Topic 1 Question 144

Professional Machine Learning Engineer

Topic 1 Question 144
You are developing an image recognition model using PyTorch based on ResNet50 architecture. Your code is working fine on your local laptop on a small subsample. Your full dataset has 200k labeled images. You want to quickly scale your training workload while minimizing cost. You plan to use 4 V100 GPUs. What should you do?
- Create a Google Kubernetes Engine cluster with a node pool that has 4 V100 GPUs. Prepare and submit a TFJob operator to this node pool.
- Create a Vertex AI Workbench user-managed notebooks instance with 4 V100 GPUs, and use it to train your model.
- Package your code with Setuptools, and use a pre-built container. Train your model with Vertex AI using a custom tier that contains the required GPUs.
- Configure a Compute Engine VM with all the dependencies that launches the training. Train your model with Vertex AI using a custom tier that contains the required GPUs.
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- 正解だと思う選択肢: C
  Custom trainer , don't overthink 1000%, this is google recommendation. you don't need Vertex AI Workbench user-managed notebooks,Google Kubernetes Engine, Compute Engine at at all , it is a waste of your effort https://cloud.google.com/vertex-ai/docs/training/configure-compute#specifying_gpus You can choose as your want
  
  👍 4
  John_Pongthorn2023/03/07
- 正解だと思う選択肢: A
  Google Kubernetes Engine (GKE) is a powerful and easy-to-use platform for deploying and managing containerized applications. It allows you to create a cluster of virtual machines that are pre-configured with the necessary dependencies and resources to run your machine learning workloads. By creating a GKE cluster with a node pool that has 4 V100 GPUs, you can take advantage of the powerful processing capabilities of these GPUs to train your model quickly and efficiently.
  
  You can then use the Kubernetes Framework such as TFJob operator to submit the job of training your model, which will automatically distribute the workload across the available GPUs.
  
  References:
  
  Google Kubernetes Engine TFJob operator Vertex Al
  
  👍 2
  TNT872023/02/13
- 正解だと思う選択肢: B
  It's B according to me, since VertexAI Notebook has alla dependencies for PyTorch that is the fastest solution
  
  👍 2
  Scipione_2023/02/16
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