The Evaluator TFX pipeline component performs deep analysis on the training results for your models, to help you understand how your model performs on subsets of your data.
Evaluator and TensorFlow Model Analysis
Using the Evaluator Component
A Evaluator pipeline component is typically very easy to deploy and requires little customization, since all of the work is done by the Evaluator TFX component. Typical code looks like this:
from tfx import components import tensorflow_model_analysis as tfma ... # For TFMA evaluation taxi_eval_spec = [ tfma.SingleSliceSpec(), tfma.SingleSliceSpec(columns=['trip_start_hour']) ] model_analyzer = components.Evaluator( examples=examples_gen.outputs['examples'], feature_slicing_spec=taxi_eval_spec, model_exports=trainer.outputs['model'], fairness_indicator_thresholds = [0.25, 0.5, 0.75] )