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27 строки
885 B
Plaintext
27 строки
885 B
Plaintext
https://github.com/monsta-hd/boltzmann-machines
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from tensorflow.examples.tutorials.mnist import input_data
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mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
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28*28 = 784 pixels (55000 samples)
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mnist.train
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mnist.train.images
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mnist.train.labels
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[0, 0, 0, 1, 0, 0, 0, 0, 0, 0] - one-hot vector for number 3
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mnist.test
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mnist.validate
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import tensorflow as tf
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x = tf.placeholder(tf.float32, [None, 784]) # use arbitrary number of 784-dim vectors for learning
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W = tf.Variable(tf.zeros[784, 10]) # matrix for mult-n
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b = tf.Variable(tf.zeros[10]) # bias vector (to add)
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y = tf.nn.softmax(tf.matmul(x, W) + b)
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y_ = tf.placeholder(tf.float32, [None, 10]) # stub-function
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cross_entropy = tf.reduce_mean(
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-tf.reduce_sum(y_ * tf.log(y), reduction_idices=[1]))
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