pixano_inference.configs.sam2

Typed model params for SAM2 models.

Sam2ImageParams(**data)

Bases: BaseModelParams

Typed parameters for Sam2ImageModel.

Attributes:

Name	Type	Description
path	str	HuggingFace model ID or local checkpoint path.
torch_dtype	Literal['float32', 'float16', 'bfloat16']	Torch dtype for autocast.
compile	bool	Whether to torch.compile the model.

Source code in pydantic/main.py

def __init__(self, /, **data: Any) -> None:
    """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.
    """
    # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks
    __tracebackhide__ = True
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
    if self is not validated_self:
        warnings.warn(
            'A custom validator is returning a value other than `self`.\n'
            "Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.\n"
            'See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.',
            stacklevel=2,
        )

Sam2VideoParams(**data)

Bases: BaseModelParams

Typed parameters for Sam2VideoModel.

Attributes:

Name	Type	Description
path	str	HuggingFace model ID or local checkpoint path.
torch_dtype	Literal['float32', 'float16', 'bfloat16']	Torch dtype for autocast.
compile	bool	Whether to torch.compile the model.
vos_optimized	bool	Use VOS-optimised predictor.
propagate	bool	Whether to propagate masks across the full video.

Source code in pydantic/main.py

def __init__(self, /, **data: Any) -> None:
    """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.
    """
    # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks
    __tracebackhide__ = True
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
    if self is not validated_self:
        warnings.warn(
            'A custom validator is returning a value other than `self`.\n'
            "Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.\n"
            'See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.',
            stacklevel=2,
        )