head.py 文件源码

def _centered_bias_step(logits_dimension, weight_collection, labels,
                        train_loss_fn):
  """Creates and returns training op for centered bias."""
  centered_bias = ops.get_collection(weight_collection)
  batch_size = array_ops.shape(labels)[0]
  logits = array_ops.reshape(
      array_ops.tile(centered_bias[0], [batch_size]),
      [batch_size, logits_dimension])
  with ops.name_scope(None, "centered_bias", (labels, logits)):
    centered_bias_loss = math_ops.reduce_mean(
        train_loss_fn(logits, labels), name="training_loss")
  # Learn central bias by an optimizer. 0.1 is a convervative lr for a
  # single variable.
  return training.AdagradOptimizer(0.1).minimize(
      centered_bias_loss, var_list=centered_bias)