Returns default EvalSharedModel.
tfma.default_eval_shared_model(
eval_saved_model_path: Text,
add_metrics_callbacks: Optional[List[types.AddMetricsCallbackType]] = None,
include_default_metrics: Optional[bool] = True,
example_weight_key: Optional[Union[Text, Dict[Text, Text]]] = None,
additional_fetches: Optional[List[Text]] = None,
blacklist_feature_fetches: Optional[List[Text]] = None,
tags: Optional[List[Text]] = None,
model_name: Text = '',
eval_config: Optional[tfma.EvalConfig
] = None,
custom_model_loader: Optional[tfma.types.ModelLoader
] = None,
rubber_stamp: Optional[bool] = False
) -> tfma.types.EvalSharedModel
Used in the notebooks
Args |
eval_saved_model_path
|
Path to EvalSavedModel.
|
add_metrics_callbacks
|
Optional list of callbacks for adding additional
metrics to the graph (see EvalSharedModel for more information on how to
configure additional metrics). Metrics for example count and example
weights will be added automatically.
|
include_default_metrics
|
True to include the default metrics that are part
of the saved model graph during evaluation. Note that
eval_config.options.include_default_metrics must also be true.
|
example_weight_key
|
Example weight key (single-output model) or dict of
example weight keys (multi-output model) keyed by output name.
|
additional_fetches
|
Prefixes of additional tensors stored in
signature_def.inputs that should be fetched at prediction time. The
"features" and "labels" tensors are handled automatically and should not
be included.
|
blacklist_feature_fetches
|
List of tensor names in the features dictionary
which should be excluded from the fetches request. This is useful in
scenarios where features are large (e.g. images) and can lead to excessive
memory use if stored.
|
tags
|
Model tags (e.g. 'serve' for serving or 'eval' for EvalSavedModel).
|
model_name
|
Optional name of the model being created (should match
ModelSpecs.name). The name should only be provided if multiple models are
being evaluated.
|
eval_config
|
Eval config. Only used for setting default tags.
|
custom_model_loader
|
Optional custom model loader for non-TF models.
|
rubber_stamp
|
True when this run is a first run without a baseline
model while a baseline is configured, the diff thresholds will be ignored.
|