逐渐的人工智能已走入了日常生活中了，从对联生成器到古诗生成器，从智能翻译到机器写作，有时候看UC头条的新闻，感觉很多逻辑混乱的文章，有可能就是机器写作的也可能是机器翻译出来的，不管怎么样，文本写作已经成为人工智能的一个重要场景了。
在《keras深度学习实战》书籍中有关于爱丽丝梦游仙境的例子，本文不仅仅是原封不动的还原代码，也包括自己对代码的理解和总结。虽然不成熟，起码也思考了，希望下个章节能够改进一下算法，或支持一下中文写作。
代码示例
# -*- coding: utf-8 -*-
from __future__ import print_function
from keras.layers.recurrent import SimpleRNN
from keras.models import Sequential
from keras.layers import Dense, Activation
import numpy as np
#从网上获取爱丽丝梦游仙境文本
INPUT_FILE = "alice.txt"
# 抽取文件，并进行清洗
print("Extracting text from input...")
fin = open(INPUT_FILE, 'rb')
lines = []
for line in fin:
line = line.strip().lower()
line = line.decode("ascii", "ignore")
if len(line) == 0:
continue
lines.append(line)
fin.close()
text = " ".join(lines)
print(text)
#爱丽丝梦游仙境文本格式如下：合计142773长度
#chapter i down the rabbit-hole chapter i down the rabbit-hole alice was beginning to get very tired of sitting by h
#142773
# 创建查找表
chars = set([c for c in text])
#{'h', 'u', ';', 'e', 'q', 'j', '_', '`', 'z', 'd', 'v', 'x', "'", 'n', 'k', '(', '?', 'p', 'y', 'o', ')', 'c', '*', 'r', '!', 'i', 'w', '"', 'g', 't', 's', '-', 'l', ',', 'm', ':', 'a', '.', 'f', 'b', ' '}
nb_chars = len(chars)
#41
#创建字符索引
char2index = dict((c, i) for i, c in enumerate(chars))
#{'h': 0, 'u': 1, ';': 2, 'e': 3, 'q': 4, 'j': 5, '_': 6, '`': 7, 'z': 8, 'd': 9, 'v': 10, 'x': 11, "'": 12, 'n': 13, 'k': 14, '(': 15, '?': 16, 'p': 17, 'y': 18, 'o': 19, ')': 20, 'c': 21, '*': 22, 'r': 23, '!': 24, 'i': 25, 'w': 26, '"': 27, 'g': 28, 't': 29, 's': 30, '-': 31, 'l': 32, ',': 33, 'm': 34, ':': 35, 'a': 36, '.': 37, 'f': 38, 'b': 39, ' ': 40}
index2char = dict((i, c) for i, c in enumerate(chars))
#{0: 'h', 1: 'u', 2: ';', 3: 'e', 4: 'q', 5: 'j', 6: '_', 7: '`', 8: 'z', 9: 'd', 10: 'v', 11: 'x', 12: "'", 13: 'n', 14: 'k', 15: '(', 16: '?', 17: 'p', 18: 'y', 19: 'o', 20: ')', 21: 'c', 22: '*', 23: 'r', 24: '!', 25: 'i', 26: 'w', 27: '"', 28: 'g', 29: 't', 30: 's', 31: '-', 32: 'l', 33: ',', 34: 'm', 35: ':', 36: 'a', 37: '.', 38: 'f', 39: 'b', 40: ' '}
# 创建输入和标签文本
# STEP变量给出字符数目，此处为1
# SEQLEN定义文本段，此处为10
# assuming an input text "The sky was falling", we would get the
# following sequence of input_chars and label_chars (first 5 only)
# The sky wa -> s
# he sky was ->
# e sky was -> f
# sky was f -> a
# sky was fa -> l
print("Creating input and label text...")
SEQLEN = 10
STEP = 1
input_chars = []
label_chars = []
for i in range(0, len(text) - SEQLEN, STEP):
#print(text[i:i + SEQLEN],'~~~~~~~~~~',text[i + SEQLEN])
#gging her ~~~~~~~~~~ s
#ging her s ~~~~~~~~~~ h
#ing her sh ~~~~~~~~~~ a
input_chars.append(text[i:i + SEQLEN])
label_chars.append(text[i + SEQLEN])
#print('input_chars=',input_chars)
#n the danc
# the dance
#the dance?
#he dance?
