内容简介:This commit makes the following writing improvements:And the following reading improvements:And the following improvements for both reading and writing:
This commit makes the following writing improvements:
write_to_vec
And the following reading improvements:
- Removes an unnecessary type annotation.
-
Fixes a dangerous unchecked slice access. Imagine a slice
[0x80]
--
the current code will read past the end of the slice some number of
bytes. The bounds check at the end will subsequently trigger, unless
something bad (like a crash) happens first. The cost of doing bounds
check in the loop body is negligible. - Avoids a mask on the final byte.
And the following improvements for both reading and writing:
-
Changes
for
toloop
for the loops, avoiding an unnecessarycondition on each iteration. This also removes the need for
leb128_size
.
All of these changes give significant perf wins, up to 5%.
以上就是本文的全部内容,希望本文的内容对大家的学习或者工作能带来一定的帮助,也希望大家多多支持 码农网
猜你喜欢:本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们。
scikit learn机器学习
黄永昌 / 机械工业出版社 / 2018-3-1 / CNY 59.00
本书通过通俗易懂的语言、丰富的图示和生动的实例,拨开了笼罩在机器学习上方复杂的数学“乌云”,让读者以较低的代价和门槛轻松入门机器学习。本书共分为11章,主要介绍了在Python环境下学习scikit-learn机器学习框架的相关知识。本书涵盖的主要内容有机器学习概述、Python机器学习软件包、机器学习理论基础、k-近邻算法、线性回归算法、逻辑回归算法、决策树、支持向量机、朴素贝叶斯算法、PCA ......一起来看看 《scikit learn机器学习》 这本书的介绍吧!