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update

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Newnius 2020-05-02 18:32:07 +08:00
parent 6b4494c334
commit 0f4ee70297
2 changed files with 28 additions and 19 deletions
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30
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17
serve.py
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@ -18,6 +18,7 @@ from keras.layers import Dense
from keras.layers import LSTM from keras.layers import LSTM
from math import sqrt from math import sqrt
import numpy import numpy
import random
PORT_NUMBER = 8080 PORT_NUMBER = 8080
lock = Lock() lock = Lock()
@ -134,13 +135,21 @@ def predict(job, seq):
if job not in models or 'model' not in models[job]: if job not in models or 'model' not in models[job]:
return -1, False return -1, False
# load dataset
batch_size = int(models[job]['batch_size']) batch_size = int(models[job]['batch_size'])
df = read_csv('./data/' + job + '.csv', header=0, index_col=0, squeeze=True) data = {
'seq': seq,
'value': 0,
}
file = './data/' + job + '.' + random.randint(1000, 9999) + '.csv'
df = pd.read_csv('./data/' + job + '.csv', usecols=['seq', 'value'])
df = df.tail(batch_size * 2 - 1) df = df.tail(batch_size * 2 - 1)
df.loc[df.shape[0]] = [seq, 0] df = df.append(data, ignore_index=True)
df.to_csv(file, index=False)
# load dataset
df = read_csv(file, header=0, index_col=0, squeeze=True)
# transform data to be stationary # transform data to be stationary
raw_values = df.values raw_values = df.values