PyTorch 阶乘函数

Question

似乎没有用于计算阶乘的 PyTorch 函数。PyTorch 有没有办法做到这一点？我希望在 Torch 中手动计算泊松分布（我知道存在这种分布：https: //pytorch.org/docs/stable/ generated /torch.poisson.html），并且该公式需要分母中的阶乘。

泊松分布： https: //en.wikipedia.org/wiki/Poisson_distribution

Answer 1

我认为你可以找到它torch.jit._builtins.math.factorial BUT pytorch以及numpyand scipy（numpy 和 scipy 中的阶乘）使用的python内置函数math.factorial：

import math

import numpy as np
import scipy as sp
import torch


print(torch.jit._builtins.math.factorial is math.factorial)
print(np.math.factorial is math.factorial)
print(sp.math.factorial is math.factorial)

True
True
True

但是，相比之下，scipy除了“主流”之外math.factorial还包含着非常“特殊”的阶乘函数scipy.special.factorial。与模块中的函数不同，math它对数组进行操作：

from scipy import special

print(special.factorial is math.factorial)

False

# the all known factorial functions
factorials = (
    math.factorial,
    torch.jit._builtins.math.factorial,
    np.math.factorial,
    sp.math.factorial,
    special.factorial,
)

# Let's run some tests
tnsr = torch.tensor(3)

for fn in factorials:
    try:
        out = fn(tnsr)
    except Exception as err:
        print(fn.__name__, fn.__module__, ':', err)
    else:
        print(fn.__name__, fn.__module__, ':', out)

factorial math : 6
factorial math : 6
factorial math : 6
factorial math : 6
factorial scipy.special._basic : tensor(6., dtype=torch.float64)

tnsr = torch.tensor([1, 2, 3])

for fn in factorials:
    try:
        out = fn(tnsr)
    except Exception as err:
        print(fn.__name__, fn.__module__, ':', err)
    else:
        print(fn.__name__, fn.__module__, ':', out)

factorial math : only integer tensors of a single element can be converted to an index
factorial math : only integer tensors of a single element can be converted to an index
factorial math : only integer tensors of a single element can be converted to an index
factorial math : only integer tensors of a single element can be converted to an index
factorial scipy.special._basic : tensor([1., 2., 6.], dtype=torch.float64)