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Google Professional Machine Learning Engineer Exam - Topic 7 Question 20 Discussion

Posted by Celeste on May 04, 2022 at 01:46 PM

You need to train a computer vision model that predicts the type of government ID present in a given image using a GPU-powered virtual machine on Compute Engine. You use the following parameters:

* Optimizer: SGD

* Image shape = 224x224

* Batch size = 64

* Epochs = 10

* Verbose = 2

During training you encounter the following error: ResourceExhaustedError: out of Memory (oom) when allocating tensor. What should you do?

Suggested Answer: B

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13 comments · newest first
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Stanton 12 months ago
Not sure if just lowering the batch size is enough...
ER
Erinn 1 year ago
Wait, can reducing image size really solve this?
ST
Stacey 1 year ago
Changing the optimizer won't help with memory issues.
TE
Tenesha 1 year ago
I agree, batch size affects memory usage a lot.
LI
Lindsey 1 year ago
Reducing the batch size is usually a good first step.
JE
Jestine 1 year ago
I recall that adjusting the learning rate usually affects convergence speed, but I'm not convinced it would help with an out of memory error.
LO
Loreta 1 year ago
I practiced a similar question where reducing the image size helped with memory constraints. Maybe that could work here too?
RE
Reuben 1 year ago
I remember we discussed how reducing the batch size can help with memory issues during training. It seems like a good option here.
DY
Dyan 1 year ago
I'm not entirely sure, but I think changing the optimizer might not directly solve the out of memory error. It feels like a workaround rather than a fix.
VA
Valentine 1 year ago
Hmm, this looks like a tricky one. I'll need to think carefully about the capabilities of Automation script settings.
AD
Adolph 1 year ago
Hmm, this looks tricky. I'll need to carefully review the options and think through the potential causes.
CH
Chantell 1 year ago
I'm a bit confused about the default action of an IP filter. Is it to forward or drop packets? I'll need to double-check that detail.
RO
Roxane 1 year ago
I've got this! The X part represents the major version of MySQL. That's the most important part of the version number, so it makes sense that it would be denoted by the X.
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