text: # Copyright (c) 2019  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.
  import sys
  import paddle
  sys.path.append("../")
  import paddleslim.quant as quant
  import unittest
  
  from static_case import StaticCase
  
  
  class TestQuantEmbedding(StaticCase):
      def test_quant_embedding(self):
          train_program = paddle.static.Program()
          with paddle.static.program_guard(train_program):
              input_word = paddle.static.data(
                  name="input_word", shape=[None, 1], dtype='int64')
              param_attr = paddle.ParamAttr(
                  name='emb',
                  initializer=paddle.nn.initializer.Uniform(-0.005, 0.005))
              weight = train_program.global_block().create_parameter(
                  (100, 128), attr=param_attr, dtype="float32")
  
              input_emb = paddle.nn.functional.embedding(
                  x=input_word, weight=weight, sparse=True)
  
          infer_program = train_program.clone(for_test=True)
  
          use_gpu = True
          place = paddle.CUDAPlace(0) if use_gpu else paddle.CPUPlace()
          exe = paddle.static.Executor(place)
          exe.run(paddle.static.default_startup_program())
  
          quant_program = quant.quant_embedding(infer_program, place)
  
  
  if __name__ == '__main__':
      unittest.main()
  