ApplyConverterUnit
Fit one converter on the scoped data and transform the same dataset.
The single-dataset case, which is what applying a converter to a notebook
means. Equivalent to :class:FitConverterUnit followed by
:class:TransformDatasetUnit on the same dataset, kept as one unit for two
reasons: it is the common case, and when there is no row scope it hands
transform the very object fit saw, which some converters rely on to
skip recomputing (see below).
Use the split pair instead whenever the converter has to be learned from one dataset and applied to another — fit on train, transform on test.
Reads dataset and writes dataset: the same key on both sides, so any
number of these can be chained in one context, each one seeing what the
previous one produced.
That is also why nothing about column identity ever crosses the context
boundary. The scope is expressed as 1-based column and row indexes, and
those indexes are resolved against dataset.column_names read at the top
of execute — the dataset as it is right now. A converter that renames,
drops or adds columns changes what index 3 means, so a resolved column list
published to the context would be stale for the very next converter.
Parameters
- converter : object
- Converter to apply, together with its own configuration.
- scope
- Part of the dataset the converter applies to: 'columns' is a list of {'idx': n} and 'rows' a list of n, both 1-based. An empty column list means every column.
- target, default=
None - Target column handed to the converter as y, as {'idx': n} with n 1-based. Leave empty for unsupervised converters.
Methods
execute(self, ctx: DashAI.back.units.context.ExecutionContext) -> None
ApplyConverterUnitDo the unit's work, reading from and writing to the context.
Parameters
- ctx : ExecutionContext
- The shared execution context.
validate(self, ctx: DashAI.back.units.context.ExecutionContext) -> None
ApplyConverterUnitReject an out-of-bounds target before any work is done.
get_credential(self, name: str)
ConfigObjectResolve a registered credential component by name.
Parameters
- name : str
- Credential component class name (e.g. "HuggingFaceCredential").
Returns
- BaseCredential
- An instance of the requested credential component.
get_schema(cls) -> dict
ConfigObjectGenerates the component related Json Schema.
Returns
- dict
- Dictionary representing the Json Schema of the component.
validate_and_transform(self, raw_data: dict) -> dict
ConfigObjectIt takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.
Parameters
- raw_data : dict
- A dictionary with the data provided by the user to initialize the model.
Returns
- dict
- A validated dictionary with the necessary objects.