text: # Copyright 2020 The FastEstimator Authors. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  # ==============================================================================
  import unittest
  
  import numpy as np
  import tensorflow as tf
  import torch
  
  from fastestimator.op.tensorop.average import Average
  from fastestimator.test.unittest_util import is_equal
  
  
  class TestAverage(unittest.TestCase):
      @classmethod
      def setUpClass(cls):
          cls.tf_data = [tf.constant([1., 2., 4.]), tf.constant([1., 4., 5.])]
          cls.tf_output = tf.constant([1., 3., 4.5])
          cls.torch_data = [torch.tensor([1., 2., 4.]), torch.tensor([1., 4., 5.])]
          cls.torch_output = torch.tensor([1., 3., 4.5])
  
      def test_tf_input(self):
          average = Average(inputs='x', outputs='x')
          output = average.forward(data=self.tf_data, state={})
          self.assertTrue(is_equal(output, self.tf_output))
  
      def test_torch_input(self):
          average = Average(inputs='x', outputs='x')
          output = average.forward(data=self.torch_data, state={})
          self.assertTrue(is_equal(output, self.torch_output))
  