def sigmoid(self, x):
try:
#r = 1 /(1+np.exp(-x))
r = 1 /(1+tools.safe_exp(-x))
return r
except Exception as e:
print e
print "exception when calculating sigmoid"
def sigmoid(self, x):
try:
#r = 1 /(1+np.exp(-x))
r = 1 / (1 + tools.safe_exp(-x))
return r
except Exception as e:
print e
print "exception when calculating sigmoid"
def softmax(self, x):
# rows of x are expected to be vectors where softmax is to be applied
r = np.copy(x)
for index, col in enumerate(x):
#m = np.max(col)
#r[index] = np.exp(col - m)
#r[index] = tools.safe_exp(col - m)
r[index] = tools.safe_exp(col)
r[index] = r[index] / np.sum(r[index])
return r
def softmax(self, x):
# rows of x are expected to be vectors where softmax is to be applied
r = np.copy(x)
for index, col in enumerate(x):
#m = np.max(col)
#r[index] = np.exp(col - m)
#r[index] = tools.safe_exp(col - m)
r[index] = tools.safe_exp(col)
r[index] = r[index] / np.sum(r[index])
return r
