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NEW QUESTION 42
A trial is running on a GPU slot within a resource pool on HPE Machine Learning Development Environment.
That GPU fails. What happens next?

• A. The conductor reschedules the trial on another available GPU in the pool, and the trial restarts from the latest checkpoint.
• B. The trial fails, and the ML engineer must manually restart it from the latest checkpoint using the WebUI.
• C. The concluded reschedules the trial on another available GPU in the pool, and the trial restarts from the state of the latest training workload.
• D. The trial tails, and the ML engineer must restart it manually by re-running the experiment.

Answer: A

NEW QUESTION 43
You want to set up a simple demo cluster for HPE Machine Learning Development Environment (or the open source Determined Al) on Amazon Web Services (AWS). You plan to use "det deploy" to set up the cluster.
What is one prerequisite?

• A. Manually creating the AWS EC2 instance with a PostgreSQL database
• B. Adding Amazon Elastic Kubernetes Services (EKS) to your AWS account
• C. Recording the name of a valid AWS EC2 keypair
• D. installing the NVIDIA Container Toolkit on your local machine

Answer: D

NEW QUESTION 44
A customer has Men expanding its deep learning (DO prefects and is confronting several challenges. Which of these challenges does HPE Machine Learning Development Environment specifically address?

• A. Complex and time-consuming data cleansing process
• B. Complex and time-consuming hyperparameter optimization (HPO)
• C. Time-consuming data collection
• D. Complex model deployment processes

Answer: A

NEW QUESTION 45
ML engineers are defining a convolutional neural network (CNN) model bur they are not sure how many filters to use in each convolutional layer. What can help them address this concern?

• A. Distributing the training across multiple CPUs
• B. Using a variable learning late
• C. Using hyperparameter optimization (HPO)
• D. Training the model on multiple epochs

Answer: D

NEW QUESTION 46
You are in a directory on your machine with your experiment config file and your model code. You enter this command:
det experiment create myfile.yaml
You receive this error:
det experiment create: error: the following arguments are required: model_def What should you do?

• A. Re-enter the command with a period (.) at the end.
• B. Make sure that you have already logged into the cluster with the "det login'' command.
• C. Make sure that the myfile.yaml tile includes code tor a PyTorchTrial or TFKerasTrial class.
• D. Re-enter the command with "-m" in which is the code filename.

Answer: C

NEW QUESTION 47
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