使用gcloud ML引擎时如何设置环境变量? [英] How to set an environment variable when using gcloud ML engine?

问题描述

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(环境:Windows 7，Python 3.6，Keras& tensorflow库，gcloud ml引擎)

(Environments: Windows 7, Python 3.6, Keras & tensorflow libs, gcloud ml engine)

我正在使用gcloud ml引擎运行某些Keras ML模型示例，如

I am running certain Keras ML model examples using gcloud ml engine as introduced here. Everything was fine but I just got various results among multiple runs although I was using the same training and validation data. My goal is to make reproductive training results from multiple runs.

我搜索了一段时间，在此 Keras Q&A 关于获得生殖结果.基本上，他们首先建议这样做:

I googled it for a while and found some solutions in this Keras Q&A regarding making reproductive results. Basically they first suggested this:

首先，您需要在程序启动之前将PYTHONHASHSEED环境变量设置为0(而不是在程序本身内部).

First, you need to set the PYTHONHASHSEED environment variable to 0 before the program starts (not within the program itself).

我知道我可以在自己的计算机上本地设置变量，也可以如介绍的那样在部署gcloud函数时进行设置此处.

I know I could set the variables locally on my own machine, or I could set it when I deploy gcloud function as introduced here.

但是，当我使用 gcloud ML引擎(在服务器端但不在本地)时，我只是不知道如何设置环境变量.因此，当我的模型程序在那里运行时，我无法在gcloud服务器上设置"PYTHONHASHSEED = 0".

But, I just do not know how to set environment variables when I was using gcloud ML engine (on server side but NOT on local). So I cannot set "PYTHONHASHSEED=0" on the gcloud server when my model programs running there.

顺便说一句，总的来说，我知道随机性在ML领域是有用的，但是我对产生生殖结果的话题还不是很熟悉，因此也欢迎对此话题提出任何想法.谢谢！

BTW, in general I know the randomness is a useful nature in the ML field but I am not very familiar about the topic of making reproductive results yet, so any thoughts regarding this topic are also welcome. Thanks!

大七

PS: 我尝试在下面的运行时设置环境变量:

PS: I have tried to setting the environment variables in running time below:

import os
os.environ["PYTHONHASHSEED"] = "0" 
print(hash("keras"))

但是不能起到在程序启动前设置变量"的作用.因此，有了此代码，我仍然无法从多次运行中获得相同的哈希结果.另一方面，在本地，如果在运行代码之前设置"PYTHONHASHSEED = 0"，则可能会得到相同的哈希结果.

But it cannot make the effect that "setting the variables before the program starts". So by having this code, I still cannot get the same hash results from the multiple runs. On the other hand, on local, if I set "PYTHONHASHSEED=0" before running the code, I may get the same hash results.

推荐答案

我不认为Cloud ML Engine API提供了设置环境变量的机制.但是，您可以通过编写包装脚本(NB:未测试的代码)来解决此问题:

I don't believe the Cloud ML Engine API provides a mechanism to set environment variables. However, you might be able to workaround this by writing a wrapper script (NB: UNTESTED CODE):

import os
import subprocess

env = os.environ.copy()
env["PYTHONHASHSEED"] = "0"

subprocess.check_call(['python', 'main.py'], env=env)

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