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rnn_play - WORKS AND HE THERES YUPPIEEEE.py
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rnn_play - WORKS AND HE THERES YUPPIEEEE.py
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# encoding: UTF-8
# Copyright 2017 Google.com
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import tensorflow as tf
import numpy as np
import my_txtutils
# these must match what was saved !
ALPHASIZE = my_txtutils.ALPHASIZE
NLAYERS = 3
INTERNALSIZE = 512
# Data files can be downloaded from the following locations:
# - Fully trained on Shakespeare or Tensorflow Python source:
# https://drive.google.com/file/d/0B5njS_LX6IsDc2lWTmtyanRpOHc/view?usp=sharing
# - Partially trained, to see how they make progress in training:
# https://drive.google.com/file/d/0B5njS_LX6IsDUlFsMkdhclNSazA/view?usp=sharing
shakespeareC0 = "checkpoints/rnn_train_1495455686-0" # random
shakespeareC1 = "checkpoints/rnn_train_1495455686-150000" # lower case gibberish
shakespeareC2 = "checkpoints/rnn_train_1495455686-300000" # words, paragraphs
shakespeareC3 = "checkpoints/rnn_train_1495455686-450000" # structure of a play, unintelligible words
shakespeareC4 = "checkpoints/rnn_train_1495447371-15000000" # better structure of a play, character names (not very good), 4-letter words in correct English
shakespeareC5 = "checkpoints/rnn_train_1495447371-45000000" # good names, even when invented (ex: SIR NATHANIS LORD OF SYRACUSE), correct 6-8 letter words
shakespeareB10 = "checkpoints/rnn_train_1495440473-102000000" # ACT V SCENE IV, [Re-enter KING JOHN with MARDIAN], DON ADRIANO DRAGHAMONE <- invented!
# most scene directions correct: [Enter FERDINAND] [Dies] [Exit ROSALIND] [To COMINIUS with me] [Enter PRINCE HENRY, and Attendants], correct English.
pythonA0 = "checkpoints/rnn_train_1495458538-300000" # gibberish
pythonA1 = "checkpoints/rnn_train_1495458538-1200000" # some function calls with parameters and ()
pythonA2 = "checkpoints/rnn_train_1495458538-10200000" # starts looking Tensorflow Python, nested () and [] not perfect yet
pythonB10 = "checkpoints/rnn_train_1495458538-201600000" # can even recite the Apache license
# use topn=10 for all but the last one which works with topn=2 for Shakespeare and topn=3 for Python
author = "checkpoints/rnn_train_1499167699-0"#shakespeareC0
ncnt = 0
with tf.Session() as sess:
new_saver = tf.train.import_meta_graph('checkpoints/rnn_train_1499167699-0.meta')
new_saver.restore(sess, author)
x = my_txtutils.convert_from_alphabet(ord("L"))
x = np.array([[x]]) # shape [BATCHSIZE, SEQLEN] with BATCHSIZE=1 and SEQLEN=1
# initial values
y = x
h = np.zeros([1, INTERNALSIZE * NLAYERS], dtype=np.float32) # [ BATCHSIZE, INTERNALSIZE * NLAYERS]
for i in range(1000000000):
yo, h = sess.run(['Yo:0', 'H:0'], feed_dict={'X:0': y, 'pkeep:0': 1., 'Hin:0': h, 'batchsize:0': 1})
# If sampling is be done from the topn most likely characters, the generated text
# is more credible and more "english". If topn is not set, it defaults to the full
# distribution (ALPHASIZE)
# Recommended: topn = 10 for intermediate checkpoints, topn=2 or 3 for fully trained checkpoints
c = my_txtutils.sample_from_probabilities(yo, topn=10)
y = np.array([[c]]) # shape [BATCHSIZE, SEQLEN] with BATCHSIZE=1 and SEQLEN=1
c = chr(my_txtutils.convert_to_alphabet(c))
print(c, end="")
if c == '\n':
ncnt = 0
else:
ncnt += 1
if ncnt == 100:
print("")
ncnt = 0
# TITUS ANDRONICUS
#
#
# ACT I
#
#
#
# SCENE III An ante-chamber. The COUNT's palace.
#
#
# [Enter CLEOMENES, with the Lord SAY]
#
# Chamberlain Let me see your worshing in my hands.
#
# LUCETTA I am a sign of me, and sorrow sounds it.
#
# [Enter CAPULET and LADY MACBETH]
#
# What manner of mine is mad, and soon arise?
#
# JULIA What shall by these things were a secret fool,
# That still shall see me with the best and force?
#
# Second Watchman Ay, but we see them not at home: the strong and fair of thee,
# The seasons are as safe as the time will be a soul,
# That works out of this fearful sore of feather
# To tell her with a storm of something storms
# That have some men of man is now the subject.
# What says the story, well say we have said to thee,
# That shall she not, though that the way of hearts,
# We have seen his service that we may be sad.
#
# [Retains his house]
# ADRIANA What says my lord the Duke of Burgons of Tyre?
#
# DOMITIUS ENOBARBUS But, sir, you shall have such a sweet air from the state,
# There is not so much as you see the store,
# As if the base should be so foul as you.
#
# DOMITIUS ENOY If I do now, if you were not to seek to say,
# That you may be a soldier's father for the field.
#
# [Exit]