54 lines
1.8 KiB
54 lines
1.8 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest
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class TestFakeQuantizeOp(OpTest):
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def setUp(self):
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self.op_type = "fake_quantize"
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self.attrs = {
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'bit_length': 8,
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'quantize_type': 'abs_max',
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'window_size': 10000
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}
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self.inputs = {
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'X': np.random.random((10, 10)).astype("float32"),
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'InScales': np.zeros(self.attrs['window_size']).astype("float32"),
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'InCurrentIter': np.zeros(1).astype("float32"),
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'InMovingScale': np.zeros(1).astype("float32")
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}
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self.scale = {
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'abs_max': np.max(np.abs(self.inputs['X'])).astype("float32")
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}
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self.outputs = {
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'Out': np.round(self.inputs['X'] / self.scale['abs_max'] * (
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(1 << (self.attrs['bit_length'] - 1)) - 1)),
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'OutScales': np.zeros(self.attrs['window_size']).astype("float32"),
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'OutMovingScale':
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np.array([self.scale['abs_max']]).astype("float32"),
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'OutCurrentIter': np.zeros(1).astype("float32")
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}
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def test_check_output(self):
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self.check_output()
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if __name__ == "__main__":
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unittest.main()
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