Exemple #1
0
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
Exemple #2
0
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)