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
  
  from fastestimator.op.numpyop.univariate import PadSequence
  from fastestimator.test.unittest_util import is_equal
  
  
  class TestPadSequence(unittest.TestCase):
      @classmethod
      def setUpClass(cls):
          cls.single_input = [np.array([1, 2, 3, 4])]
          cls.single_output = [np.array([1, 2, 3, 4, 0, 0, 0])]
          cls.multi_input = [np.array([2, 2]), np.array([0, 1, 2])]
          cls.multi_output = [np.array([2, 2, -1, -1]), np.array([0, 1, 2, -1])]
  
      def test_single_input(self):
          op = PadSequence(inputs='x', outputs='x', max_len=7, value=0)
          data = op.forward(data=self.single_input, state={})
          self.assertTrue(is_equal(data, self.single_output))
  
      def test_multi_input(self):
          op = PadSequence(inputs='x', outputs='x', max_len=4, value=-1)
          data = op.forward(data=self.multi_input, state={})
          self.assertTrue(is_equal(data, self.multi_output))
  
      def test_sequence_truncate(self):
          op = PadSequence(inputs='x', outputs='x', max_len=3)
          data = op.forward(data=self.single_input, state={})
          self.assertTrue(is_equal(data, [np.array([1, 2, 3])]))
  
      def test_sequene_prepent(self):
          op = PadSequence(inputs='x', outputs='x', max_len=7, value=0, append=False)
          data = op.forward(data=self.single_input, state={})
          self.assertTrue(is_equal(data, [np.array([0, 0, 0, 1, 2, 3, 4])]))
  