#print('label_chars=',label_chars)
#d
#o
#w
#n
# 把输入和标签文本向量化
# RNN输入的每行对应前面展示的一个输入文本
# 输入中共有SEQLEN-10个字符
# 字典大小由nb_chars-41给定,把每个字符表示成one-hot编码的大小为nb_chars的向量
# 每行输入就是一个大小为（SEQLEN-10，nb_chars-41）的张量
# 输出标签是一个单个的字符，所以和输入的每个字符表示类似
# 输出标签表示为（nb_chars-41)的one-hot编码的向量
print("Vectorizing input and label text...")
X = np.zeros((len(input_chars), SEQLEN, nb_chars), dtype=np.bool)
# X形状为(142763, 10, 41)，类型为bool，缺省值为False
y = np.zeros((len(input_chars), nb_chars), dtype=np.bool)
# y形状为(142763, 41)，类型为bool，缺省值为False
#遍历每个单词
for i, input_char in enumerate(input_chars):
#遍历每个字符
for j, ch in enumerate(input_char):
#print(i,input_char,j,ch)
#138004 course-- " 4 s
#138004 course-- " 5 e
#138004 course-- " 6 -
#把对应的单词，字符和索引索引置为1
X[i, j, char2index[ch]] = 1
#把对应的单词和字符索引位置置为1
y[i, char2index[label_chars[i]]] = 1
#print(i,label_chars[i],char2index[label_chars[i]])
#50011 h 37
#50012 i 10
#print('X=',X)
#X= [[[False False False ... False False False]
# ...
# [False False False ... False False True]]
#
# [[False False False ... False False False]
# ...
# [False False False ... False False True]]
# [[ True False False ... False False False]
# ...
# [False False True ... False False False]]]
#print('y=',y)
#y= [[False False False ... False False False]
# [False False False ... False False False]
# [False False False ... False False False]
# ...
# [False False False ... True False False]
# [False False True ... False False False]
# [False False False ... False False False]]
#构建模型
HIDDEN_SIZE = 128
#BATCH_SIZE = 128
#NUM_ITERATIONS = 25
BATCH_SIZE = 128
NUM_ITERATIONS = 50
NUM_EPOCHS_PER_ITERATION = 1
NUM_PREDS_PER_EPOCH = 100
model = Sequential()
#将RNN输出维度大小定义为128
#选择值太小，模型不具有生成较好文本的有效容量，会看到重复字符或重复词组的长时运行
#选择值太大，模型参数过多，需要很多数据才能有效训练
model.add(SimpleRNN(HIDDEN_SIZE, return_sequences=False,
input_shape=(SEQLEN, nb_chars),
unroll=True))
#创建一个全连接dense层，dense层有nb_chars个单元，为字典中每个字符发出评分
model.add(Dense(nb_chars))
#全连接层激活函数是softmax，把分数标准化为概率，概率最高的字符即成为预测字符。
model.add(Activation("softmax"))
#用分类输出中出色的分类交叉熵函数作为损失函数
model.compile(loss="categorical_crossentropy", optimizer="rmsprop")
# 一共迭代25次
for iteration in range(NUM_ITERATIONS):
print("=" * 50)
print("Iteration #: %d" % (iteration))
model.fit(X, y, batch_size=BATCH_SIZE, epochs=NUM_EPOCHS_PER_ITERATION)
#model.fit(X, y, batch_size=142763, epochs=NUM_EPOCHS_PER_ITERATION)
# 测试模型
# 给定一个随机的输入
test_idx = np.random.randint(len(input_chars))
#从模型中生成一个字符
test_chars = input_chars[test_idx]
#test_chars = 'alice'
#打印随机选出的种子字符
print("Generating from seed: %s" % (test_chars))
print('result=',test_chars, end="")
#持续进行100次，生成并打印结果字符串，即生成100长度的字符串
for i in range(NUM_PREDS_PER_EPOCH):
Xtest = np.zeros((1, SEQLEN, nb_chars))
for i, ch in enumerate(test_chars):
Xtest[0, i, char2index[ch]] = 1
#print('0, i, char2index[ch]]=',i,char2index[ch])
#print(Xtest)
pred = model.predict(Xtest, verbose=0)[0]
ypred = index2char[np.argmax(pred)]
print(ypred, end="")
# move forward with test_chars + ypred
test_chars = test_chars[1:] + ypred
print()
#BATCH_SIZE = 10000
#NUM_ITERATIONS = 100
#test_chars=random char
# he lory, w
# ck turtle, ao ho he oo ho he oo ho he oo ho he oo ho he oo ho he oo ho he oo ho he oo
# ust begun the ao ae ao ae ao ae ao ae ao ae ao ae ao ae ao ae ao ae ao ae ao ae ao ae
# next peep ao the ao the ao the ao the ao the ao the ao the ao the ao the ao the ao the ao the ao
# g. `and ju the ao he ao he ao he ao he ao he ao he ao he ao he ao he ao he ao he ao he
# den you ev the ao he ao ao he ao ao he ao ao he ao ao he ao ao he ao ao he ao ao he ao
# gerly, for the the the the the the the the the the the the the the the the the the the the the the the the the
# the rabbit an the he the the the the the the the the the the the the the the the the the the the the the the
# queer ind the aid the sard the sard the sard the sard the sard the sard the sard the sard the sard the sard
# ; but she said the said the said the said the said the said the said the said the said the said the said the s
# y until it and the sare the sare the sare the sare the sare the sare the sare the sare the sare the sare the s
# wn the lithe sout and the sout the was ing the are the sout the was ing the are the sout the was ing the ar
# and quietling the said the said the said the said the said the said the said the said the said the said the sa
# ers in the wast and the sare the sare the sare the sare the sare the sare the sare the sare the sare the sare
# here, bill the said the sard the sar said the sard the sar said the sard the sar said the sard the sar said t
# tering ove the southe sald the sare the sare the sare the sare the sare the sare the sare the sare the sare th
# said alice sas ing the was in the was in the was in the was in the was in the was in the was in the was in th
# swam near and the sare the sar she cat se the was in the said the said the said the said the said the said th
# `of course for the the said the more the said the more the said the more