forked from TensorLayer/tensorlayer3
123 lines
3.1 KiB
Python
123 lines
3.1 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import os
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import unittest
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os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
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import tensorflow as tf
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import tensorlayer as tl
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from tests.utils import CustomTestCase
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class Test_Leaky_ReLUs(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.alpha = 0.2
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cls.vmin = 0
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cls.vmax = 10
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@classmethod
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def tearDownClass(cls):
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pass
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def test_lrelu(self):
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for i in range(-5, 15):
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if i > 0:
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good_output = i
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else:
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good_output = self.alpha * i
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computed_output = tl.act.leaky_relu(float(i), alpha=self.alpha)
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self.assertAlmostEqual(computed_output.numpy(), good_output, places=5)
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net = tl.layers.Input([10, 2])
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net = tl.layers.Dense(n_units=100, act=lambda x: tl.act.lrelu(x, 0.2), name='dense')(net)
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print(net)
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def test_lrelu6(self):
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for i in range(-5, 15):
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if i < 0:
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good_output = self.alpha * i
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else:
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good_output = min(6, i)
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computed_output = tl.act.leaky_relu6(float(i), alpha=self.alpha)
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self.assertAlmostEqual(computed_output.numpy(), good_output, places=5)
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net = tl.layers.Input([10, 2])
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net = tl.layers.Dense(n_units=100, act=lambda x: tl.act.leaky_relu6(x, 0.2), name='dense')(net)
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print(net)
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def test_ltrelu6(self):
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for i in range(-5, 15):
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if i < 0:
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good_output = self.alpha * i
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elif i < 6:
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good_output = i
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else:
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good_output = 6 + (self.alpha * (i - 6))
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computed_output = tl.act.leaky_twice_relu6(float(i), alpha_low=self.alpha, alpha_high=self.alpha)
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self.assertAlmostEqual(computed_output.numpy(), good_output, places=5)
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net = tl.layers.Input([10, 200])
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net = tl.layers.Dense(n_units=100, act=lambda x: tl.act.leaky_twice_relu6(x, 0.2, 0.2), name='dense')(net)
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print(net)
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def test_ramp(self):
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for i in range(-5, 15):
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if i < self.vmin:
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good_output = self.vmin
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elif i > self.vmax:
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good_output = self.vmax
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else:
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good_output = i
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computed_output = tl.act.ramp(float(i), v_min=self.vmin, v_max=self.vmax)
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self.assertAlmostEqual(computed_output.numpy(), good_output, places=5)
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def test_sign(self):
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for i in range(-5, 15):
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if i < 0:
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good_output = -1
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elif i == 0:
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good_output = 0
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else:
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good_output = 1
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computed_output = tl.act.sign(float(i))
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self.assertAlmostEqual(computed_output.numpy(), good_output, places=5)
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def test_swish(self):
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import numpy as np
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for i in range(-5, 15):
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good_output = i / (1 + np.math.exp(-i))
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computed_output = tl.act.swish(float(i))
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self.assertAlmostEqual(computed_output.numpy(), good_output, places=5)
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if __name__ == '__main__':
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unittest.main()
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