ReclassTransformerConfig#
Note
All Configs are derived from rastervision.pipeline.config.Config
, which itself is a pydantic Model.
- pydantic model ReclassTransformerConfig[source]#
Configure a
ReclassTransformer
.Show JSON schema
{ "title": "ReclassTransformerConfig", "description": "Configure a :class:`.ReclassTransformer`.", "type": "object", "properties": { "type_hint": { "title": "Type Hint", "default": "reclass_transformer", "enum": [ "reclass_transformer" ], "type": "string" }, "mapping": { "title": "Mapping", "description": "The reclassification mapping.", "type": "object", "additionalProperties": { "type": "integer" } } }, "required": [ "mapping" ], "additionalProperties": false }
- Config
extra: str = forbid
validate_assignment: bool = True
- Fields
- build() ReclassTransformer [source]#
Build an instance of the corresponding type of object using this config.
For example, BackendConfig will build a Backend object. The arguments to this method will vary depending on the type of Config.
- Return type
- recursive_validate_config()#
Recursively validate hierarchies of Configs.
This uses reflection to call validate_config on a hierarchy of Configs using a depth-first pre-order traversal.
- revalidate()#
Re-validate an instantiated Config.
Runs all Pydantic validators plus self.validate_config().
Adapted from: https://github.com/samuelcolvin/pydantic/issues/1864#issuecomment-679044432
- update(pipeline: RVPipelineConfig = None, scene: SceneConfig = None)#
Update any fields before validation.
Subclasses should override this to provide complex default behavior, for example, setting default values as a function of the values of other fields. The arguments to this method will vary depending on the type of Config.
- Parameters
pipeline (RVPipelineConfig) –
scene (SceneConfig) –
- validate_config()#
Validate fields that should be checked after update is called.
This is to complement the builtin validation that Pydantic performs at the time of object construction.