I am trying to build on top of this example. I am trying to deploy the shap explainer as a custom prediction routine on google AI platform. Unfortunately when I create the version I get the following error:
Create Version failed. Bad model detected with error: Model requires more memory than allowed. Please try to decrease the model size and re-deploy. If you continue to have error, please contact Cloud ML.
Furthermore, instead of text i am working with images, and the shap explainer is a GradientExplainer.
I have sent a message to google support, but the only result I have achieved is "The Free Trial status of project xxxxx has been upgraded and you are no longer entitled to free technical support. ". Sweet. I have also tried on a no free trial account, and I get the same problem. It is not related to the account being free. It just happened that I have sent the email from my personal account. Any suggestions?
Related
When accessing Google Cloud Platform Services, I'm requested to retry due to an unknown error. It affects all services I want to access.
The snapshot below showcases the issue with Google Cloud Build.
Here's the same error with Google Cloud Storage.
This has first occurred month ago but been automagically resolved without any further action from my side. This second appearance has now lasted 4 days.
Looking at Google Cloud Status, I can't link any incident to this behaviour.
Options I've been exploring with no success are:
Logging back in
Checking credential access
Important notes:
I have access to the global project dashboard: https://console.cloud.google.com/home/dashboard?project=<project-name>
Other teammates do not face this. I'm now left with a few further actions since I access have been verified.
I tried disabling all the browser extensions. Before narrowing it down to find that the Apollo Client DevTools extension was the culprit.
I had the same error resolved disabling "Keepa - Amazon Price Tracker" extension.
I have been using the Google Cloud speech recognition service for some time, through a python application.
Due to accidentally copying my Google Cloud json file to a GitHub shared location (I was doing a backup), I suddenly got a warning from Google Cloud that I was violating the rules as json is private. Then, I promptly removed the file, but nevertheless, I got an email saying that my resources for my project "santo1" were suspended, saying some reasons of "cryptocurrency mining" which I have no idea.
I applied to reactivate and my appeal was accepted promptly, saying that my resources about santo1 were reinstated.
Unfortunately, the speech recognition still didn't work.
Launching it from python, it records from the microphone but no answer from the service - and no error messages at all.
Then I attempted the following:
regenerate API
create a new json
create a new project with its own json under my same google account
as suggested by the Google Cloud chat operator, I manually clicked play to the VM resource that appeared stopped
create a new gmail account, with another new project, setup with billing and everything (also reconfigured through "gcloud init")
None of these attempts worked.
I need assistance on this, as the chat operator didn't seem capable of telling me more.
Thank you in advance
Best regards
I would recommend you to contact GCP support for this case as your cloud service could be still in suspended status regardless your access is OK
Apparently, the access key is stolen and used by hackers and they did crypto mining using your GCP account, hence your service account was banned
If it's your testing account/project, you should consider to create a new project rather than continue with it, the hacker could create some other services which you may not realize until too late
Worse case is it's your PROD service, then you'd better review the bill and transaction report thoroughly
When I open the Google Cloud Shell Code Editor it is not loading the resources and hence I am unable to work. I have attached a screenshot below with a view of the developer tools console. Please help me out. Thanks.
This issue seems to be related to an internal project/billing configuration. Since this kind of access errors are thrown when the accounts have payment issues, I think that you should firstly verify that your billing account is in a good status; however, if you continue getting these error messages after this validation, I suggest you to take a look the Issue Tracker tool that you can use to raise a Cloud Shell ticket in order to verify this scenario with the Google Technical Support Team.
A couple things could cause this:
An interfering browser extension
Are you using any browser extensions that could be interfering
(e.g., an ad blocker)
A bug.
As #Armin_SC suggested, use Issue Tracker to file an issue in this case.
As a workaround, you might want to try gcloud compute ssh to connect to your instances.
I'm using Google cloud machine learning to get prediction on an image.
I have created a model and a version in cloud-ml with my training data, but when I try to get a prediction with gcloud beta ml predict sometimes cloud-ml gives me the correct results, while some other times using the same command and the same files I encounter a server error 502, as you can see here.
I saw this post and I know that predict is actually an alpha feature and sometimes it gives problems. Can it be my case?
If so, is there alternative? Or, will there be a new release in the near future?
Note that the online prediction feature is now in Beta.
I'd suggest trying your scenario to see if you can get past the failed requests on startup.
In particular, please ensure the request to deploy a model version is complete before issuing requests.
I've been trying to use custom made images to run my google data flow pipeline. Given the information from https://cloud.google.com/compute/docs/reference/latest/images I've tested the following code snippets:
DataflowPipelineOptions options = PipelineOptionsFactory.create().as(DataflowPipelineOptions.class);
...
options.setDiskSourceImage("ubuntu-1504-vivid-v20150911");
options.setDiskSourceImage("projects/ubuntu-os-cloud/global/images/ubuntu-1504-vivid-v20150911");
options.setDiskSourceImage("https://www.googleapis.com/compute/beta/projects/ubuntu-os-cloud/global/images/ubuntu-1504-vivid-v20150911");
all of the above tries led to the following error in my pipeline:
(b9c7b66a676906f4): Unable to create VMs. Causes: (b9c7b66a67690aef): Error: Message: Invalid value for field 'resource.disks[0].initializeParams.sourceImage': '[edited]'. Must be the URL to a Compute resource of the correct type HTTP Code: 400
Using a custom disk image with Dataflow is not a viable option. The flag diskSourceImage is deprecated and will be removed in a future SDK release. The reason it is no longer supported is because the Dataflow service relies on versioned resources in the VM image. So Dataflow needs control of the VM image so that we can upgrade it as necessary. If users supply their own custom images we have no way of keeping them in sync with the requirements of the Dataflow service.
If your custom VM image is based off a Dataflow image then you would be able to execute jobs using that custom image until the next release of a Dataflow VM image. There is no reasonable way in which you would be able to keep your custom images in sync with Dataflow's VM images so that you would be able to keep this working.
If you would like to customize the VM image please let us know why (e.g. send us an email at dataflow-feedback#google.com) so we can either suggest an alternative solution or else consider supporting your use case in the future.
There's a subtle issue with setDiskSourceImage -- it uses 'beta' instead of the current 'v1' version for Compute Engine. If you try the following, it should work:
options.setDiskSourceImage("https://www.googleapis.com/compute/v1/projects/ubuntu-os-cloud/global/images/ubuntu-1504-vivid-v20150911");