(self, hr_images)
Args:[-0.5, 0.5]
      hr_images: [batch_size, hr_height, hr_width, in_channels]
    Returns:
      prior_logits: [batch_size, hr_height, hr_width, 3*256]
Args:[-0.5, 0.5]
      hr_images: [batch_size, hr_height, hr_width, in_channels]
    Returns:
      prior_logits: [batch_size, hr_height, hr_width, 3*256]
Args : [ - 0 . 5 0 . 5 ] hr_images : [ batch_size hr_height hr_width in_channels ] Returns : prior_logits : [ batch_size hr_height hr_width 3 * 256 ]
def prior_network(self, hr_images):
    """
    Args:[-0.5, 0.5]
      hr_images: [batch_size, hr_height, hr_width, in_channels]
    Returns:
      prior_logits: [batch_size, hr_height, hr_width, 3*256]
    """
    with tf.variable_scope('prior') as scope:
      conv1 = conv2d(hr_images, 64, [7, 7], strides=[1, 1], mask_type='A', scope="conv1")
      inputs = conv1
      state = conv1
      for i in range(20):
        inputs, state = gated_conv2d(inputs, state, [5, 5], scope='gated' + str(i))
      conv2 = conv2d(inputs, 1024, [1, 1], strides=[1, 1], mask_type='B', scope="conv2")
      conv2 = tf.nn.relu(conv2)
      prior_logits = conv2d(conv2, 3 * 256, [1, 1], strides=[1, 1], mask_type='B', scope="conv3")

      prior_logits = tf.concat([prior_logits[:, :, :, 0::3], prior_logits[:, :, :, 1::3], prior_logits[:, :, :, 2::3]], 3)

      return prior_logits
def prior_network ( self , hr_images ) : with tf . variable_scope ( 'prior' ) as scope : conv1 = conv2d ( hr_images , 64 , [ 7 , 7 ] , strides = [ 1 , 1 ] , mask_type = 'A' , scope = "conv1" ) inputs = conv1 state = conv1 for i in range ( 20 ) : inputs , state = gated_conv2d ( inputs , state , [ 5 , 5 ] , scope = 'gated' + str ( i ) ) conv2 = conv2d ( inputs , 1024 , [ 1 , 1 ] , strides = [ 1 , 1 ] , mask_type = 'B' , scope = "conv2" ) conv2 = tf . nn . relu ( conv2 ) prior_logits = conv2d ( conv2 , 3 * 256 , [ 1 , 1 ] , strides = [ 1 , 1 ] , mask_type = 'B' , scope = "conv3" ) prior_logits = tf . concat ( [ prior_logits [ : , : , : , 0 : : 3 ] , prior_logits [ : , : , : , 1 : : 3 ] , prior_logits [ : , : , : , 2 : : 3 ] ] , 3 ) return prior_logits