(net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=None)
return net
Builds the 17x17 resnet block.
Builds the 17x17 resnet block.
Builds the 17x17 resnet block .
def block17(net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=None):
  """Builds the 17x17 resnet block."""
  with tf.variable_scope(scope, 'Block17', [net], reuse=reuse):
    with tf.variable_scope('Branch_0'):
      tower_conv = slim.conv2d(net, 192, 1, scope='Conv2d_1x1')
    with tf.variable_scope('Branch_1'):
      tower_conv1_0 = slim.conv2d(net, 128, 1, scope='Conv2d_0a_1x1')
      tower_conv1_1 = slim.conv2d(tower_conv1_0, 160, [1, 7],
                                  scope='Conv2d_0b_1x7')
      tower_conv1_2 = slim.conv2d(tower_conv1_1, 192, [7, 1],
                                  scope='Conv2d_0c_7x1')
    mixed = tf.concat(axis=3, values=[tower_conv, tower_conv1_2])
    up = slim.conv2d(mixed, net.get_shape()[3], 1, normalizer_fn=None,
                     activation_fn=None, scope='Conv2d_1x1')
    net += scale * up
    if activation_fn:
      net = activation_fn(net)
  return net
def block17 ( net , scale = 1.0 , activation_fn = tf . nn . relu , scope = None , reuse = None ) : with tf . variable_scope ( scope , 'Block17' , [ net ] , reuse = reuse ) : with tf . variable_scope ( 'Branch_0' ) : tower_conv = slim . conv2d ( net , 192 , 1 , scope = 'Conv2d_1x1' ) with tf . variable_scope ( 'Branch_1' ) : tower_conv1_0 = slim . conv2d ( net , 128 , 1 , scope = 'Conv2d_0a_1x1' ) tower_conv1_1 = slim . conv2d ( tower_conv1_0 , 160 , [ 1 , 7 ] , scope = 'Conv2d_0b_1x7' ) tower_conv1_2 = slim . conv2d ( tower_conv1_1 , 192 , [ 7 , 1 ] , scope = 'Conv2d_0c_7x1' ) mixed = tf . concat ( axis = 3 , values = [ tower_conv , tower_conv1_2 ] ) up = slim . conv2d ( mixed , net . get_shape ( ) [ 3 ] , 1 , normalizer_fn = None , activation_fn = None , scope = 'Conv2d_1x1' ) net += scale * up if activation_fn : net = activation_fn ( net ) return net