Here is the python:

def softmax(self): result = copy.deepcopy(self) the_sum = sum(math.exp(x.value) for x in result.data) if the_sum > 0: for x in result.data: x.value = math.exp(x.value)/the_sum return result def log(x,t=None): if x <= 0: return 0 if t == None: return math.log(x) # default is base e, ie natural logarithm return math.log(x,t) # choose another baseNow, putting them to use:

sa: softmax 10|x> |x> sa: softmax (10|x> + 5|y> + 30|z> + |u> + 0.5|v>) 0.0|x> + 0.0|y> + 1.0|z> + 0.0|u> + 0.0|v> sa: softmax (20|x> + 25|y>) 0.007|x> + 0.993|y> sa: log |x> 0|x> -- default is base e, so log(e) = 1. sa: log 2.71828 |x> 1.0|x> sa: log[2] 128|x> 7|x> sa: log[10] (5|a> + 10|b> + 100|c> + 375|d> + 123456|e>) 0.699|a> + |b> + 2|c> + 2.574|d> + 5.092|e>

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