1da5440d8444f99f79b597356e9342ffab0eaf5f,models/official/detection/modeling/architecture/heads.py,RpnHead,__init__,#RpnHead#Any#Any#Any#Any#Any#Any#Any#Any#,35

Before Change

          depth_multiplier=1,
          bias_initializer=tf.zeros_initializer())
    else:
      self._conv2d_op = functools.partial(
          tf.layers.conv2d,
          kernel_initializer=tf.random_normal_initializer(stddev=0.01),
          bias_initializer=tf.zeros_initializer())

    self._use_batch_norm = use_batch_norm
    self._batch_norm_activation = batch_norm_activation

After Change

    self._upsample_num_filters = upsample_num_filters
    if activation == "relu":
      self._activation = tf.nn.relu
    elif activation == "swish":
      self._activation = tf.nn.swish
    else:
      raise ValueError("Activation {} not implemented.".format(activation))
    self._use_batch_norm = use_batch_norm
    self._batch_norm_activation = batch_norm_activation

  def __call__(self, features, is_training):

Instances