hubai_sdk.utils.config.SingleStageConfig

class documentation

class SingleStageConfig(CustomBaseModel):

View In Hierarchy

Undocumented

Method get_target_config Returns the target configuration for the given target.
Class Variable disable_onnx_optimization Undocumented
Class Variable disable_onnx_simplification Undocumented
Class Variable hailo Undocumented
Class Variable input_bin Undocumented
Class Variable input_file_type Undocumented
Class Variable input_model Undocumented
Class Variable inputs Undocumented
Class Variable intermediate_outputs_remote_url Undocumented
Class Variable keep_intermediate_outputs Undocumented
Class Variable output_remote_url Undocumented
Class Variable outputs Undocumented
Class Variable put_file_plugin Undocumented
Class Variable rvc2 Undocumented
Class Variable rvc3 Undocumented
Class Variable rvc4 Undocumented
Class Method _download_input_model Resolve input model paths and normalize OpenVINO IR inputs.
Class Method _validate_model Expand top-level config shortcuts into explicit tensor config.

Inherited from CustomBaseModel:

Class Variable model_config Undocumented
def get_target_config(self, target: Target) -> TargetConfig:

Returns the target configuration for the given target.

disable_onnx_optimization: bool =

Undocumented

disable_onnx_simplification: bool =

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hailo: HailoConfig =

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input_bin: Path | None =

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input_file_type: InputFileType =

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input_model: Path =

Undocumented

inputs: Annotated[list[InputConfig], Field(min_length=1)] =

Undocumented

intermediate_outputs_remote_url: str | None =

Undocumented

keep_intermediate_outputs: bool =

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output_remote_url: str | None =

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outputs: Annotated[list[OutputConfig], Field(min_length=1)] =

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put_file_plugin: str | None =

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rvc2: RVC2Config =

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rvc3: RVC3Config =

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rvc4: RVC4Config =

Undocumented

@model_validator(mode='before')
@classmethod
def _download_input_model(cls, value: dict[str, Any]) -> dict[str, Any]:

Resolve input model paths and normalize OpenVINO IR inputs.

@model_validator(mode='before')
@classmethod
def _validate_model(cls, data: dict[str, Any]) -> dict[str, Any]:

Expand top-level config shortcuts into explicit tensor config.

This fills in inferred metadata, default inputs and outputs, and propagates shared calibration and preprocessing settings down to per-input configuration.