在尝试一些记忆技术时,我偶然发现这个基准测试结果与我的预期不符。似乎我犯了一些愚蠢的错误,有人看到我在做错了什么(基准测试给出了记忆和非记忆代码的相似结果)?
require 'benchmark'
# -----------------------------------------
class FactorialClass
@@sequence = [1]
def self.of( n )
@@sequence[n] || n * of( n - 1 )
end
end
# -----------------------------------------
def factorial_with_memoization
sequence = [1]
lambda = Proc.new do |n|
sequence[n] || n * lambda.call( n - 1 )
end
end
f = factorial_with_memoization()
# -----------------------------------------
def factorial n
n == 0 ? 1 : n * factorial( n - 1 )
end
# -----------------------------------------
count = 1_000
n = 1000
without_memoization = Benchmark.measure do
count.times do
factorial(n)
end
end
with_memoization_lambda = Benchmark.measure do
count.times do
f.call(n)
end
end
with_memoization_class = Benchmark.measure do
count.times do
FactorialClass.of(n)
end
end
puts "Without memoization : #{ without_memoization }"
puts "With memoization using lambda : #{ with_memoization_lambda }"
puts "With memoization using class : #{ with_memoization_class }"
**结果是:**
Without memoization : 1.210000 0.100000 1.310000 ( 1.309675)
With memoization using lambda : 1.750000 0.100000 1.850000 ( 1.858737)
With memoization using class : 1.270000 0.090000 1.360000 ( 1.358375)
答案 0 :(得分:2)
您永远不会将任何记忆值分配给缓存。正如@xlembouras所说,你没有记住任何东西。
class FactorialClass
@@sequence = [1]
def self.of( n )
# @@sequence[n] get evaluated to nil unless n is 0, always!
@@sequence[n] || n * of( n - 1 )
end
end
完成计算后,您需要手动将记忆值分配给缓存。
class FactorialClass
@@sequence = [1]
def self.of( n )
@@sequence[n] = (@@sequence[n] || n * of( n - 1 ))
end
end
但是,记忆真的适用于你的因子计算吗?否。
f(n) = n * f(n-1) = n * ((n-1) * f(n-2)) = ... = n * ((n-1) * (... * (3 * f(2))))
所有递归步骤计算新值的阶乘(从2到n),之前没有计算过。记忆不会在任何一步都被击中。