.log

The above regex-es work for my case.

Before I got this answer, we had a discussion with @Tim and @Wiktor, they both suggested a lookahead regex pattern, and that pattern actually works on older version (V.1.2.0) of Visual Studio Code as @Wiktor pointed out. But apparently, the advanced Regex feature for searching in files is no longer supported since V1.12.0 version. However, it's still working if you search within the file using Ctrl+F.

Thanks to @Tim, @Wiktor and @Mark who have helped to clarify things out.

Those Google search suggestions, which you have visited before, appear to be settable with CSS like this:

You're initializing the neural net wrong. If you look closer at every cnn example in the dl4j examples repo (hint: this is the canonical source of where you should be pulling code from, anything else will likely be invalid or out of date: https://github.com/deeplearning4j/dl4j-examples) You'll notice in all of our examples we have an inputType config: https://github.com/deeplearning4j/dl4j-examples/blob/master/dl4j-examples/src/main/java/org/deeplearning4j/examples/convolution/LenetMnistExample.java#L114

There are various types you should be using you should never set nIn manually. Just nOut.

For mnist, we use convolutional flat and convert it in to a 4d dataset automaticall for you.

Mnist starts off as a flat vector, but a cnn only understands 3d data. We do that transition and reshape for you.