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View rnn
import theano
import theano.tensor as T
import numpy as np
import cPickle
import random
import matplotlib.pyplot as plt
class RNN(object):
def __init__(self, nin, n_hidden, nout):
View gensim doc2vec tutorial
from gensim import models
sentence = models.doc2vec.LabeledSentence(
words=[u'so`bme', u'words', u'here'], tags=["SENT_0"])
sentence1 = models.doc2vec.LabeledSentence(
words=[u'here', u'we', u'go'], tags=["SENT_1"])
sentences = [sentence, sentence1]
class LabeledLineSentence(object):
balajikvijayan /
Created Nov 17, 2015 — forked from karpathy/
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
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)
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