utils.types.Environments

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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
)

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