snowflake.ml.model.batch_inference.OutputSpec

class snowflake.ml.model.batch_inference.OutputSpec(*, stage_location: str, mode: SaveMode = SaveMode.ERROR)

Bases: BaseModel

Output block of the batch inference job specification.

Results are written under <stage_location>/<job_name>/.

stage_location

The stage path under which batch inference results will be saved. This should be a full path including the stage with @ prefix. For example, ‘@My_DB.PUBLIC.MY_STAGE/some/path/’. Only Snowflake internal stages are supported.

Type:

str

mode

The save mode that determines behavior when files already exist at the output stage location. Defaults to SaveMode.ERROR.

Type:

SaveMode

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Attributes

model_computed_fields = {}
model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_extra

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to “allow”.

model_fields = {'mode': FieldInfo(annotation=SaveMode, required=False, default=<SaveMode.ERROR: 'error'>), 'stage_location': FieldInfo(annotation=str, required=True)}
model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

stage_location: str
mode: SaveMode