hubai_sdk.services.convert

module documentation

Undocumented

Function	`convert`	Starts the online conversion process.
Function	`Hailo`	Convert a model to Hailo format.
Function	`RVC2`	Convert a model to RVC2 format.
Function	`RVC3`	Convert a model to RVC3 format.
Function	`RVC4`	Convert a model to RVC4 format.
Function	`_combine_opts`	Merge generic options with target-prefixed conversion options.
Function	`_export`	Starts an export job for a model instance.
Function	`_get_instance_response`	Fetch a model instance response, returning `None` if missing.
Function	`_resolve_exported_instance`	Resolve the exported model instance from a completed export job.
Function	`_wait_for_exported_instance_ready`	Wait until an exported model instance is actually downloadable.

@telemetry_operation(OperationTelemetrySpec(operation_name=OperationName.CONVERT, operation_group=TelemetryGroup.CONVERSION, target_resource=TargetResource.CONVERSION))

Starts the online conversion process.

Parameters
target:`Target`	Target platform.
opts:`list[str] \| None`	Additional options for the conversion process.
path:`str`	Path to the model file, NN Archive, or configuration file.
name:`str \| None`	Model name. If not specified, the name is taken from the configuration file or the model file.
license_type:`License`	License type.
is_public:`bool \| None`	Whether the model is public (`True`), private (`False`), or team-scoped (`None`).
description_short:`str`	Short description of the model.
description:`str \| None`	Full description of the model.
architecture_id:`UUID \| str \| None`	Architecture ID.
tasks:`list[Task] \| None`	Tasks this model supports.
links:`list[str] \| None`	Links to related resources.
is_yolo:`bool`	Whether the model is a YOLO model.
model_id:`UUID \| str \| None`	ID of an existing model resource. If specified, that model is used instead of creating a new one.
variant_version:`str \| None`	Model version. If not specified, the version is auto-incremented from the latest version of the model. If no versions exist, the version is `"0.1.0"`.
variant_description:`str \| None`	Full description of the model variant.
repository_url:`str \| None`	URL of the repository.
commit_hash:`str \| None`	Commit hash.
quantization_mode:`QuantizationMode \| None`	Quantization mode to use during conversion. Must be one of `INT8_STANDARD`, `INT8_ACCURACY_FOCUSED`, `INT8_INT16_MIXED`, `INT8_INT16_MIXED_ACCURACY_FOCUSED`, or `FP16_STANDARD`. `INT8_STANDARD` is standard INT8 quantization with calibration for optimal performance and model size. `INT8_ACCURACY_FOCUSED` is INT8 quantization with calibration that may improve accuracy without reducing performance or increasing model size, depending on the model. `INT8_INT16_MIXED` uses 8-bit weights and 16-bit activations across all layers for improved numeric stability and accuracy at the cost of performance and model size. `INT8_INT16_MIXED_ACCURACY_FOCUSED` is a mixed INT8 and INT16 calibration-based mode that prioritizes accuracy over throughput. `FP16_STANDARD` is FP16 quantization without calibration for models that require higher accuracy and numeric stability at the cost of performance and model size.
domain:`str \| None`	Domain of the model.
variant_tags:`list[str] \| None`	Tags for the model variant.
variant_id:`UUID \| str \| None`	ID of an existing model version resource. If specified, that version is used instead of creating a new one.
quantization_data:`QuantizationData \| PathType \| None`	Data used to quantize this model. This can be a predefined domain (`DRIVING`, `FOOD`, `GENERAL`, `INDOORS`, `RANDOM`, `WAREHOUSE`, `CLIP`, `UNKNOWN`), a dataset ID, or a path to a local quantization `.zip` file. Pass the `.zip` path itself instead of `CUSTOM`; the SDK normalizes local zip inputs automatically.
max_quantization_images:`int \| None`	Maximum number of quantization images.
instance_tags:`list[str] \| None`	Tags for the model instance.
input_shape:`list[int] \| None`	Input shape for the model instance.
is_deployable:`bool \| None`	Whether the model instance is deployable.
output_dir:`str \| None`	Directory path for the downloaded files. If not specified, the downloader creates a directory named after the exported instance slug under the current working directory.
tool_version:`str \| None`	Version of the tool used for conversion. For RVC2 and RVC3 this is the IR version, while for RVC4 this is the SNPE version.
yolo_input_shape:`list[int] \| None`	Input shape for YOLO models.
yolo_version:`YoloVersion \| None`	YOLO version.
yolo_class_names:`list[str] \| None`	Class names for YOLO models.