the said the more the said the more t
# its head the wast ou the the said the wast ou the the said the wast ou the the said the wast ou the the said
# d the moon the said the sallere the said the sallere the said the sallere the said the sallere the said the sa
# d'; and she said the said the said the said the said the said the said the said the said the said the said the
# sure whethe wast and the wast oure and the wast oure and the wast oure and the wast oure and the wast oure and
# to her usus the said the sald the said the sald the said the sald the said the sald the said the sald the said
# n to look the she her alice sad the growe the said the dore the she said the dore the she said the dore the sh
# s the stuped an the coust of at ing tore the mouthe said the more the said the more the said the more the said
# as going of the southe said the more the said the more the said the more the said the more the said the more t
# list of she sound he sere the said the mack to the was in the was in the was in the was in the was in the was
# poor alice sad the coust on the the harded the harded the harded the harded the harded the harded the harded
# ner!' cried an the said the mack ture said the mack ture said the mack ture said the mack ture said the mack t
# be shutting tore the mouthe said the mack turele the was the was the was the was the was the was the was the
# her, about the growe the the grithe the grithe the grithe the grithe the grithe the grithe the grithe the grit
# y over alice sad the d at she sad she don the d at she sad she don the d at she sad she don the d at she sad s
# self, `if the said the donge for and the donge for and the donge for and the donge for and the donge for and t
# me that fire the mast the said the mack turele the said the mack turele the said the mack turele the said the
# ome, there the said the dore the she the donge said the dore the she the donge said the dore the she the donge
# as an unuthe sad the dored so she was so the king the was so the king the was so the king the was so the king
# ' `so they wish as all to the marte the marte the marte the marte the marte the marte the marte the marte the
# ke to piece to the rither all the dong the said the dore the mouthe the said the dore the mouthe the said the
# f i shall the said the harded and alice said the harded and alice said the harded and alice said the harded an
# ell, at and the donge said the donge said the donge said the donge said the donge said the donge said the dong
# e queen! the wast of the harded and the growe the growe the growe the growe the growe the growe the growe the
# reason of the said the mack turele the was ous the was ous the was ous the was ous the was ous the was ous th
# d still whe the har she was the way her alice sad the cares in the harded the har her all the was of the har s
# le. i wond and the was of the said the could and the was of the said the could and the was of the said the cou
# ' said alice said the mouthe said the mouthe said the mouthe said the mouthe said the mouthe said the mouthe s
# th, and it and the wast of the harded and the moust of the harded and the moust of the harded and the moust of
# ny rate, the was of the mous the mous the mous the mous the mous the mous the mous the mous the mous the mous
# cheered, and the growe the growe the growe the growe the growe the growe the growe the growe the growe the gr
# g merrily an the could be the said the dored she had the dored she had the dored she had the dored she had the
# uld go thry har said the cat out the was of the had and the gat has look to the donde say the way har alice sa
# d the grean the could the could the could the could the could the could the could the could the could the coul
# thought alice said the gryphon inge the gring the said the gryphon inge the gring the said the gryphon inge th
# und an oppeat it on the could be the could be the could be the could be the could be the could be the could be
# as in the said to the rabbet it all the was of the said to the rabbet it all the was of the said to the rabbet
# shock of be the said the donge said the donge said the donge said the donge said the donge said the donge said
# phon. `we the there the mast the cate the mouse fore the madd the mack to the rabbet at it and the wast of the
# hness?' `realice and all as it a the har her alice all at it a the har her alice all at it a the har her alice
# nk it was, the came the marte to the dored and the dore the mores in the said to the dored and the dore the mo
# no time she had all the harded and the growe the hat her the harded and the growe the hat her the harded and
# n minutes the was of the said the mack to the rouse she was of the said the mack to the rouse she was of the s
# d ordered. `in the say said to the donge wat on the madde was a ling on the said the mack to the roush she was
# the cook the marth the mart the mad the mack turtle