Tutorial by Examples

Here we will create collection for losses of Neural Network's computational graph. First create a computational graph like so: with tf.variable_scope("Layer"): W = tf.get_variable("weights", [m, k], initializer=tf.zeros_initializer([m, k], dtype=tf.float32)) ...

Below is a single hidden layer Multilayer Perceptron (MLP) using nested scoping of variables. def weight_variable(shape): return tf.get_variable(name="weights", shape=shape, initializer=tf.zeros_initializer(dtype=tf.float32)) def bias_variable(shape): ...