23 lines
513 B
Python
23 lines
513 B
Python
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class activationFunction:
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def applyTo(value):
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pass
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def applyDerivateTo(value):
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pass
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class sigmoid(activationFunction):
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def applyTo(value):
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return 1.0/(1.0+np.exp(-value))
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def applyDerivateTo(value):
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return sigmoid.applyTo(value) * (1 - sigmoid.applyTo(value))
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class reLu(activationFunction):
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def applyTo(value):
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return max(0, value)
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def applyDerivateTo(value):
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return 0 if (value < 0) else 1
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class softMax(activationFunction):
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pass
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