the examples passed to Evaluator function below shouldnt be from tranform component , as this component updates the evaluation split with necessary preprocessing stpes applied during transformation.
using examples from ExampleGen will leads to input mismatch as evaluation split set there wouldn't take care of tranformation/preprocessing steps
so insteed of:
evaluator = Evaluator( examples=example_gen.outputs['examples'], model=trainer.outputs['model'], baseline_model=model_resolver.outputs['model'], eval_config=eval_config ) context.run(evaluator)
it should be ?:
from tfx.components import Evaluator evaluator = Evaluator(examples=transform.outputs['transformed_examples'], model=trainer.outputs['model'], baseline_model=model_resolver.outputs['model'], eval_config=eval_config) context.run(evaluator)
there may be another reason why you have used example gen in examples please let me if any
the examples passed to Evaluator function below shouldnt be from tranform component , as this component updates the evaluation split with necessary preprocessing stpes applied during transformation. using examples from ExampleGen will leads to input mismatch as evaluation split set there wouldn't take care of tranformation/preprocessing steps so insteed of:
evaluator = Evaluator( examples=example_gen.outputs['examples'], model=trainer.outputs['model'], baseline_model=model_resolver.outputs['model'], eval_config=eval_config ) context.run(evaluator)it should be ?:from tfx.components import Evaluator evaluator = Evaluator(examples=transform.outputs['transformed_examples'], model=trainer.outputs['model'], baseline_model=model_resolver.outputs['model'], eval_config=eval_config) context.run(evaluator)there may be another reason why you have used example gen in examples please let me if any