Returns
`ConvertResponse`	Conversion result containing the downloaded output path, export job, and exported model instance.

def Hailo(path: PathType, optimization_level: Literal[-100, 0, 1, 2, 3, 4] = 2, compression_level: Literal[0, 1, 2, 3, 4, 5] = 2, batch_size: int = 8, alls: list[str] | None = None, opts: Kwargs | list[str] | None = None, **hub_kwargs) -> ConvertResponse: ¶

Convert a model to Hailo format.

Parameters
path:`PathType`	Path to the model file to convert.
optimization_level:`Literal[-100, 0, 1, 2, 3, 4]`	Optimization level for the conversion.
compression_level:`Literal[0, 1, 2, 3, 4, 5]`	Compression level for the conversion.
batch_size:`int`	Batch size for the conversion.
alls:`list[str] \| None`	`alls` parameters for the conversion.
opts:`Kwargs \| list[str] \| None`	Additional conversion options. These can override config values.
name	Model name. If not specified, the name is taken from the configuration file or the model file.
license_type	License type.
is_public	Whether the model is public (`True`), private (`False`), or team-scoped (`None`).
description_short	Short description of the model.
description	Full description of the model.
architecture_id	Architecture ID.
tasks	Tasks this model supports.
links	Links to related resources.
is_yolo	Whether the model is a YOLO model.
model_id	ID of an existing model resource. If specified, that model is used instead of creating a new one.
variant_version	Model version. If not specified, the version is auto-incremented from the latest version of the model. If no versions exist, the version is `"0.1.0"`.
variant_description	Full description of the model variant.
repository_url	URL of the repository.
commit_hash	Commit hash.
quantization_mode	Quantization mode.
quantization_data	Data used to quantize this model. This can be a predefined domain (`DRIVING`, `FOOD`, `GENERAL`, `INDOORS`, `RANDOM`, `WAREHOUSE`, `CLIP`, `UNKNOWN`), a dataset ID, or a path to a local quantization `.zip` file.
max_quantization_images	Maximum number of quantization images.
domain	Domain of the model.
variant_tags	Tags for the model variant.
variant_id	ID of an existing model version resource. If specified, that version is used instead of creating a new one.
input_shape	Input shape for the model instance.
is_deployable	Whether the model instance is deployable.
output_dir	Directory path for the downloaded files. If not specified, the downloader creates a directory named after the exported instance slug under the current working directory.
tool_version	Version of the tool used for conversion. For RVC2 and RVC3 this is the IR version, while for RVC4 this is the SNPE version.
yolo_input_shape	Input shape for YOLO models.
yolo_version	YOLO version.
yolo_class_names	Class names for YOLO models.
**hub_kwargs	Additional keyword arguments passed to `convert`.

Returns
`ConvertResponse`	Conversion result containing the downloaded output path, export job, and exported model instance.

def RVC2(path: PathType, mo_args: list[str] | None = None, compile_tool_args: list[str] | None = None, compress_to_fp16: bool = True, number_of_shaves: int = 8, superblob: bool = True, opts: Kwargs | list[str] | None = None, **hub_kwargs) -> ConvertResponse: ¶

Convert a model to RVC2 format.

Parameters
path:`PathType`	Path to the model file to convert.
mo_args:`list[str] \| None`	Additional arguments for the Model Optimizer.
compile_tool_args:`list[str] \| None`	Additional arguments for the compile tool.
compress_to_fp16:`bool`	Whether to compress the model weights to FP16.
number_of_shaves:`int`	Number of shaves to use for the conversion.
superblob:`bool`	Whether to create a superblob for the model.
opts:`Kwargs \| list[str] \| None`	Additional conversion options. These can override config values.
name	Model name. If not specified, the name is taken from the configuration file or the model file.
license_type	License type.
is_public	Whether the model is public (`True`), private (`False`), or team-scoped (`None`).
description_short	Short description of the model.
description	Full description of the model.
architecture_id	Architecture ID.
tasks	Tasks this model supports.
links	Links to related resources.
is_yolo	Whether the model is a YOLO model.
model_id	ID of an existing model resource. If specified, that model is used instead of creating a new one.
variant_version	Model version. If not specified, the version is auto-incremented from the latest version of the model. If no versions exist, the version is `"0.1.0"`.
variant_description	Full description of the model variant.
repository_url	URL of the repository.
commit_hash	Commit hash.
domain	Domain of the model.
variant_tags	Tags for the model variant.
variant_id	ID of an existing model version resource. If specified, that version is used instead of creating a new one.
input_shape	Input shape for the model instance.
is_deployable	Whether the model instance is deployable.
output_dir	Directory path for the downloaded files. If not specified, the downloader creates a directory named after the exported instance slug under the current working directory.
tool_version	Version of the tool used for conversion. For RVC2 and RVC3 this is the IR version, while for RVC4 this is the SNPE version.
yolo_input_shape	Input shape for YOLO models.
yolo_version	YOLO version.
yolo_class_names	Class names for YOLO models.
**hub_kwargs	Additional keyword arguments passed to `convert`.

