+++ /dev/null
-import numpy as np
-from keras.models import model_from_json
-
-with open('model.json', 'r') as f:
- json = f.read()
-
-model = model_from_json(json)
-model.load_weights('./model.hdf5')
-model.compile(
- loss='binary_crossentropy',
- optimizer='rmsprop',
- metrics=['accuracy'])
-
-model.summary()
-
-dat = np.genfromtxt('test.txt', dtype=float, delimiter='\t', usecols=range(1, 14))
-lab = np.genfromtxt('test.txt', dtype=int, delimiter='\t', usecols=[0])
-
-print(model.evaluate(dat, lab, batch_size=32))