April 2020
Intermediate to advanced
816 pages
18h 32m
Chinese
Content preview from 精通機器學習
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672
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第十九章：大規模訓練與部署 TensorFlow 模型
如果你想要將操作放到非預設的裝置
，
可使用
tf.device()
：
>>> with
tf.device("/cpu:0"):
...
c = tf.Variable(42.0)
...
>>>
c.device
'/job:localhost/replica:0/task:0/device:CPU:0'
CPU
一定會被視為單一裝置
（
/cpu:0
），
即使你的電腦有多個
CPU
核心
。
如果
CPU
有多執行緒
kernel，
被放到
CPU
的任何操作都可以在多個核心
之間平行運行
。
如果你明確地將一個操作或變數放到不存在或沒有
kernel
的裝置
，
你將會看到例外
。
但
是有時你可能比較想要退回去使用
CPU，
例如
，
如果你的程式可以在純
CPU
電腦運行
，
也可以在
GPU
電腦運行
，
你可能想要讓
TensorFlow
在純
CPU
電腦忽略
tf.device("/
gpu:*")
，
為此
，
你可以在匯入
TensorFlow
之後呼叫
tf.config.set_soft_device_
placement(True)
：
當一個置放請求失敗時
，TensorFlow
會退回去使用它的預設置放規則
（
也就是當
GPU 0
存在而且有
GPU kernel
時
，
預設使用
GPU 0，
否則使用
CPU 0）。
那麼
，TensorFlow
究竟是如何在多台裝置上執行這些操作的
？
在多台裝置上平行執行
第
12
章介紹過
，
使用
TF Functions
的其中一項好處就是平行執行
。
我們來更深入地討論
這一點
。
當
TensorFlow ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.