循环神经网络

Tutorial/lesson-5/activators.py

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+# -*- coding: UTF-8 -*-
+
+
+import numpy as np
+
+
+class ReluActivator(object):
+    def forward(self, weighted_input):
+        #return weighted_input
+        return max(0, weighted_input)
+
+    def backward(self, output):
+        return 1 if output > 0 else 0
+
+
+class IdentityActivator(object):
+    def forward(self, weighted_input):
+        return weighted_input
+
+    def backward(self, output):
+        return 1
+
+
+class SigmoidActivator(object):
+    def forward(self, weighted_input):
+        return 1.0 / (1.0 + np.exp(-weighted_input))
+
+    def backward(self, output):
+        return output * (1 - output)
+
+
+class TanhActivator(object):
+    def forward(self, weighted_input):
+        return 2.0 / (1.0 + np.exp(-2 * weighted_input)) - 1.0
+
+    def backward(self, output):
+        return 1 - output * output