Files
tensorneat-mend/algorithms/neat/genome/numpy/activations.py
2023-05-06 21:04:28 +08:00

114 lines
1.8 KiB
Python

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)