• Remove semantic-version dependency.
• Update jinja2 dependency.

• Fix bug where ModelCardGenerator fails if template_io is unspecified.

• ModelCardArtifact, a TFX/MLMD artifact which references the assets generated by MCT. This can be created with model_card_toolkit.tfx.create_and_save_artifact().
• tfx.executor.Executor, which can be used as the core MCT logic for a TFX custom component.
• tfx.component.ModelCardGenerator, a component that can be used to generate Model Cards directly in a TFX pipeline.

• ModelCard.merge_from_json(), allowing ModelCards to be populated with JSON without overwriting all pre-existing fields.
• Minor styling change to table CSS in default HTML template
• Minor update to CSS linting in default HTML template

• source classes now uses tfx.types.Artifact instead of standard_artifacts.

• ModelCard updates
  • Fields
    • Add model_details.path.
      • 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.

• 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.

• 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.

• Update TFX compatibility to TFX 1.2.
• Fix bug where all datasets from MLMD were being compressed into one model_card.Dataset object.

• Introduce model_card.proto. See https://developers.google.com/protocol-buffers for more info.
• All classes in model_card_toolkit.model_card submodule now have to_proto(), merge_from_proto(), copy_from_proto(), and clear() functions.
• ModelCardToolkit.export_format() now accepts model_card arg.
• json_util.update(), which updates a v0.0.1 JSON object to a v0.0.2 JSON object.

• Update default template layout so charts can wrap to multiple rows
• Installing from source now requires Bazel>=2.0.0.
• Update model card templates to use new schema.
• model_card_toolkit.utils.validation.validate_json_schema() can now validate both schema v0.0.1 and v0.0.2.
• Add _jinja_loader attribute to model_card_toolkit to allow custom Jinja loaders.

• JSON schema v0.0.2 replaces JSON schema v0.0.1.
• ModelCardToolkit.update_model_card_json() deprecated and replaced with ModelCardToolkit.update_model_card(). Writes to data/model_card.proto instead of data/model_card.json.
• graphics.annotate_dataset_feature_statistics_plots accepts a list of stats files instead of two individual train and eval stats params.

• Update model_card.py docstrings. Now hosted on Responsible AI.

• In default_template.md.jinja and default_template.html.jinja, generate metrics table from quantitative_analysis.performance_metrics.

• Reference URLs in default HTML and Markdown template are now hyperlinks
• Fix bug where Considerations div is displayed in HTML model cards, even if Considerations div is empty.
• Update required fields in schema.
  • Removed considerations as required field.
  • Add lower_bound and upper_bound as required fields to confidence_interval.
• Fixed the part dependencies error for new pip dependency resolver.
• Update how UI templates are copied to be compatible with different platforms (colab, wetlab).
• Add model_card_toolkit.validation.validate_json_schema(), a function to validate a Python dictionary against the Model Card JSON schema.
• Fix the bug that some slices may have extra metrics that other slices does not have. e.g. ERROR metric.

• add Markdown template

• remove quantitative_analysis from required fields
• add input_format and export_format fields
• add model_architecture, input_format, and export_format to HTML template
• add Cats vs Dogs util for Standalone_Model_Card_toolkit_Demo.ipynb

• Rename _figure_to_base64str to figure_to_base64str

Initial release of Model Card Toolkit.