wehub-resource-sync
73 lines
2.1 KiB
Python
73 lines
2.1 KiB
Python
# copyright (c) 2022 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 annotations
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import unittest
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from typing import TYPE_CHECKING
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from paddle.nn import Linear
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from paddle.quantization.base_quanter import BaseQuanter
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from paddle.quantization.factory import quanter
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if TYPE_CHECKING:
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from collections.abc import Iterable
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import numpy as np
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import paddle
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linear_quant_axis = 1
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@quanter("CustomizedQuanter")
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class CustomizedQuanterLayer(BaseQuanter):
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def __init__(self, layer, bit_length=8, kwargs1=None):
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super().__init__()
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self._layer = layer
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self._bit_length = bit_length
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self._kwargs1 = kwargs1
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def scales(self) -> paddle.Tensor | np.ndarray:
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return None
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def bit_length(self):
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return self._bit_length
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def quant_axis(self) -> int | Iterable:
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return linear_quant_axis if isinstance(self._layer, Linear) else None
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def zero_points(self) -> paddle.Tensor | np.ndarray:
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return None
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def forward(self, input):
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return input
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class TestCustomizedQuanter(unittest.TestCase):
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def test_details(self):
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layer = Linear(5, 5)
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bit_length = 4
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quanter = CustomizedQuanter( # noqa: F821
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bit_length=bit_length, kwargs1="test"
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)
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quanter = quanter._instance(layer)
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self.assertEqual(quanter.bit_length(), bit_length)
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self.assertEqual(quanter.quant_axis(), linear_quant_axis)
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self.assertEqual(quanter._kwargs1, 'test')
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if __name__ == '__main__':
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unittest.main()
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