text: #  Copyright (c) 2022 PaddlePaddle 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.
  
  from __future__ import print_function
  
  import numpy as np
  import unittest
  import sys
  
  sys.path.append("..")
  from op_test import OpTest
  import paddle
  import paddle.fluid as fluid
  
  paddle.enable_static()
  SEED = 2022
  
  
  class TestLookupTableV2(OpTest):
  
      def setUp(self):
          self.set_mlu()
          self.op_type = "lookup_table_v2"
  
          self.init_dtype()
          self.init_dims()
          self.init_padding_idx()
          np.random.seed(SEED)
          w = np.random.random([self.vocab, self.dim]).astype(self.dtype)
          x = np.random.randint(0, self.vocab,
                                size=(self.bsz,
                                      self.seqlen)).astype(self.ids_dtype)
          out = w[x]
          if self.padding_idx != -1:
              out[np.squeeze(x == self.padding_idx)] = np.zeros(self.dim)
  
          self.inputs = {
              'W': OpTest.np_dtype_to_fluid_dtype(w),
              'Ids': OpTest.np_dtype_to_fluid_dtype(x)
          }
          self.attrs = {
              'is_sparse': False,
              'is_distributed': False,
              'remote_prefetch': False,
              'padding_idx': self.padding_idx
          }
          self.outputs = {'Out': out}
  
      def set_mlu(self):
          self.__class__.use_mlu = True
          self.place = paddle.device.MLUPlace(0)
  
      def init_dtype(self):
          self.dtype = np.float32
          self.ids_dtype = np.int32
  
      def init_dims(self):
          self.bsz = 6
          self.seqlen = 8
          self.vocab = 10
          # embedding_dim is not multiple of 32
          self.dim = 20
  
      def init_padding_idx(self):
          self.padding_idx = -1
  
      def test_check_output(self):
          self.check_output_with_place(self.place)
  
      def test_check_grad(self):
          if self.dtype == np.float16:
              self.check_grad_with_place(self.place, ['W'],
                                         'Out',
                                         max_relative_error=0.01)
          else:
              self.check_grad_with_place(self.place, ['W'], 'Out')
  
  
  class TestLookupTableV2FP16(TestLookupTableV2):
      no_need_check_grad = True
  
      def init_dtype(self):
          self.dtype = np.float16
          self.ids_dtype = np.int32
  
      def set_mlu(self):
          self.__class__.use_mlu = True
          self.place = paddle.device.MLUPlace(0)
  
  
  class TestLookupTableV2Dim32(TestLookupTableV2):
  
      def init_dims(self):
          self.bsz = 6
          self.seqlen = 8
          self.vocab = 10
          # embedding_dim is multiple of 32
          self.dim = 64
  
  
  class TestLookupTableV2Dim32FP16(TestLookupTableV2):
      no_need_check_grad = True
  
      def init_dtype(self):
          self.dtype = np.float16
          self.ids_dtype = np.int64
  
      def init_dims(self):
          self.bsz = 6
          self.seqlen = 8
          self.vocab = 10
          self.dim = 64
  
      def set_mlu(self):
          self.__class__.use_mlu = True
          self.place = paddle.device.MLUPlace(0)
  
  
  class TestLookupTableV2WithPadding(TestLookupTableV2):
  
      def init_padding_idx(self):
          self.padding_idx = np.random.randint(0, self.vocab)
  
  
  class TestLookupTableV2WithPadding1(TestLookupTableV2):
  
      def init_padding_idx(self):
          self.padding_idx = np.random.randint(0, self.vocab)
  
      def init_dtype(self):
          self.dtype = np.float32
          self.ids_dtype = np.int64
  
  
  if __name__ == '__main__':
      unittest.main()
  