Tensorflow手写数字softmax识别
Tensorflow手写数字softmax识别百度网盘链接：链接：http://pan.baidu.com/s/1c1OJp4G百度网盘代码分享：http://pan.baidu.com/s/1eRQcCuu
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import argparse
import sys
from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
import Get_Mnist_Data
#mnist = input_data.read_data_sets('/temp/', one_hot=True)
mnist = Get_Mnist_Data.read_data_sets('Get_Mnist_Data', one_hot=True)
# Create the model
x = tf.placeholder(tf.float32, )
W = tf.Variable(tf.zeros())
b = tf.Variable(tf.zeros())
y = tf.matmul(x, W) + b
# Define loss and optimizer
y_ = tf.placeholder(tf.float32, )
cross_entropy = tf.reduce_mean(
tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y))
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
sess = tf.InteractiveSession()
tf.global_variables_initializer().run()
# Train
for _ in range(1000):
batch_xs, batch_ys = mnist.train.next_batch(100)
sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
# Test trained model
correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
print(sess.run(accuracy, feed_dict={x: mnist.test.images,
y_: mnist.test.labels}))
我反复看了多遍，好帖，得支持
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