Labelbox

Changed
* `ModelRun.get_config()`
* Modifies get_config to return un-nested Model Run config
Added
* `ModelRun.update_config()`
* Updates model run training metadata
* `ModelRun.reset_config()`
* Resets model run training metadata
* `ModelRun.get_config()`
* Fetches model run training metadata

Changed
* `Model.create_model_run()`
* Add training metadata config as a model run creation param

v.3.26.0

Added
* `Batch.delete()` which will delete an existing `Batch`
* `Batch.delete_labels()` which will delete all `Label`’s created after a `Project`’s mode has been set to batch.
* Note: Does not include labels that were imported via model-assisted labeling or label imports
* Support for creating model config when creating a model run
* `RAW_TEXT` and `TEXT_FILE` attachment types to replace the `TEXT` type.

v.3.25.3

Fixed
* Label export will continue polling if the downloadUrl is None

v.3.25.2

Updated
* Mask downloads now have retries
* Failed `upload_data` now shows more details in the error message

Fixed
* Fixed Metadata not importing with DataRows when bulk importing local files.
* Fixed COCOConverter failing for empty annotations

Documentation
* Notebooks are up-to-date with examples of importing annotations without `schema_id`

Fix
* Remove extra dependency causing import errors.

v.3.25.0

Added
* Importing annotations with model assisted labeling or label imports using ontology object names instead of schemaId now possible
* In Python dictionaries, you can now use `schemaId` key or `name` key for all tools, classifications, options
* Labelbox's Annotation Types now support model assisted labeling or label imports using ontology object names
* Export metadata when using the following methods:
* `Batch.export_data_rows(include_metadata=True)`
* `Dataset.export_data_rows(include_metadata=True)`
* `Project.export_queued_data_rows(include_metadata=True)`
* `VideoObjectAnnotation` has `segment_index` to group video annotations into video segments

Removed
* `Project.video_label_generator`. Use `Project.label_generator` instead.

Updated
* Model Runs now support unassigned splits
* `Dataset.create_data_rows` now has the following limits:
* 150,000 rows per upload without metadata
* 30,000 rows per upload with metadata

v.3.24.1