import paddle.fluid as fluid import paddleslim.quant as quant import unittest class TestQuantEmbedding(unittest.TestCase): def test_quant_embedding(self): train_program = fluid.Program() with fluid.program_guard(train_program): input_word = fluid.data( name="input_word", shape=[None, 1], dtype='int64') input_emb = fluid.embedding( input=input_word, is_sparse=False, size=[100, 128], param_attr=fluid.ParamAttr( name='emb', initializer=fluid.initializer.Uniform(-0.005, 0.005))) infer_program = train_program.clone(for_test=True) use_gpu = True place = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace() exe = fluid.Executor(place) exe.run(fluid.default_startup_program()) config = {'params_name': 'emb', 'quantize_type': 'abs_max'} quant_program = quant.quant_embedding(infer_program, place, config) if __name__ == '__main__': unittest.main()