text-generator | Having fun with LSTMs by creating a simple text | Data Manipulation library

Please try to install tensorflow with conda with below command.

Need more p: the proper target name for link with is libzippp::libzippp.

The project's README wrongly suggests to use libzipp::libzipp.

As far as I can see this code doesn't provide multiple samples, but you can adjust it with a some adjustments.

This line uses already multinomial but returns only 1:

Let's say you have an array of letters with different styles (in any programming language, here we're going to use Javascript).

The styles need to be extended and add more..., I've only tried to give you an example of it.

Julia has PCRE, which means its regular expressions are far more powerful than true regular expressions. And are in-fact turing complete. I suspect there is a bunch of interesting theoretical computer science around this. I suspect your task for PCRE might be proved to be impossible because of the halting problem. But still what we can do is try a bunch of random strings and toss out those that don't match. And for simple regex that goes a long way. Its not guaranteed to give an answer though.

If one wanted stricter regex, like those covered by Automa.jl, there is probably something better that can be done, since you can walk the state machine solving it 1 bit at a time. Hopefully someone that knows Automa.jl can post their own answer.

I cannot think of a quick way other than iterating over the word's characters, counting the occurences in each list of the dictionary and summing it in the end:

Those special characters are actually each composed of two code points: 55349 and something else, 56658 and above (the second code point varies for each character).

After doing a bit of digging, I finally found out that the way I was creating the dictionary mapping between characters and one-hot vectors was the issue. I was using the char = list(set(data)) function to get a list of all the characters in the file, and then assign the index of the character as that character's 'code number'. However, apparently the list(set(data)) function does not always output the same list, instead the order is randomized for each 'session' of python. So my dictionary mapping used to change between saving and loading the model, since that occurred in different scripts. Using char = sorted(list(set(data))) works to eliminate this problem.