Accelerator | project aims to crack Any galgame using dynamic memory

I'm trying to deploy a cluster with self managed node groups. No matter what config options I use, I always come up with the following error:

Error: Post "http://localhost/api/v1/namespaces/kube-system/configmaps": dial tcp 127.0.0.1:80: connect: connection refusedwith module.eks-ssp.kubernetes_config_map.aws_auth[0]on .terraform/modules/eks-ssp/aws-auth-configmap.tf line 19, in resource "kubernetes_config_map" "aws_auth":resource "kubernetes_config_map" "aws_auth" {

​

The .tf file looks like this:

I am trying to add an accelerator to the rocket chip framework through the MMIO peripheral. I went through the GCD example and was able to build the basic GCD code. I then replaced the GCD with an accelerator which has it's own Config, Parameters and Field information. Now when I try to pass this information to the rocket chip there is a name clash with the freechips.rocketchip.config.{Parameters, Field, Config}. I tried specifying the whole path i.e; accelerator.util.conig.Parameters to distinguish it from freechips.rocketchip.config.Parameters but it still gave me the same error. When I remove my accelerator configs and parameters and pass simple hand made parameters the build is successful, however, when I add my config I get %Error-TIMESCALEMOD and this error is in the generated file which I am not modifying. I tried a work around by altering my verilator options but that goes down a rabbit hole of errors. I have narrowed down the problem to the fact that this is being caused because I am using two different configs both of which have their own Config.scala file shown here Is there a way to fix this problem? I have attached the error with this question.

Sometimes we need to preprocess the data by feeding them through preprocessing layers. This becomes problematic when your model is an autoencoder, in which case the input is both the x and the y.

Correct me if I'm wrong, and perhaps there's other ways around this, but it seems obvious to me that if the true input is, say, [1,2,3], and I scale this to 0 and 1: [0,0.5,1], then the model should be evaluating the autoencoder based on x=[0,0.5,1] and y=[0,0.5,1] rather than x=[1,2,3]. So if my model is, for example:

I have a JAX Boolean array and want to print a statement combined with sum of Trues:

Since some time around March 4, suddenly I have not been able to create a Cloud TPU node.

When I attempt to create a TPU node/VM via GUI, it crashes upon choosing TPU type with any region. I get tons of JS errors in the console:

I'm trying to setup a Google Kubernetes Engine cluster with GPU's in the nodes loosely following these instructions, because I'm programmatically deploying using the Python client.

For some reason I can create a cluster with a NodePool that contains GPU's

...But, the nodes in the NodePool don't have access to those GPUs.

I've already installed the NVIDIA DaemonSet with this yaml file: https://raw.githubusercontent.com/GoogleCloudPlatform/container-engine-accelerators/master/nvidia-driver-installer/cos/daemonset-preloaded.yaml

You can see that it's there in this image:

For some reason those 2 lines always seem to be in status "ContainerCreating" and "PodInitializing". They never flip green to status = "Running". How can I get the GPU's in the NodePool to become available in the node(s)?

Based on comments I ran the following commands on the 2 NVIDIA pods; kubectl describe pod POD_NAME --namespace kube-system.

To do this I opened the UI KUBECTL command terminal on the node. Then I ran the following commands:

gcloud container clusters get-credentials CLUSTER-NAME --zone ZONE --project PROJECT-NAME

Then, I called kubectl describe pod nvidia-gpu-device-plugin-UID --namespace kube-system and got this output:

I am trying to run a Custom Training Job in Google Cloud Platform's Vertex AI Training service.

The job is based on a tutorial from Google that fine-tunes a pre-trained BERT model (from HuggingFace).

When I use the gcloud CLI tool to auto-package my training code into a Docker image and deploy it to the Vertex AI Training service like so:

I try to build a simple Text Editor using Electron. At the moment I want to add a custom title bar which doesn't really work as the buttons are not clickable...

I added an onclick tag to the buttons.

main.js:

I have a custom Class in Excel, and some of its methods are recognised while others aren't.

VBA returns the run-time error '438' object doesn't support this property or method once my module gets to .addButton "button1", "Click Me", "msgbox (""Button clicked!"")" but it has no issue with the previous line, which is a method of the same object.

What could be causing VBA to not recognise the addButton() method, when it recognises createForm() and successfully creates a UserForm?

Module (Example.bas)