#pycharm
#save model algorithm, so that don't have to create model everytime for a new prediction. Just load the model saved.
model.save('model.h5')
#add a txt file for testing
----------------------------
import tensorflow as td
from tensorflow import keras
import numpy as np
data = keras.datasets.imdb
#word dictionary, format [{word, digit}...]
word_index = data.get_word_index()
def review_encode(s):
#1 means 'start line'
encoded = [1]
for word in s:
#translate human words to machine digits
if word.lower() in word_index:
encoded.append(word_index[word.lower()])
else:
#2 means 'word not found in dictionary'
encoded.append(2)
return encoded
#load model generated from machine training
model = keras.models.load_model('model.h5')
#assume review is either negative or positive
class_names = ['negative', 'positive']
with open('test.txt', encoding='utf-8') as f:
for line in f.readlines():
#dictionary does not contain symbols and punctuation, only pure english words
nline = line.replace(',','').replace('(','').replace(')','').replace(':','').replace("\"",'').strip().split(' ')
encode = review_encode(nline)
#comply with the data format the model is trained in, 256 words a paragraphy, fill and trim to keep data shape
encode = keras.preprocessing.sequence.pad_sequences([encode], value=0, padding='post', maxlen=256)
predict = model.predict(encode)
print(line)
print(encode)
#predict function input and output are lists, since input is a single paragraph, output[0] is the prediction. A prediction output is a list of numbers, this model only outputs 1 number - predict[0][0], value is between 0 and 1.
print(predict[0], class_names[int(round(predict[0][0]))])
-------------------------------
#logs
If you're in desperate need of 90 minutes of gore-filled violence, Rambo: Last Blood will fill the order. Beyond that, there's nothing of value to be found here.
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[0.34005865] negative
While Sylvester Stallone made the word Rambo synonymous with tough guy action in the 1980s, it's been a long time since he first made the character famous. In fact, it's been over a decade since the last Rambo movie, which itself came two decades before its predecessor. Culture, attitudes, and movies themselves have all changed a lot in that time. I'm not sure anybody was dying for another Rambo movie in 2019, and after having seen Rambo: Last Blood I'm still not sure exactly who this movie is for.
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[0.13580143] negative
It's been 10 years since the events of Rambo, at the end of which, Vietnam War veteran John Rambo (Sylvester Stallone) returned to his family's home in Arizona. We learn as Rambo: Last Blood opens that while on the family ranch, he met Maria (Adriana Barraza) and her granddaughter Gabrielle (Yvette Monreal).
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127 4 60 2568 322 2493 305 3953 13509 5808 3779 5
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[0.10586126] negative
The three of them have lived together on the Rambo ranch where John trains horses and he's become a surrogate father to Gabrielle. Rambo appears mostly at peace, though John's constructed a series of tunnels beneath the property where he keeps a pretty significant arsenal, because he is Rambo, after all.
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[0.36746112] negative
-----------------------------------------------------
#copy and paste into test.txt positive reviews, run again
#logs
With its energy, its creativity, its raw passion and its fun, this film and its newcomer cast are the best thing I’ve seen at this year’s Toronto film festival.
[[ 1 16 91 1705 91 4855 91 2818 1794 2 91 250
11 19 2 91 6947 174 23 1 115 152 32871 107
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[0.71682703] positive
It’s a social-realist adventure written by Theresa Ikoko and Claire Wilson and directed by Sarah Gavron about a multi-ethnic community in East London - in the spirit of Ken Loach’s Kes or Céline Sciamma’s Bande Des Filles. It’s tough, but it’s the opposite of miserablist. At the story’s centre is a group of year 11 girls and the star is Bukky Bakray, playing a Nigerian British girl nicknamed “Rocks”, who is maybe no great academic high-flier but really talented at cosmetics. Her dad is dead and she lives with her troubled mum, who has had, as a social worker delicately puts it, issues managing her medication.
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[0.69423324] positive
It is Rocks who largely has the responsibility of minding her kid brother, Emmanuel, gloriously played by D’Angelou Osei Kissiedu – and Emmanuel is a black-belt scene-stealer. He starts the film the way he means to go on, with a hilarious setpiece. Asking if he may say grace before dinner, Emmanuel launches into his own version of the Lord’s Prayer: “Our father – he’s up in heaven.” Rocks cheerfully calls that his “remix”. But there’s real trouble when Rocks’s mum absents herself from the family home.
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[0.7644717] positive
The odyssey of Rocks and Emmanuel – who in effect go on the run, fugitives from the world of grownup authority – provides a motor that drives the film but, in a way, its best moments come when Rocks and her friends are doing nothing more dramatically significant than just hanging out, talking and laughing. Occasionally these scenes erupt into something defiant, as when a food fight monumentally kicks off in the middle of a home economics class or when a girl tells her grumpy teacher: “You’re like this because you’ve got your period, sir.” (He furiously replies: “That’s actually really offensive.”)
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[0.64768946] positive
But really, the improv-type dialogue doesn’t need to go anywhere or do anything to be hugely entertaining and watchable. The group around Rocks are capable, in the best possible way, of laughing about nothing, laughing from sheer directionless joy. The sadness, when it comes, is piercing – yet so is Rocks’s resilience and her philosophical acceptance. Bukky Bakray gives a very moving portrayal of someone who has boldly accepted maternal responsibility for Emmanuel at the very moment that she is to be deprived of it.
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[0.63985294] positive
Of course, there is a larger sadness here: the realisation that the sheer energy and dynamism of this group is likely to be dissipated and wasted when they leave school – society will probably not find a way to tap this resource. When the class is taught about Picasso and cubism and they make spoof Picasso cut-out images of people’s faces cut from magazines, it is a funny moment, but serious too, because there is a real sense of potential. This film is such a rush of vitality. It rocks.
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[0.6369015] positive
----------------------------------
reference:
http://chuanshuoge2.blogspot.com/2019/09/neural-network-6.html
https://www.youtube.com/watch?v=Xmga_snTFBs&list=PLzMcBGfZo4-lak7tiFDec5_ZMItiIIfmj&index=8
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