the dond on the donge the gring the was of the dorse the
# ou are all the mouth and the doon the mad the mouse sa done with the king the mouse sa done with the king the
# sidering her alice the mouse said the mack turtle the was of the moust on the was of the moust on the was of t
# e of the donge wat the way so the don't and the doon the way so the don't and the doon the way so the don't an
# thought alice, `in's a down the gat hourd and the gryphon it of chast her was of the harded to her all the wa
# it tricksen the gat hourden the was of the could be the cat out the was of the could be the cat out the was o
# read-knifer the said the dores it was the dores it was the dores it was the dores it was the dores it was the
# way up as it as and the say the was erought the harte for the said the dore the mores it a could her to the d
# `but i mustle to the dorse the cat of the sare the could and the dorse the cat of the sare the could and the d
# tle girl of the soof hing to see the hard the could be the could be the could be the could be the could be the
# ed at it grown the was of the said the doon the marther said the doon the marther said the doon the marther sa
# rot away quite and all as and the catere the could be the catere the could be the catere the could be the cate
# vered his mouse be the say the way or the could and the soof anowe to the rouse said to herself, `i don't the
# t by the erought the harter the har she sad the dore the could bet mo the har her the har she sad the dore the
# by producing the dorse for the was of the sare the dorse for the was of the sare the dorse for the was of the
# at the nuther a done said the dock turtle the harded the harded the harded the harded the harded the harded t
# nother snat it all the catt at the say said the mack to the rabbet mast the cat of the could and the say said
# trial's be the say the was of the mores it said the dorme the har she was not leat do she her for the was the
# d see, whe the king to the dore the could be the catt reat her the harde for the mack to the dore the could be
# nocking,' said the could be the said the could be the said the could be the said the could be the said the cou
# ok his head the could at and the say the was the was the was the was the was the was the was the was the was t
# ll you, you know she last down the say so for and the say so for and the say so for and the say so for and the
# their curly had for the harded to the dorme the harded to the dorme the harded to the dorme the harded to the
# l whether said to herself to the dore of the marth urse the marte said to herself to the dore of the marth urs
# y wrote do goon the mouse betone of the could be the cat of and the king to the king to the king to the king t
# nt to stay she was not mean she said the gryphon the say she was not mean she said the gryphon the say she was
# more puzzled the mouse so gat in a the said the mouse so gat in a the said the mouse so gat in a the said the
# d better not of the some to the say she was a look an the could all was the harter and her alice the gat here
# low with it the dormouse the could be the said the dormouse the could be the said the dormouse the could be th
# ily on slack of the mouse say the gat it and the dores it was the door as the could an the came the marth a do
# fter them!' said the cat of the har she said the cat of the har she said the cat of the har she said the cat o
# nd she, oh the the could all whing to she cat of chart which was the could all whing to she cat of chart which
# t, being mo ding the mouse of the mouse of the mouse of the mouse of the mouse of the mouse of the mouse of th
# much conter of the soof a atile the parce to the dormouse the could at the could at the could at the could at
# ing up in a long the mares it was the was the mack turtle the sabe to the mares it was the was the mack turtle
# y it ran and whing to she said the mouse beto doon the marth a dong on the sare the could be the say the way t
# with one extly soon the marth a mone that it was the mart the marth a mone that it was the mart the marth a mo
# han't! you know the mouse sad the was the growh her her had for the harde was the growh her her had for the ha
#BATCH_SIZE = 128
#NUM_ITERATIONS = 50
#test_chars=random char
#id alice; `ind he wall the wall the wall the wall the wall the wall the wall the wall the wall the wall the wa
#at all. `be the was the was the was the was the was the was the was the was the was the was the was the was th
# on each so the rould all the tore the rould all the tore the rould all the tore the rould all the tore the ro
#id so, and was in the had her said the mouthe to the say her same the mouthe to the say her same the mouthe to
#hapter v and it a a mance said the gryphon in a and the sait the mack the gryphon in a and the sait the mack t
#ant to go see the mock turtle sear the rabbed and the satter a marce the was she was not in the was she was no
