Question 1mediummultiple choice
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Refer to the exhibit. ``` symptom: Cloud Build trigger fails with: Build failed: could not resolve source: fetching source: fetching storage object: object not found trigger configuration: event: push to branch main repository: my-repo included files: 'train/**' excluded files: 'test/**' source: gs://my-bucket/source.tar.gz ```
Drag steps to the numbered slots on the right, or tap a step then tap a slot.
Drag steps to the numbered slots on the right, or tap a step then tap a slot.
Drag a concept onto its matching description — or click a concept then click the description.
End-to-end ML platform for building, deploying, and managing models
Train high-quality custom ML models with minimal effort
Managed service for distributed training of ML models
Custom ASIC for accelerating ML training workloads
Create and execute ML models using SQL queries
Drag a concept onto its matching description — or click a concept then click the description.
Continuous integration and deployment for ML pipelines
Track and manage different model iterations
Monitor for changes in data or model performance over time
Schedule or trigger model retraining based on conditions
Compare model versions in production with traffic splitting
environment_variables: GOOGLE_APPLICATION_CREDENTIALS: /home/airflow/gcs/data/vertex-ai-key.json AIRFLOW_VAR_PROJECT_ID: my-project AIRFLOW_VAR_LOCATION: us-central1
gcloud ai pipelines submit \ --project=my-project \ --region=us-central1 \ --pipeline-job-name=training-pipeline-20231001 \ --pipeline-template=template.yaml \ --parameter='input_data_path=gs://my-bucket/data/input.csv' \ --parameter='training_epochs=50'
Refer to the exhibit.
```
# vertex_ai_pipeline.yaml
components:
- name: data_processing
container:
image: us-central1-docker.pkg.dev/my-project/my-repo/data_processor:v1
command: ["python", "process.py"]
- name: training
container:
image: us-central1-docker.pkg.dev/my-project/my-repo/trainer:v2
command: ["python", "train.py"]
inputs:
- name: train_data
type: Dataset
outputs:
- name: model
type: Model
- name: evaluation
container:
image: us-central1-docker.pkg.dev/my-project/my-repo/evaluator:v1
inputs:
- name: model
type: Model
- name: test_data
type: Dataset
outputs:
- name: metrics
type: Metrics
```{
"pipelineJob": {
"pipelineSpec": {
"pipelineInfo": {"name": "training-pipeline"},
"root": {
"dag": {
"tasks": {
"preprocess": {
"taskInfo": {"name": "preprocess"},
"componentRef": {"name": "data-processing"},
"inputs": {"data": {"artifacts": [{"name": "raw_data", "type": "Dataset"}]}}
},
"train": {
"taskInfo": {"name": "train"},
"componentRef": {"name": "trainer"},
"inputs": {"dataset": {"taskOutputArtifact": {"taskName": "preprocess", "outputKey": "processed_data"}}},
"dependentTasks": ["preprocess"],
"executorLabel": "train-exec"
}
}
}
}
},
"runtimeConfig": {
"gcsOutputDirectory": "gs://my-bucket/pipeline-output",
"parameterValues": {
"learning_rate": 0.01,
"epochs": 10
},
"inputArtifacts": {
"raw_data": {
"gcsSourceArtifact": {
"artifacts": [{"uri": "gs://my-bucket/data/raw.csv"}]
}
}
}
}
}
}