Returns
`ConvertResponse`	Conversion result containing the downloaded output path, export job, and exported model instance.

def RVC3(path: PathType, mo_args: list[str] | None = None, compile_tool_args: list[str] | None = None, compress_to_fp16: bool = True, pot_target_device: PotDevice | Literal['VPU', 'ANY'] = PotDevice.VPU, opts: Kwargs | list[str] | None = None, **hub_kwargs) -> ConvertResponse: ¶

Convert a model to RVC3 format.

Parameters
path:`PathType`	Path to the model file to convert.
mo_args:`list[str] \| None`	Additional arguments for the Model Optimizer.
compile_tool_args:`list[str] \| None`	Additional arguments for the compile tool.
compress_to_fp16:`bool`	Whether to compress the model weights to FP16.
pot_target_device:`PotDevice \| Literal['VPU', 'ANY']`	Target device for POT quantization.
opts:`Kwargs \| list[str] \| None`	Additional conversion options. These can override config values.
name	Model name. If not specified, the name is taken from the configuration file or the model file.
license_type	License type.
is_public	Whether the model is public (`True`), private (`False`), or team-scoped (`None`).
description_short	Short description of the model.
description	Full description of the model.
architecture_id	Architecture ID.
tasks	Tasks this model supports.
links	Links to related resources.
is_yolo	Whether the model is a YOLO model.
model_id	ID of an existing model resource. If specified, that model is used instead of creating a new one.
variant_version	Model version. If not specified, the version is auto-incremented from the latest version of the model. If no versions exist, the version is `"0.1.0"`.
variant_description	Full description of the model variant.
repository_url	URL of the repository.
commit_hash	Commit hash.
domain	Domain of the model.
variant_tags	Tags for the model variant.
variant_id	ID of an existing model version resource. If specified, that version is used instead of creating a new one.
input_shape	Input shape for the model instance.
is_deployable	Whether the model instance is deployable.
output_dir	Directory path for the downloaded files. If not specified, the downloader creates a directory named after the exported instance slug under the current working directory.
tool_version	Version of the tool used for conversion. For RVC2 and RVC3 this is the IR version, while for RVC4 this is the SNPE version.
yolo_input_shape	Input shape for YOLO models.
yolo_version	YOLO version.
yolo_class_names	Class names for YOLO models.
**hub_kwargs	Additional keyword arguments passed to `convert`.

Returns
`ConvertResponse`	Conversion result containing the downloaded output path, export job, and exported model instance.

def RVC4(path: PathType, snpe_onnx_to_dlc_args: list[str] | None = None, snpe_dlc_quant_args: list[str] | None = None, snpe_dlc_graph_prepare_args: list[str] | None = None, use_per_channel_quantization: bool = True, use_per_row_quantization: bool = False, htp_socs: list[Literal['sm8350', 'sm8450', 'sm8550', 'sm8650', 'qcs6490', 'qcs8550']] | None = None, opts: Kwargs | list[str] | None = None, **hub_kwargs) -> ConvertResponse: ¶

Convert a model to RVC4 format.

