# tfma.default_extractors

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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#L508-L693) |

Returns the default extractors for use in ExtractAndEvaluate.

    tfma.default_extractors(
        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,
        slice_spec: Optional[List[slicer.SingleSliceSpec]] = None,
        materialize: Optional[bool] = None,
        tensor_adapter_config: Optional[tensor_adapter.TensorAdapterConfig] = None,
        custom_predict_extractor: Optional[https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma/extractors/Extractor] = None,
        config_version: Optional[int] = None
    ) -> List[https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma/extractors/Extractor]

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| ## Args ||
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| `eval_shared_model` | Shared model (single-model evaluation) or list of shared models (multi-model evaluation). Required unless the predictions are provided alongside of the features (i.e. model-agnostic evaluations). |
| `eval_config` | Eval config. |
| `slice_spec` | Deprecated (use EvalConfig). |
| `materialize` | True to have extractors create materialized output. |
| `tensor_adapter_config` | Tensor adapter config which specifies how to obtain tensors from the Arrow RecordBatch. If None, an attempt will be made to create the tensors using default TensorRepresentations. |
| `custom_predict_extractor` | Optional custom predict extractor for non-TF models. |
| `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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| ## Raises ||
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| `NotImplementedError` | If eval_config contains mixed serving and eval models. |

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