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#!/usr/bin/env python

import numpy as np

import nnet

import preprocessing

x = preprocessing.X

y = preprocessing.Y

model = nnet.nnet(x.shape[1:])

model.compile(

optimizer='adam',

loss='binary_crossentropy',

metrics=['accuracy'],

)

model.fit(

x,

y,

batch_size=32,

epochs=10,

validation_split=0.1,

)