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PureML accepts matplotlib figures to be logged. These figures are converted to images before registering.

Logging inside the model decorator

Using log method, matplotlib figures are added to a model version:

from pureml.decorators import model
import pureml

@model('sales forecast')
def train_model():
    #model = model training code

    fig = #matplotlib figure object

    return model

When log method is invoked inside the model decorator, the figures are added to the version of the model that is registered by the decorator.

Logging outside the model decorator

Logging can be done outside the model decorator in the following ways:

           label='sales forecast')

By default, log method adds the figure to the latest version of the model. It can be added to a particular version of a model by providing version parameter as the following:

           label='sales forecast:v3')