[PYTHON/TENSORFLOW] 신경망 모델 로드하기

■ 신경망 모델을 로드하는 방법을 보여준다.

▶ 예제 코드 (PY)


import random
import tensorflow as tf
import tensorflow.examples.tutorials.mnist as mnist

mnistDatasets = mnist.input_data.read_data_sets("data", one_hot = True)

session = tf.InteractiveSession()

saver = tf.train.import_meta_graph("data/mnist_1_layer_softmax.ckpt.meta")

saver.restore(session, "data/mnist_1_layer_softmax.ckpt")

tf.get_default_graph().as_graph_def()

inputTensor  = session.graph.get_tensor_by_name("input:0" )
outputTensor = session.graph.get_tensor_by_name("output:0")

testImageIndex   = random.randint(0, mnistDatasets.test.images.shape[0])
testImageNDArray = mnistDatasets.test.images[testImageIndex]

result = session.run(["input:0", outputTensor], feed_dict = {inputTensor : [testImageNDArray]})

print("정답 : ", session.run(tf.argmax(mnistDatasets.test.labels[testImageIndex])))
print("판단 : ", session.run(tf.argmax(result[1], 1)[0]))

import random

import tensorflow as tf

import tensorflow.examples.tutorials.mnist as mnist

mnistDatasets = mnist.input_data.read_data_sets("data", one_hot = True)

session = tf.InteractiveSession()

saver = tf.train.import_meta_graph("data/mnist_1_layer_softmax.ckpt.meta")

saver.restore(session, "data/mnist_1_layer_softmax.ckpt")

tf.get_default_graph().as_graph_def()

inputTensor = session.graph.get_tensor_by_name("input:0" )

outputTensor = session.graph.get_tensor_by_name("output:0")

testImageIndex = random.randint(0, mnistDatasets.test.images.shape[0])

testImageNDArray = mnistDatasets.test.images[testImageIndex]

result = session.run(["input:0", outputTensor], feed_dict = {inputTensor : [testImageNDArray]})

print("정답 : ", session.run(tf.argmax(mnistDatasets.test.labels[testImageIndex])))

print("판단 : ", session.run(tf.argmax(result[1], 1)[0]))