correcting errors

class Hingeloss():

  def __init__(self,in_layers=None,weights,batch_size,labels,reg,**kwargs):

  def __init__(self, in_layers=None, weights, batch_size, labels, reg,

               **kwargs):

    self.weights = weights

    self.batch_size = batch_size

    self.reg = reg

    super(Hingeloss, self).__init__(in_layers, **kwargs)

  def create_tensor(self, in_layers=None, set_tensors=True, **kwargs):

    inputs = self.get_input_tensors(in_layers)

    weights,batch_size,labels,reg=inputs[0],inputs[1],inputs[2],inputs[3]

    weights, batch_size, labels, reg = inputs[0], inputs[1], inputs[2], inputs[

        3]

    scores = tf.matmul(batch_size, weights)

    labels_i = scores[np.arange(scores.shape[0]), labels]

    loss_i = tf.maximum(0, scores - tf.transpose(labels_i) + 1)

      out_tensor = Hingeloss()(input_tensor)

      out_tensor = out_tensor.eval()

      assert out_tensor.shape == (batch_size,)