Something Something [char-rnn-tensorflow]

[vgan]

I decided to try using char-rnn-tensorflow and I've been downloading and cleaning up a selection of books from Project Gutenberg as training input.

Ingredients so far:

• Isaac Asimov
• Jane Austen
• Ray Bradbury
• Philip K. Dick
• Charles Dickens
• Frank Herbert
• Herman Hesse
• Communist Manifesto
• H.G. Wells

Just finished training on 5MB of text. I think I'm going to add some more books, remove others, do a bit more manual cleaning of the input text and then re-train.

Here are some fun samples:

• my face. A matter rose, imagining, had verial to my faculty.
• the darkening of never was a full of few of them?
• Why, the evils of worth.
• He seems his man and the advantage of trap it. The glorious. He busted wis which sher, but set and in things. But she broke men.

UPDATE 1:

I removed war of the worlds, added some childrens books and cleaned up the source text a little more.

Here are some samples:

• "There blessed to three wonderful meat! Don’t be from his sister.”
• Miss Lucy and Mrs. Smally from the sauce.

UPDATE 2:

Added the Sherlock Holmes books and after retraining, things got pretty weird. Maybe because of the size of the input and formatting variations? I cleaned up the text more, removing margins (they were only in the sherlock holmes books) and Chapter/ Part headers and going to re-train again.

Trying to follow some general tips from Karpathy. I'm using a GTX1080 so I increased the rnn_size to 700, num_layers to 3 to try to improve the model and increased the batch_size to 1000 to speed up the process.

Samples are much more interesting:

• Then I will not ask what you have; but I am very sorry for my plagued questions.
• The bear was delightedly round, when very free trails of debris were to go, could eat all the blackened slopes of strength to do something like blood from the fireplace.

UPDATE 3:

OK, the book is done and source is here!