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AutoEncoder: Training one Autoencoder at a time in multiple graphs
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| # image input | |
| n_inputs = 28*28 | |
| # merged to one stacked AE | |
| X = tf.placeholder(tf.float32, shape=[None, n_inputs]) | |
| hidden1 = tf.nn.elu(tf.matmul(X, W1) + b1) | |
| hidden2 = tf.nn.elu(tf.matmul(hidden1, W2) + b2) | |
| hidden3 = tf.nn.elu(tf.matmul(hidden2, W3) + b3) | |
| outputs = tf.matmul(hidden3, W4) + b4 |
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