TensorFlow: simple example

simple-nn-tf.py

import numpy as np
import tensorflow as tf

data_size = 10

input_size = 28 * 28
hidden1_output = 200
output_size = 1

data = tf.placeholder(tf.float32, shape=(data_size, input_size))
target = tf.placeholder(tf.float32, shape=(data_size, output_size))

h1_w1 = tf.Variable(tf.random_uniform((input_size, hidden1_output)))
h2_w1 = tf.Variable(tf.random_uniform((hidden1_output, output_size)))

hidden1_out = tf.maximum(tf.matmul(data, h1_w1), 0)
target_ = tf.matmul(hidden1_out, h2_w1)
loss = tf.losses.mean_squared_error(target_, target)

opt = tf.train.GradientDescentOptimizer(1e-3)
upd = opt.minimize(loss)

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())

    feed = {data: np.random.randn(data_size, input_size), target: np.random.randn(data_size, output_size)}

    for step in range(100):
        loss_val, _ = sess.run([loss, upd], feed_dict=feed)