ops.py 文件源码

def dropout(inputs, keep_prob=0.5, is_training=True, scope=None):
  """Returns a dropout layer applied to the input.

  Args:
    inputs: the tensor to pass to the Dropout layer.
    keep_prob: the probability of keeping each input unit.
    is_training: whether or not the model is in training mode. If so, dropout is
    applied and values scaled. Otherwise, inputs is returned.
    scope: Optional scope for op_scope.

  Returns:
    a tensor representing the output of the operation.
  """
  if is_training and keep_prob > 0:
    with tf.op_scope([inputs], scope, 'Dropout'):
      return tf.nn.dropout(inputs, keep_prob)
  else:
    return inputs