volleyball_train_stage_a.py 文件源码

def attention_weights(features, tau=10.0, num_hidden=512):
  """computing attention weights
  Args:
    features: [B,N,F]
  Returns:
    [B,N] tensor with soft attention weights for each sample
  """
  B, N, F = features.get_shape().as_list()

  with tf.variable_scope('attention'):
    x = tf.reshape(features, [-1, F])
    x = slim.fully_connected(x, num_hidden, scope='fc0')
    x = slim.fully_connected(x, 1, activation_fn=None, scope='fc1')
    x = tf.reshape(x, features.get_shape()[:2])
    alpha = tf.reshape(slim.softmax(x / tau), [B,N,])
  return alpha