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
  
  import fastestimator as fe
  from fastestimator.test.unittest_util import is_equal
  
  
  class TestGather(unittest.TestCase):
      def test_np_input_3x2(self):
          ind = np.array([1, 0, 1])
          n = np.array([[0, 1], [2, 3], [4, 5]])
          b = fe.backend.gather(n, ind)
          self.assertTrue(is_equal(b, np.array([[2, 3], [0, 1], [2, 3]])))
  
      def test_np_input_3x2x2(self):
          ind = np.array([[1], [0], [1]])
          n = np.array([[[0, 1], [2, 3]], [[4, 5], [6, 7]], [[8, 9], [10, 11]]])
          b = fe.backend.gather(n, ind)
          self.assertTrue(is_equal(b, np.array([[[4, 5], [6, 7]], [[0, 1], [2, 3]], [[4, 5], [6, 7]]])))
  
      def test_tf_input_3x2(self):
          ind = tf.constant([1, 0, 1])
          n = tf.constant([[0, 1], [2, 3], [4, 5]])
          b = fe.backend.gather(n, ind)
          self.assertTrue(is_equal(b, tf.constant([[2, 3], [0, 1], [2, 3]])))
  
      def test_tf_input_3x2x2(self):
          ind = tf.constant([[1], [0], [1]])
          n = tf.constant([[[0, 1], [2, 3]], [[4, 5], [6, 7]], [[8, 9], [10, 11]]])
          b = fe.backend.gather(n, ind)
          self.assertTrue(is_equal(b, tf.constant([[[4, 5], [6, 7]], [[0, 1], [2, 3]], [[4, 5], [6, 7]]])))
  
      def test_torch_input_3x2(self):
          ind = torch.tensor([1, 0, 1])
          n = torch.tensor([[0, 1], [2, 3], [4, 5]])
          b = fe.backend.gather(n, ind)
          self.assertTrue(is_equal(b, torch.tensor([[2, 3], [0, 1], [2, 3]])))
  
      def test_torch_input_3x2x2(self):
          ind = torch.tensor([[1], [0], [1]])
          n = torch.tensor([[[0, 1], [2, 3]], [[4, 5], [6, 7]], [[8, 9], [10, 11]]])
          b = fe.backend.gather(n, ind)
          self.assertTrue(is_equal(b, torch.tensor([[[4, 5], [6, 7]], [[0, 1], [2, 3]], [[4, 5], [6, 7]]])))
  