This is an implementation of sec.4 and 5 of "Generating Sequences With Recurrent Neural Networks" paper by Alex Graves
Setting: bias=0.2, seed=range(5)
Setting: bias=2, seed=range(5)
Strength means blessed with an enemy : words are wind! : Bridged by a lightwave : kimi no na ma : Bonjour! On y va? :
- Place data (
sentences.txt
andstrokes-py3.npy
) indata/
directory. - Use
train.py
script to train the model. - Runs are saved in
runs/
directory. - To generate above samples, use
models/dummy.py
from models.dummy import generate_unconditionally, generate_conditionally for i in range(5): x = generate_unconditionally(i) plot_stroke(x,save_name=f'asset/un_{i+1}') texts = ['Strength means blessed with an enemy!', 'words are wind!', 'Bridged by a lightwave ', 'kimi no na ma', 'Bonjour! On y va?'] for i in range(5): x = generate_conditionally(random_seed=i, text=texts[i]) plot_stroke(x, save_name=f'asset/co_{i}')