theanhle

#############################################################################
# 				Documentation				    #
#############################################################################

# Author:   Todd Whiteman
# Date:     16th March, 2009
# Verion:   2.0.0
# License:  Public Domain - free to do as you wish
# Homepage: http://twhiteman.netfirms.com/des.html
#

theanhle

*2vec papers

1. act2vec, trace2vec, log2vec, model2vec https://link.springer.com/chapter/10.1007/978-3-319-98648-7_18
2. apk2vec https://arxiv.org/abs/1809.05693
3. app2vec http://paul.rutgers.edu/~qma/research/ma_app2vec.pdf
4. author2vec http://dl.acm.org/citation.cfm?id=2889382
5. bb2vec https://arxiv.org/pdf/1809.09621.pdf
6. behavior2vec https://dl.acm.org/citation.cfm?id=3184454
7. care2vec https://arxiv.org/abs/1812.00715
8. cat2vec http://104.155.136.4:3000/forum?id=HyNxRZ9xg

theanhle

# Keras==1.0.6
from keras.models import Sequential
import numpy as np
from keras.layers.recurrent import LSTM
from keras.layers.core import TimeDistributedDense, Activation
from keras.preprocessing.sequence import pad_sequences
from keras.layers.embeddings import Embedding
from sklearn.cross_validation import train_test_split
from keras.layers import Merge
from keras.backend import tf

theanhle

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)