Initial commit

net/activation.py

@@ -0,0 +1,59 @@
+import numpy as np
+
+class Activations:
+    @staticmethod
+    def LeakyReLU(x, alpha=0.01):
+        return np.where(x > 0, x, alpha * x)
+
+    @staticmethod
+    def LeakyReLU_deriv(x, alpha=0.01):
+        return np.where(x > 0, 1, alpha)
+
+    @staticmethod
+    def InverseLeakyReLU(x, alpha=0.01):
+        return np.where(x > 0, x, x / alpha)
+
+    @staticmethod
+    def ReLU(x):
+        return np.maximum(0, x)
+
+    @staticmethod
+    def ReLU_deriv(x):
+        return np.where(x > 0, 1, 0)
+
+    @staticmethod
+    def InverseReLU(x):
+        return np.maximum(0, x)  # Note: This is lossy for negative values
+
+    @staticmethod
+    def Sigmoid(x):
+        return 1 / (1 + np.exp(-x))
+
+    @staticmethod
+    def Sigmoid_deriv(x):
+        s = Activations.Sigmoid(x)
+        return s * (1 - s)
+
+    @staticmethod
+    def InverseSigmoid(x):
+        return np.log(x / (1 - x))
+
+    @staticmethod
+    def Softmax(x):
+        exp_x = np.exp(x - np.max(x, axis=0, keepdims=True))
+        return exp_x / np.sum(exp_x, axis=0, keepdims=True)
+
+    @staticmethod
+    def InverseSoftmax(x):
+        return np.log(x) - np.max(np.log(x))
+    
+    @classmethod
+    def get_function_name(cls, func):
+        return func.__name__
+
+    @classmethod
+    def get_all_activation_names(cls):
+        return [name for name, func in cls.__dict__.items() 
+                if callable(func) and not name.startswith("__") and 
+                not name.endswith("_deriv") and not name.startswith("Inverse") and 
+                not name in ['get_function_name', 'get_all_activation_names']]