I have built my network and would like to see how the activation of a particular layer change after each epoch of training. For example, as code shown below, I want to see the activation values of "act_layer_1". What should I do so that I can see the activation values? Thanks in advance!
W1 = tf.get_variable('W1', [n_input,n_hidden_1], initializer = tf.contrib.layers.xavier_initializer(seed = 1)) b1 = tf.Variable(tf.constant(0.0, shape=[n_hidden_1], dtype=tf.float32), trainable=True, name='b1'), act_layer_1 = tf.nn.relu(hidden_layer(x_image, W1) + b1) drop_layer_1 = tf.nn.dropout(act_layer_1, keep_prob)