tfma.is_batched_input
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Returns true if batched input should be used.
tfma.is_batched_input(
eval_shared_model: Optional[tfma.types.EvalSharedModel] = None,
eval_config: Optional[tfma.EvalConfig] = None,
config_version: Optional[int] = None
) -> bool
We will keep supporting the legacy unbatched V1 PredictExtractor as it parses
the features and labels, and is the only solution currently that allows for
slicing on transformed features. Eventually we should have support for
transformed features via keras preprocessing layers.
Args |
|---|
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.
|
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.
|
Returns |
|---|
|
A boolean indicating if batched extractors should be used.
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tfma.is_batched_input\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/model-analysis/blob/v0.46.0/tensorflow_model_analysis/api/model_eval_lib.py#L1035-L1062) |\n\nReturns true if batched input should be used. \n\n tfma.is_batched_input(\n eval_shared_model: Optional[../tfma/types/EvalSharedModel] = None,\n eval_config: Optional[../tfma/EvalConfig] = None,\n config_version: Optional[int] = None\n ) -\u003e bool\n\nWe will keep supporting the legacy unbatched V1 PredictExtractor as it parses\nthe features and labels, and is the only solution currently that allows for\nslicing on transformed features. Eventually we should have support for\ntransformed features via keras preprocessing layers.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `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). |\n| `eval_config` | Eval config. |\n| `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. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A boolean indicating if batched extractors should be used. ||\n\n\u003cbr /\u003e"]]
View source on GitHub