utils.types.Environments

View source on Github

Arize enum to specify your model environment represented in the platform for further analysis and comparisons

Environment	SDK Environment	Description
Training	Environments.TRAINING	An environment used to develop and train ML models (data prep, data processing, and model tuning)
Validation	Environments.VALIDATION	An environment used to evaluate and fine-tune ML models before deployment (testing performance separate from training data)
Production	Environments.PRODUCTION	An environment to deploy ML models and serve predictions
Corpus	Environments.CORPUS	An environment used to send Corpus/Knowledge Base data to Arize. Learn more here.

Code Example

response = arize_client.log(
    model_id='sample-model', 
    ...
    environment=Environments.TRAINING
)

response = arize_client.log(
    model_id='sample-model', 
    ...
    environment=Environments.VALIDATION
)

response = arize_client.log(
    model_id='sample-model', 
    ...
    environment=Environments.PRODUCTION
)

response = arize_client.log(
    model_id='sample-model', 
    ...
    environment=Environments.CORPUS
)