Model API
- pydantic model mlopus.mlflow.ModelApi[source]
Bases:
Model
,EntityApi
Registered model metadata with MLflow API handle.
- field name: str [Required]
Model vame in the pattern [w-./]+
- field tags: Dict[str, Any] [Required]
Nested tags dict with JSON-serializable leaf-values and keys in the pattern: [w-/]+
- class Config
Bases:
object
Pydantic class config.
- find_versions(query=None, sorting=None)[source]
Search versions of this model with query in MongoDB query language.
- Parameters:
- Return type:
Iterator
[ModelVersionApi
]
- log_version(run, source, path_in_run=None, keep_the_source=None, allow_duplication=None, use_cache=None, version=None, tags=None)[source]
Publish artifact file or dir as model version inside the specified experiment run.
- Parameters:
- Run ID or object.
source¶ (
Union
[Path
,Callable
[[Path
],None
]]) –Seesource
path_in_run¶ (
Optional
[str
]) –Seepath_in_run
keep_the_source¶ (
Optional
[bool
]) –Seekeep_the_source
allow_duplication¶ (
Optional
[bool
]) –- See
use_cache
- See
version
- Model version tags.
- Return type:
- Returns:
New model version metadata with API handle.
- set_tags(tags)[source]
Set tags on this model.
- Parameters:
tags¶ (
Mapping
) – Seeschema.Model.tags
.- Return type:
- update()
Use API to get latest data for this entity and update this entity in place.
- Return type:
EntityApi
- property url: str
This model’s URL.