Error for running with TensorFlow: ValueError: Variable d_w1/Adam/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope? about generative_adversarial_networks_live HOT 6 OPEN

sess = tf.Session() 
batch_size = 50 
z_dimensions = 100 
x_placeholder = tf.placeholder("float", shape = [None,28,28,1], name='x_placeholder') 
Gz = generator(batch_size, z_dimensions) 
Dx = discriminator(x_placeholder) 
with tf.variable_scope(tf.get_variable_scope()) as scope:
    pass 
Dg = discriminator(Gz, reuse=True)
g_loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits=Dg, labels=tf.ones_like(Dg))) 
d_loss_real = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits=Dx, labels=tf.fill([batch_size, 1], 0.9))) 
d_loss_fake = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits=Dg, labels=tf.zeros_like(Dg))) 
d_loss = d_loss_real + d_loss_fake 
tvars = tf.trainable_variables() 
d_vars = [var for var in tvars if  'd_' in var.name] 
g_vars = [var for var in tvars if not 'g_' in var.name] 

with tf.variable_scope(scope):    
    d_trainer_fake = tf.train.AdamOptimizer(0.0001).minimize(d_loss_fake, var_list=d_vars) 
    d_trainer_real = tf.train.AdamOptimizer(0.0001).minimize(d_loss_real, var_list=d_vars) 
    g_trainer = tf.train.AdamOptimizer(0.0001).minimize(g_loss, var_list=g_vars)
    

            plt.imshow(im.reshape([28, 28]), cmap='Greys')
            plt.show(block=False)
            plt.pause(2)
            plt.close()