wehub-resource-sync
87 lines
2.8 KiB
Python
87 lines
2.8 KiB
Python
# Copyright (c) 2020 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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import unittest
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import numpy as np
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import paddle
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class TestFunctionalLayers(unittest.TestCase):
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""" """
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def setUp(self):
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paddle.disable_static()
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np.random.seed(1)
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shape = [3, 100, 120]
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self.x = paddle.to_tensor(np.random.random(shape))
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self.y = paddle.to_tensor(np.random.random(shape))
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def check(self, x, y):
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np.testing.assert_allclose(x.numpy(), y.numpy(), rtol=1e-05)
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def test_quant_add(self):
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out_1 = paddle.add(self.x, self.y)
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out_2 = paddle.nn.quant.add()(self.x, self.y)
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self.check(out_1, out_2)
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def test_quant_subtract(self):
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out_1 = paddle.subtract(self.x, self.y)
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out_2 = paddle.nn.quant.subtract()(self.x, self.y)
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self.check(out_1, out_2)
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def test_quant_multiply(self):
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out_1 = paddle.multiply(self.x, self.y)
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out_2 = paddle.nn.quant.multiply()(self.x, self.y)
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self.check(out_1, out_2)
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def test_quant_divide(self):
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out_1 = paddle.divide(self.x, self.y)
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out_2 = paddle.nn.quant.divide()(self.x, self.y)
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self.check(out_1, out_2)
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def test_quant_reshape(self):
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reshape = [120, 300]
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out_1 = paddle.reshape(self.x, reshape)
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out_2 = paddle.nn.quant.reshape()(self.x.clone(), reshape)
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self.check(out_1, out_2)
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self.assertTrue(out_1.shape == out_2.shape)
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def test_quant_transpose(self):
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perm = [1, 2, 0]
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out_1 = paddle.transpose(self.x, perm)
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out_2 = paddle.nn.quant.transpose()(self.x.clone(), perm)
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self.check(out_1, out_2)
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self.assertTrue(out_1.shape == out_2.shape)
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def test_quant_concat(self):
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out_1 = paddle.concat([self.x, self.y], axis=0)
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out_2 = paddle.nn.quant.concat()([self.x, self.y], 0)
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self.check(out_1, out_2)
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self.assertTrue(out_1.shape == out_2.shape)
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def test_quant_flatten(self):
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start_axis = 1
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end_axis = 2
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out_1 = paddle.flatten(self.x, start_axis, end_axis)
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out_2 = paddle.nn.quant.flatten()(self.x.clone(), start_axis, end_axis)
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self.check(out_1, out_2)
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self.assertTrue(out_1.shape == out_2.shape)
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if __name__ == '__main__':
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unittest.main()
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