import os import json import time import tensorflow.compat.v1 as tf from tensorflow.python.util import deprecation deprecation._PRINT_DEPRECATION_WARNINGS = False tf.disable_v2_behavior() import mnist dirname = os.path.dirname(__file__) train_labels, train_images = mnist.read_csv(os.path.join(dirname, '../data/mnist_train.csv')) DATASET = mnist.DataSet(train_images, train_labels) OUT = os.path.join(dirname, "../models/mnist") batch_size = 128 num_steps = 1800 learning_rate = 0.024 start = time.time() # input x = tf.placeholder(tf.float32, [None, 784], "x") y_ = tf.placeholder(tf.float32, [None, 10], "y") # weight W = tf.Variable(tf.zeros([784, 10])) # bias b = tf.Variable(tf.zeros([10])) # test_data * W + b y = tf.matmul(x, W) + b
import os import json import tensorflow.compat.v1 as tf from tensorflow.python.util import deprecation deprecation._PRINT_DEPRECATION_WARNINGS = False tf.disable_v2_behavior() import mnist dirname = os.path.dirname(__file__) LABELS, IMAGES = mnist.read_csv(os.path.join(dirname, '../data/mnist_test.csv')) META = os.path.join(dirname, '../models/mnist.meta') MODELS = os.path.join(dirname, '../models/') init = tf.global_variables_initializer() with tf.Session() as sess: saver = tf.train.import_meta_graph(META) saver.restore(sess, tf.train.latest_checkpoint(MODELS)) graph = tf.get_default_graph() x = graph.get_tensor_by_name("x:0") y = graph.get_tensor_by_name("y:0") softmax = graph.get_tensor_by_name("softmax:0") accuracy = graph.get_tensor_by_name("accuracy:0") feed_dict = {x: IMAGES, y: LABELS} pred = sess.run([softmax, accuracy], feed_dict=feed_dict)