autoencoder - Feeding a hidden tensor in Tensorflow -

i have autoencoder. model not important now. suppose model takes input image , output reconstructed image. after training, see effect of 1 tensor on output. in addition, images being fed autoencoder through fifoqueue. therefore, when running following peace of code:

reconstructed_image = sess.run([deconv_image], feed_dict={mu:my_vector}) 

where deconv_image output tensor of model , mu hidden tensor inside model; automatically feed model image queue.

my question is: value inside mu replaced whatever should come input image, or, takes vector fed using feed_dict argument.

any appreciated!!

when running final tensor, is, evaluating last tensor of graph, run tensors depends on. if have y3 operation depends on y2 , y2 depends on y1, then, running final tensor in graph cause y1 run first, y2 evaluated after gets input y1 , finally, output of y2 feed y3. graph follows: y1 -> y2 -> y3

on other hand, can run (evaluate) y3 feeding inputs directly using feed_dict argument. in case, y2 , y1 evaluated.

ex:

import tensorflow tf import numpy np  x = np.array([1.0, 2.0, 3.0])  x_var = tf.variable(x, dtype=tf.float32)  y1 = tf.square(x_var) y2 = tf.subtract(y1, tf.constant(1.0))  init_op = tf.global_variables_initializer()  tf.session() sess:     sess.run(init_op)      print(sess.run(y2)) # output: [ 0.  3.  8.]     print(sess.run(y2, feed_dict={y1: [1.0, 1.0, 1.0]}))# output: [ 0.  0.  0.]