# tfma.default_evaluators

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/model-analysis/blob/v0.46.0/tensorflow_model_analysis/api/model_eval_lib.py#L696-L767) |

Returns the default evaluators for use in ExtractAndEvaluate.

    tfma.default_evaluators(
        eval_shared_model: Optional[https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma/types/EvalSharedModel] = None,
        eval_config: Optional[https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma/EvalConfig] = None,
        schema: Optional[schema_pb2.Schema] = None,
        compute_confidence_intervals: Optional[bool] = False,
        min_slice_size: int = 1,
        serialize: bool = False,
        random_seed_for_testing: Optional[int] = None,
        config_version: Optional[int] = None
    ) -> List[https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma/evaluators/Evaluator]

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| ## Args ||
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| `eval_shared_model` | Optional shared model (single-model evaluation) or list of shared models (multi-model evaluation). Only required if there are metrics to be computed in-graph using the model. |
| `eval_config` | Eval config. |
| `schema` | A schema to use for customizing default evaluators. |
| `compute_confidence_intervals` | Deprecated (use eval_config). |
| `min_slice_size` | Deprecated (use eval_config). |
| `serialize` | Deprecated. |
| `random_seed_for_testing` | Provide for deterministic tests only. |
| `config_version` | Optional config version for this evaluation. This should not be explicitly set by users. It is only intended to be used in cases where the provided eval_config was generated internally, and thus not a reliable indicator of user intent. |

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