# HG changeset patch # User Jeff Hammel # Date 1513549415 28800 # Node ID 3ff05538259c11c08930d435180982326098859f # Parent 800f3938ebaa5dda55f80b28d1f6c8a803f3c6c1 mnist example diff -r 800f3938ebaa -r 3ff05538259c tvii/mnist.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tvii/mnist.py Sun Dec 17 14:23:35 2017 -0800 @@ -0,0 +1,51 @@ +#!/usr/bin/env python + +""" +https://www.tensorflow.org/get_started/mnist/beginners + +Exercise to reader: compare + contrast to +https://github.com/tensorflow/tensorflow/blob/r1.1/tensorflow/examples/tutorials/mnist/mnist_softmax.py +""" + +import sys +import tensorflow as tf +from .cli import CLIParser as Parser +from tensorflow.examples.tutorials.mnist import input_data +mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) + +def main(args=sys.argv[1:]): + """CLI""" + + parser = Parser(description=__doc__) + options = parser.parse_args(args) + + # 28*28 = 784 + x = tf.placeholder(tf.float32, [None, 784]) + + # A Variable is a modifiable tensor that lives in TensorFlow's + # graph of interacting operations. + # It can be used and even modified by the computation. + W = tf.Variable(tf.zeros([784, 10])) + b = tf.Variable(tf.zeros([10])) # 0,1,2,34,5,6,7,8,9 + + # implement model + y = tf.nn.softmax(tf.matmul(x, W) + b) + + # implement cross-entropy + y_ = tf.placeholder(tf.float32, [None, 10]) + cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1])) + + # define training curriculum + train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy) + + # launch the model + sess = tf.InteractiveSession() + tf.global_variables_initializer().run() + + # train the model + 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}) + +if __name__ == '__main__': + main()