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This is populated with the new ModelSource object, which stores a reference to a TFX PushedModel.
Add model_parameters.input_format_map and model_parameters.output_format_map.
These are key-value pairs, and are used to render inputs and outputs in tabular form. They can be used as an alternative to the singular model_parameters.input_format and model_parameters.output_format fields.
Functions
Add from_json().
model_card_toolkit.source
This is a new submodule, and is responsible for ModelCardToolkit's' inputs (see TFX standard artifacts). It provides the following classes:
MlmdSource: Args to extract data from TFX artifacts in MLMD. Contains the mlmd_store and model_uri args. Previously, these were args to ModelCardToolkit.
Source: Args to extract data from TFX artifacts outside MLMD (by passing in a path to the artifact, or by passing in the artifact directly). Contains tfma, tfdv, and model args.
Bug fixes and other changes
ModelCardToolkit
model_card.quantitative_analysis.performance_metrics is now populated when a tfma.EvalResult is found in MLMD store.
export_format() and update_model_card() now accept model_card_pb2.ModelCard's, in addition to model_card.ModelCard's.
tfx_util
Add annotate_eval_result_metrics(), which appends PerformanceMetrics to a ModelCard based on a tfma.EvalResult.
Add read_stats_protos(), which returns dataset stats protos for all splits in the provided directory.
Add filter_metrics() to facilitate filtering out unwanted TFMA metrics in model cards.
Add filter_features() and tfx._util.read_stats_protos_and_filter_features() to facilitate filtering out unwanted TFDV features in model cards.
PerformanceMetrics
Add confidence_interval field.
Breaking changes and Deprecations
Replace ModelCardToolkit(output_dir, mlmd_store, model_uri) with ModelCardToolkit(output_dir, mlmd_source, source). See "Major Features and Improvements" above for details.
Complete deprecation of ModelCardToolkit.update_model_card_json(). Users should migrate to ModelCardToolkit.update_model_card(), which uses a proto representation. Alternatively, users can use ModelCard.to_json() and ModelCard.from_json() to interact with JSON representations.