debug-branch

algorithms/neat/genome/numpy/activations.py

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+import numpy as np
+
+
+def sigmoid_act(z):
+    z = np.clip(z * 5, -60, 60)
+    return 1 / (1 + np.exp(-z))
+
+
+def tanh_act(z):
+    z = np.clip(z * 2.5, -60, 60)
+    return np.tanh(z)
+
+
+def sin_act(z):
+    z = np.clip(z * 5, -60, 60)
+    return np.sin(z)
+
+
+def gauss_act(z):
+    z = np.clip(z, -3.4, 3.4)
+    return np.exp(-5 * z ** 2)
+
+
+def relu_act(z):
+    return np.maximum(z, 0)
+
+
+def elu_act(z):
+    return np.where(z > 0, z, np.exp(z) - 1)
+
+
+def lelu_act(z):
+    leaky = 0.005
+    return np.where(z > 0, z, leaky * z)
+
+
+def selu_act(z):
+    lam = 1.0507009873554804934193349852946
+    alpha = 1.6732632423543772848170429916717
+    return np.where(z > 0, lam * z, lam * alpha * (np.exp(z) - 1))
+
+
+def softplus_act(z):
+    z = np.clip(z * 5, -60, 60)
+    return 0.2 * np.log(1 + np.exp(z))
+
+
+def identity_act(z):
+    return z
+
+
+def clamped_act(z):
+    return np.clip(z, -1, 1)
+
+
+def inv_act(z):
+    return 1 / z
+
+
+def log_act(z):
+    z = np.maximum(z, 1e-7)
+    return np.log(z)
+
+
+def exp_act(z):
+    z = np.clip(z, -60, 60)
+    return np.exp(z)
+
+
+def abs_act(z):
+    return np.abs(z)
+
+
+def hat_act(z):
+    return np.maximum(0, 1 - np.abs(z))
+
+
+def square_act(z):
+    return z ** 2
+
+
+def cube_act(z):
+    return z ** 3
+
+
+ACT_TOTAL_LIST = [sigmoid_act, tanh_act, sin_act, gauss_act, relu_act, elu_act, lelu_act, selu_act, softplus_act,
+                  identity_act, clamped_act, inv_act, log_act, exp_act, abs_act, hat_act, square_act, cube_act]
+
+act_name2key = {
+    'sigmoid': 0,
+    'tanh': 1,
+    'sin': 2,
+    'gauss': 3,
+    'relu': 4,
+    'elu': 5,
+    'lelu': 6,
+    'selu': 7,
+    'softplus': 8,
+    'identity': 9,
+    'clamped': 10,
+    'inv': 11,
+    'log': 12,
+    'exp': 13,
+    'abs': 14,
+    'hat': 15,
+    'square': 16,
+    'cube': 17,
+}
+
+
+def act(idx, z):
+    idx = np.asarray(idx, dtype=np.int32)
+    return ACT_TOTAL_LIST[idx](z)