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67 lines
2.2 KiB
67 lines
2.2 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_abs_max"
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self.attrs = {'bit_length': 8}
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self.inputs = {'X': np.random.random((124, 240)).astype("float32"), }
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scale = np.max(np.abs(self.inputs['X'])).astype("float32")
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self.outputs = {
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'Out': np.round(self.inputs['X'] / scale * (
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(1 << (self.attrs['bit_length'] - 1)) - 1)),
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'OutScale': np.array(scale).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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class TestFakeQuantizeOp(OpTest):
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def setUp(self):
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self.op_type = "fake_quantize_range_abs_max"
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self.attrs = {
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'bit_length': int(5),
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'window_size': int(1),
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'is_test': False
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}
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self.inputs = {
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'X': np.random.random((8, 16, 7, 7)).astype("float32"),
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'Iter': np.zeros(1).astype("int64"),
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'InScale': np.zeros(1).astype("float32")
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}
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scale = np.max(np.abs(self.inputs['X'])).astype("float32")
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out_scales = np.zeros(self.attrs['window_size']).astype("float32")
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out_scales[0] = scale
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self.outputs = {
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'Out': np.round(self.inputs['X'] / scale * (
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(1 << (self.attrs['bit_length'] - 1)) - 1)),
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'OutScale': scale,
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'OutScales': out_scales,
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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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