# Copyright (c) 2018 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 unittest import numpy as np from .op_test import OpTest class TestFakeQuantizeOp(OpTest): def setUp(self): self.op_type = "fake_quantize" self.attrs = { 'bit_length': 8, 'quantize_type': 'abs_max', 'window_size': 10000 } self.inputs = { 'X': np.random.random((10, 10)).astype("float32"), 'InScales': np.zeros(self.attrs['window_size']).astype("float32"), 'InCurrentIter': np.zeros(1).astype("float32"), 'InMovingScale': np.zeros(1).astype("float32") } self.scale = { 'abs_max': np.max(np.abs(self.inputs['X'])).astype("float32") } self.outputs = { 'Out': np.round(self.inputs['X'] / self.scale['abs_max'] * ( (1 << (self.attrs['bit_length'] - 1)) - 1)), 'OutScales': np.zeros(self.attrs['window_size']).astype("float32"), 'OutMovingScale': np.array([self.scale['abs_max']]).astype("float32"), 'OutCurrentIter': np.zeros(1).astype("float32") } def test_check_output(self): self.check_output() if __name__ == "__main__": unittest.main()