#the hatter the read the gryphon said the gryphon said the gryphon said the gryphon said the gryphon said the g
#t, jumping the dore with the gryphon a little so mack to the gryphon a little so mack to the gryphon a little
#, that alice a don't be a little she was nother the rabbit was the ery, and the mouse was she said the caterpi
#ously replied in a little and the sore of the sore of the sore of the sore of the sore of the sore of the sore
#ked, with her head a soup of a little got the dormouse for a little got the dormouse for a little got the dorm
#could, if a to har she said the mock turtle said to the gryphon, and the mock turtle said to the gryphon, and
#ad said the mors the dormouse the mors the dormouse the mors the dormouse the mors the dormouse the mors the d
#ossed the rabbit haster a with the rabbit haster a with the rabbit haster a with the rabbit haster a with the
#seven jogg not in a was not in a was not in a was not in a was not in a was not in a was not in a was not in a
#o my boy, and the mock turtle some of the errout for the mock turtle some of the errout for the mock turtle so
#l, it must be a mame the hatter was a look a marter the rabbit and the mouse the mouse the mouse the mouse the
#ed alice. `it's a little she was the read the round. `they were the erreat of the words all reading her all th
#t about it was not in the rabbit was the rabbit was the rabbit was the rabbit was the rabbit was the rabbit wa
#their face in the look the looked at the mock turtle the last the tone, and the dormouse the dormouse the dorm
# `i know what it was a great one on the way in a very the jury and the white rabbit and said to the plose to t
# direction in the dormouse don't be a little be the cat on the court to be a marking that the dormouse don't b
#d of mine--on it must be off the right in a very some of the dormouse the mock turtle in a little she went on
#g,' said the caterpillar the caterpillar the caterpillar the caterpillar the caterpillar the caterpillar the c
#te much accuritule the way the wase that she was no door of the hatter with the hatter with the hatter with th
# like it, and she was to see of the long and alice a can in a little shrilking about the sout very good to the
#nt,' and she seant which she her fand him all the rabbit here all the stood here with a don't be a marked and
#into the cook and the words with the rabbit alice to the room, and they were the mock turtle and the words wit
#deal frightened to her hands, and was not a mant with the white rabbit some the hatter with the white rabbit s
# memory, and she said to herself in a mort to be a little sharing down and great such a can't the room, and sh
# the duchess were like the poor as the door as the door as the door as the door as the door as the door as the
#with. alice thought the dormouse the door the rabbit was of the table. `now it was a little that the rabbit wa
#ls in its down to herself to her hands and was very croquetting in the wase that her eyes a little got to the
#tone. `praided to here and the words with the gryphon, and the words with the gryphon, and the words with the
#nly know her lifting a tone on the end of the tires in the right all the right all the right all the right all
#y it too: she was not as she said to herself, `i don't be a little sharppean wall be trees would be a minute o
#le for it, i don't be a minute on the door as mouth a down the commoute of the tame off and the cook again, an
# very sorrout for a great had the rabbit has hearts in a large all have had not a large all have had not a lar
#ds; `so not to the door a looking and shouted the door a looking and shouted the door a looking and shouted th
#igently to go and the gryphon ander with the gryphon ander with the gryphon ander with the gryphon ander with
#rink me' beauting of the sort as she car and the white rabbit had been that she had not the bolkn't be so mark
#know all the king out of the stalles were said to herself, `on the story, and she had for the hatter, and the
#get into the words of the mouse they were all round a dear face and the caterpillar. `i'm to the roots and she
#se?' said the door as she spoke that the looked at the things it was a door what you have to the tame the door
#ar off to the things it was a little shrough of the were to the right and she seaning the white rabbit asked i
#ed very poor she little got to the first to be a marted to the footman the mouse to the mock turtle said, `it
# anything the gryphon with a she was sore and she was sore and she was sore and she was sore and she was sore
#y, it fillow the king, and the white rabbit had been to herself, and the white rabbit had been to herself, and
# herself had and the dormouse in a very curious to see hor she was some of the bolkn't me sire of the gryphon,
#nches high it was the dormouse in the mock turtle in a low the least to the mock turtle in a low the least to
