JokeR: seqgan for Joke generation (Tensorflow)
SeqGAN implementation for generating jokes using an RNN and LSTM.
Generating jokes is a challenging and understudied task of Natural Language Processing. A computer that intends and succeeds to generate jokes could be deemed artificially intelligent. We present a couple of novel approaches to joke generation, such as using SeqGAN and a language model. We implement a variety of word-level models to tackle parts of the joke-generation problem, namely text generation and joke classification. Ideally, merging these steps will allow for a model to write joke candidates, that are then pruned by a well-trained classifier. We train these models from a corpus of 231,657 userwritten jokes scraped from reddit.com
Samples
Some sample jokes that the model generated.
• I was in the bar, but I wasn’t the bartender.
• What do you call a bar, a bar because it was a bar
• What do you call a girlfriend? a child to the bar.
• I was in the bar and the bar says I am not a bar.
Usage
To train the default model to generate lines from sample_text.txt, use:
>>> ./train
To sample from a trained model, use:
>>> ./sample <sample_len>
To specify your own text, use:
>>> ./train -t /path/to/your/file.txt
To see all the training options, use:
>>> ./train --help
This gives
usage: train.py [-h] [-t TEXT] [-l SEQ_LEN] [-b BATCH_SIZE] [-n NUM_STEPS]
[-e NUM_EPOCHS] [-c] [-p LEARN_PHASE]
Train a SeqGAN model on some text.
optional arguments:
-h, --help show this help message and exit
-t TEXT, --text TEXT path to the text to use
-l SEQ_LEN, --seq_len SEQ_LEN
the length of each training sequence
-b BATCH_SIZE, --batch_size BATCH_SIZE
size of each training batch
-n NUM_STEPS, --num_steps NUM_STEPS
number of steps per epoch
-e NUM_EPOCHS, --num_epochs NUM_EPOCHS
number of training epochs
-c, --only_cpu if set, only build weights on cpu
-p LEARN_PHASE, --learn_phase LEARN_PHASE
learning phase (None for synchronized)