(self, hr_images, lr_images, scope)
Args:[0, 255]
      hr_images: [batch_size, hr_height, hr_width, in_channels] float32
      lr_images: [batch_size, lr_height, lr_width, in_channels] float32
Args:[0, 255]
      hr_images: [batch_size, hr_height, hr_width, in_channels] float32
      lr_images: [batch_size, lr_height, lr_width, in_channels] float32
Args : [ 0 255 ] hr_images : [ batch_size hr_height hr_width in_channels ] float32 lr_images : [ batch_size lr_height lr_width in_channels ] float32
def __init__(self, hr_images, lr_images, scope):
    """
    Args:[0, 255]
      hr_images: [batch_size, hr_height, hr_width, in_channels] float32
      lr_images: [batch_size, lr_height, lr_width, in_channels] float32
    """
    with tf.variable_scope(scope) as scope:
      self.train = tf.placeholder(tf.bool)
      self.construct_net(hr_images, lr_images)
def __init__ ( self , hr_images , lr_images , scope ) : with tf . variable_scope ( scope ) as scope : self . train = tf . placeholder ( tf . bool ) self . construct_net ( hr_images , lr_images )