Parameters
path:`PathType`	Path to the model file to convert.
snpe_onnx_to_dlc_args:`list[str] \| None`	Additional arguments for the SNPE ONNX to DLC conversion.
snpe_dlc_quant_args:`list[str] \| None`	Additional arguments for SNPE DLC quantization.
snpe_dlc_graph_prepare_args:`list[str] \| None`	Additional arguments for SNPE DLC graph preparation.
use_per_channel_quantization:`bool`	Whether to use per-channel quantization.
use_per_row_quantization:`bool`	Whether to use per-row quantization.
htp_socs:`list[Literal['sm8350', 'sm8450', 'sm8550', 'sm8650', 'qcs6490', 'qcs8550']] \| None`	HTP SoCs for the final DLC graph.
opts:`Kwargs \| list[str] \| None`	Additional conversion options. These can override config values.
name	Model name. If not specified, the name is taken from the configuration file or the model file.
license_type	License type.
is_public	Whether the model is public (`True`), private (`False`), or team-scoped (`None`).
description_short	Short description of the model.
description	Full description of the model.
architecture_id	Architecture ID.
tasks	Tasks this model supports.
links	Links to related resources.
is_yolo	Whether the model is a YOLO model.
model_id	ID of an existing model resource. If specified, that model is used instead of creating a new one.
variant_version	Model version. If not specified, the version is auto-incremented from the latest version of the model. If no versions exist, the version is `"0.1.0"`.
variant_description	Full description of the model variant.
repository_url	URL of the repository.
commit_hash	Commit hash.
quantization_mode	Quantization mode to use during conversion. Must be one of `INT8_STANDARD`, `INT8_ACCURACY_FOCUSED`, `INT8_INT16_MIXED`, `INT8_INT16_MIXED_ACCURACY_FOCUSED`, or `FP16_STANDARD`. `INT8_STANDARD` is standard INT8 quantization with calibration for optimal performance and model size. `INT8_ACCURACY_FOCUSED` is INT8 quantization with calibration that may improve accuracy without reducing performance or increasing model size, depending on the model. `INT8_INT16_MIXED` uses 8-bit weights and 16-bit activations across all layers for improved numeric stability and accuracy at the cost of performance and model size. `INT8_INT16_MIXED_ACCURACY_FOCUSED` is a mixed INT8 and INT16 calibration-based mode that prioritizes accuracy over throughput. `FP16_STANDARD` is FP16 quantization without calibration for models that require higher accuracy and numeric stability at the cost of performance and model size.
domain	Domain of the model.
variant_tags	Tags for the model variant.
variant_id	ID of an existing model version resource. If specified, that version is used instead of creating a new one.
quantization_data	Data used to quantize this model. This can be a predefined domain (`DRIVING`, `FOOD`, `GENERAL`, `INDOORS`, `RANDOM`, `WAREHOUSE`, `CLIP`, `UNKNOWN`), a dataset ID, or a path to a local quantization `.zip` file. Pass the `.zip` path itself instead of `CUSTOM`; the SDK normalizes local zip inputs automatically.
max_quantization_images	Maximum number of quantization images.
input_shape	Input shape for the model instance.
is_deployable	Whether the model instance is deployable.
output_dir	Directory path for the downloaded files. If not specified, the downloader creates a directory named after the exported instance slug under the current working directory.
tool_version	Version of the tool used for conversion. For RVC2 and RVC3 this is the IR version, while for RVC4 this is the SNPE version.
yolo_input_shape	Input shape for YOLO models.
yolo_version	YOLO version.
yolo_class_names	Class names for YOLO models.
**hub_kwargs	Additional keyword arguments passed to `convert`.

Returns
`ConvertResponse`	Conversion result containing the downloaded output path, export job, and exported model instance.

def _combine_opts(target: Target, target_kwargs: Kwargs, opts: list[str] | Kwargs | None) -> list[str]: ¶

Merge generic options with target-prefixed conversion options.

Returns
`list[str]`	A flat option list ready for config parsing.

def _export(name: str, identifier: UUID | str, target: Target, quantization_mode: QuantizationMode | None, quantization_data: str | None, max_quantization_images: int | None = None, yolo_version: str | None = None, yolo_class_names: list[str] | None = None, **kwargs) -> JobMessageResponse: ¶

Starts an export job for a model instance.

Returns
`JobMessageResponse`	The created export job response.

def _get_instance_response(instance_id: str) -> ModelInstanceResponse | None: ¶

Fetch a model instance response, returning None if missing.

Returns
`ModelInstanceResponse \| None`	The model instance response, or `None` if the instance does not exist yet.

def _resolve_exported_instance(job: JobMessageResponse) -> ModelInstanceResponse: ¶

Resolve the exported model instance from a completed export job.

Returns
`ModelInstanceResponse`	The exported model instance once it is ready to download.

def _wait_for_exported_instance_ready(instance_id: str, *, timeout_seconds: int = 180, poll_interval_seconds: int = 2) -> ModelInstanceResponse: ¶

Wait until an exported model instance is actually downloadable.

Returns
`ModelInstanceResponse`	The exported model instance once it becomes downloadable.