## Nodes for encoding layer

n_nodes_inpl = 3706

n_nodes_hl1 = 1853

n_nodes_hl2 = 925

## Nodes for hiddern layer

n_nodes_hl3 = 252

## Nodes for decoding layer

n_nodes_hl4 = 925

n_nodes_hl5 = 1853

n_nodes_outl = 3706

## input layer has 9724*4862 weights and 4862 biases

hidden_1_layer_vals = {'weights':tf.Variable(tf.random_normal([n_nodes_inpl,n_nodes_hl1]))}

## second encode layer has 4862*2431 weights and 2431 biases

hidden_2_layer_vals = {'weights':tf.Variable(tf.random_normal([n_nodes_hl1,n_nodes_hl2]))}

## Third encode layer has 2431*512 weights and 512 biases

hidden_3_layer_vals = {'weights':tf.Variable(tf.random_normal([n_nodes_hl2,n_nodes_hl3]))}

## First decode layer has 512*2431 weights and 2431 biases

hidden_4_layer_vals = {'weights':tf.Variable(tf.random_normal([n_nodes_hl3,n_nodes_hl4]))}