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test_quant_embedding.py
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test_quant_embedding.py
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# 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 set_config(self):
self.config = {
'quantize_op_types': ['lookup_table_v2'],
'lookup_table': {
'quantize_type': 'abs_max',
'quantize_bits': 8,
'dtype': 'int8'
}
}
def test_quant_embedding(self):
self.set_config()
train_program = paddle.static.Program()
startup_program = paddle.static.Program()
with paddle.static.program_guard(train_program, startup_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 = paddle.static.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)
place = paddle.CPUPlace()
exe = paddle.static.Executor(place)
exe.run(startup_program)
quant_program = quant.quant_embedding(infer_program, place)
class TestQuantEmbeddingInt16(TestQuantEmbedding):
def set_config(self):
self.config = {
'quantize_op_types': ['lookup_table'],
'lookup_table': {
'quantize_type': 'abs_max',
'quantize_bits': 16,
'dtype': 'int16'
}
}
if __name__ == '__main__':
unittest.main()