HP HPE2-N69 Exam Practice Test Instant Access

Question 1

Compared to Asynchronous Successive Halving Algorithm (ASHA), what is an advantage of Adaptive ASHA?

AAdaptive ASHA can handle hyperparameters related to neural architecture while ASHA cannot.

BASHA selects hyperparameter configs entirely at random while Adaptive ASHA clones higher-performing configs.

CAdaptive ASHA can train more trials in certain amount of time, as compared to ASHA.

DAdaptive ASHA tries multiple exploration/exploitation tradeoffs oy running multiple Instances of ASHA.

Answer : B

Adaptive ASHA is an enhanced version of ASHA that uses a reinforcement learning approach to select hyperparameter configurations. This allows Adaptive ASHA to select higher-performing configs and clone those configurations, allowing for better performance than ASHA.

Question 2

What common challenge do ML teams lace in implementing hyperparameter optimization (HPO)?

AHPO is a joint ml and IT Ops effort, and engineers lack deep enough integration with the IT team.

BThey cannot implement HPO on TensorFlow models, so they must move their models to a new framework.

CImplementing HPO manually can be time-consuming and demand a great deal of expertise.

DML teams struggle to find large enough data sets to make HPO feasible and worthwhile.

Answer : C

Implementing hyperparameter optimization (HPO) manually can be time-consuming and demand a great deal of expertise. HPO is not a joint ML and IT Ops effort and it can be implemented on TensorFlow models, so these are not the primary challenges faced by ML teams. Additionally, ML teams often have access to large enough data sets to make HPO feasible and worthwhile.

Question 3

An HPE Machine Learning Development Environment cluster has this resource pool:

Name: pool 1

Location: On-prem

Agents: 2

Aux containers per agent: 100

Total slots: 0

Which type of workload can run In pool I?

ATraining

BGPU Jupyter Notebook

CValidation

DCPU-only Jupyter Notebook

Answer : D

Pool 1 has two agents, each with 100 aux containers, and a total of 0 slots. This means that the cluster is configured to run CPU-only workloads, such as running a CPU-only Jupyter Notebook. Training, GPU Jupyter Notebook, and validation workloads cannot be run on this cluster due to the lack of GPU resources.

Question 4

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?

ARe-enter the command with '-m' in which is the code filename.

BMake sure that the myfile.yaml tile includes code tor a PyTorchTrial or TFKerasTrial class.

CRe-enter the command with a period (.) at the end.

DMake sure that you have already logged into the cluster with the 'det login'' command.

Answer : B

Make sure that the myfile.yaml tile includes code for a PyTorchTrial or TFKerasTrial class. When creating an experiment with the det experiment create command, you need to specify the model_def parameter to provide the code for the PyTorchTrial or TFKerasTrial class. This code should be specified in the myfile.yaml file, so make sure that the myfile.yaml file includes the code for the model you want to use.

Question 5

You want to set up a simple demo cluster for HPE Machine Learning Development Environment for the open source Determined all on a local machine. Which OS Is supported?

AHP-UX v11i

BWindows Server 2016 or above

CWindows 10 or above

DRed Hat 7-based Linux

Answer : D

The OS supported for setting up a simple demo cluster for HPE Machine Learning Development Environment for the open source Determined on a local machine is Red Hat 7-based Linux. Red Hat 7-based Linux is an open source operating system that is used extensively in enterprise applications. It provides a stable and secure platform for running applications and is suitable for use in a demo cluster.

Question 6

You want to set up a simple demo Ouster tor HPE Machine learning Development Environment for the open source Determined AI) on a local machine. You plan to use "del deploy" to set up the cluster. What software must be installed on the machine before you run that command?

AKubernetes

BPyTorch

CTerralorm

DDocker

Answer : D

Before running the 'del deploy' command to set up the cluster, you must first install Docker on the machine. Docker is a containerization platform that is used to run applications in an isolated environment. It is necessary to have Docker installed before running the 'del deploy' command to set up the cluster for the open source Determined AI on a local machine.

Question 7

A company has an HPE Machine Learning Development Environment cluster. The ML engineers store training and validation data sets in Google Cloud Storage (GCS). What is an advantage of streaming the data during a trial, as opposed to downloading the data?

AStreaming requires just one bucket, while downloading requires many.

BThe trial can more quickly start up and begin training the model.

CThe trial can better separate training and validation data.

DSetting up streaming is easier that setting up downloading.

Answer : B

Streaming the data during a trial allows the data to be processed more quickly, as it does not need to be downloaded onto the cluster before training can begin. This means that the trial can start up faster and the model can begin training more quickly.

HPE2-N69 Using HPE AI and Machine Learning Exam Practice Test