keras34_gpu_test.py

#gpu와 cpu 성능 테스트 모델

import tensorflow as tf
from keras.applications import Xception
from keras.utils import multi_gpu_model
import numpy as np
import datetime

''' 처리시간
 GPU 처리시간 :  0:00:32.044086
 CPU 처리시간 :  0:00:54.327245 '''

num_samples =100
height = 71
width = 71
num_classes = 100

print("GPU 시간 측정 시작 !!!")
start1 = datetime.datetime.now()
with tf.device('/gpu:0'):
    model = Xception(weights=None,
                     input_shape=(height, width, 3), classes=num_classes)
    model.compile(loss='categorical_crossentropy', optimizer='rmsprop')

    # Generate dummy data.
    x = np.random.random((num_samples, height, width, 3))
    y = np.random.random((num_samples, num_classes))

    model.fit(x, y, epochs=3, batch_size=16) 

    model.save('./model/time_check1.h5')

end1 = datetime.datetime.now()
time_delta1 = end1 - start1

print("GPU 시간 측정 끝 !!!")
print("CPU 시간 측정 시작 !!!")
start2 = datetime.datetime.now()
with tf.device('/cpu:0'):
    model = Xception(weights=None,
                     input_shape=(height, width, 3), classes=num_classes)
    model.compile(loss='categorical_crossentropy', optimizer='rmsprop')

    # Generate dummy data.
    x = np.random.random((num_samples, height, width, 3))
    y = np.random.random((num_samples, num_classes))

    model.fit(x, y, epochs=3, batch_size=16) 

    model.save('./model/time_check2.h5')

end2 = datetime.datetime.now()
time_delta2 = end2 - start2


print('GPU 처리시간 : ', time_delta1)
print('CPU 처리시간 : ', time_delta2)