# type: ignore from . import device from . import hint from . import intel_auto from . import intel_cpu from . import intel_gpu from . import intel_npu from . import log from . import streams from __future__ import annotations import openvino._pyopenvino import typing """ openvino.properties submodule """ __all__ = ['CacheMode', 'WorkloadType', 'auto_batch_timeout', 'available_devices', 'cache_dir', 'cache_encryption_callbacks', 'cache_mode', 'compilation_num_threads', 'device', 'enable_mmap', 'enable_profiling', 'execution_devices', 'force_tbb_terminate', 'hint', 'inference_num_threads', 'intel_auto', 'intel_cpu', 'intel_gpu', 'intel_npu', 'key_cache_group_size', 'key_cache_precision', 'loaded_from_cache', 'log', 'max_batch_size', 'model_name', 'num_streams', 'optimal_batch_size', 'optimal_number_of_infer_requests', 'range_for_async_infer_requests', 'range_for_streams', 'streams', 'supported_properties', 'value_cache_group_size', 'value_cache_precision', 'weights_path', 'workload_type'] class CacheMode: """ Members: OPTIMIZE_SIZE OPTIMIZE_SPEED """ OPTIMIZE_SIZE: typing.ClassVar[CacheMode] # value = OPTIMIZE_SPEED: typing.ClassVar[CacheMode] # value = __members__: typing.ClassVar[dict[str, CacheMode]] # value = {'OPTIMIZE_SIZE': , 'OPTIMIZE_SPEED': } def __eq__(self, other: typing.Any) -> bool: ... def __ge__(self, other: typing.Any) -> bool: ... def __getstate__(self) -> int: ... def __gt__(self, other: typing.Any) -> bool: ... def __hash__(self) -> int: ... def __index__(self) -> int: ... def __init__(self, value: typing.SupportsInt) -> None: ... def __int__(self) -> int: ... def __le__(self, other: typing.Any) -> bool: ... def __lt__(self, other: typing.Any) -> bool: ... def __ne__(self, other: typing.Any) -> bool: ... def __repr__(self) -> str: ... def __setstate__(self, state: typing.SupportsInt) -> None: ... def __str__(self) -> str: ... @property def name(self) -> str: ... @property def value(self) -> int: ... class WorkloadType: """ Members: DEFAULT EFFICIENT """ DEFAULT: typing.ClassVar[WorkloadType] # value = EFFICIENT: typing.ClassVar[WorkloadType] # value = __members__: typing.ClassVar[dict[str, WorkloadType]] # value = {'DEFAULT': , 'EFFICIENT': } def __eq__(self, other: typing.Any) -> bool: ... def __ge__(self, other: typing.Any) -> bool: ... def __getstate__(self) -> int: ... def __gt__(self, other: typing.Any) -> bool: ... def __hash__(self) -> int: ... def __index__(self) -> int: ... def __init__(self, value: typing.SupportsInt) -> None: ... def __int__(self) -> int: ... def __le__(self, other: typing.Any) -> bool: ... def __lt__(self, other: typing.Any) -> bool: ... def __ne__(self, other: typing.Any) -> bool: ... def __repr__(self) -> str: ... def __setstate__(self, state: typing.SupportsInt) -> None: ... def __str__(self) -> str: ... @property def name(self) -> str: ... @property def value(self) -> int: ... @typing.overload def auto_batch_timeout() -> str: ... @typing.overload def auto_batch_timeout(arg0: typing.SupportsInt) -> tuple[str, openvino._pyopenvino.OVAny]: ... def available_devices() -> str: ... @typing.overload def cache_dir() -> str: ... @typing.overload def cache_dir(arg0: str) -> tuple[str, openvino._pyopenvino.OVAny]: ... def cache_encryption_callbacks(arg0: typing.Any) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def cache_mode() -> str: ... @typing.overload def cache_mode(arg0: CacheMode) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def compilation_num_threads() -> str: ... @typing.overload def compilation_num_threads(arg0: typing.SupportsInt) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def enable_mmap() -> str: ... @typing.overload def enable_mmap(arg0: bool) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def enable_profiling() -> str: ... @typing.overload def enable_profiling(arg0: bool) -> tuple[str, openvino._pyopenvino.OVAny]: ... def execution_devices() -> str: ... @typing.overload def force_tbb_terminate() -> str: ... @typing.overload def force_tbb_terminate(arg0: bool) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def inference_num_threads() -> str: ... @typing.overload def inference_num_threads(arg0: typing.SupportsInt) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def key_cache_group_size() -> str: ... @typing.overload def key_cache_group_size(arg0: typing.SupportsInt) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def key_cache_precision() -> str: ... @typing.overload def key_cache_precision(arg0: openvino._pyopenvino.Type) -> tuple[str, openvino._pyopenvino.OVAny]: ... def loaded_from_cache() -> str: ... def max_batch_size() -> str: ... def model_name() -> str: ... @typing.overload def num_streams() -> str: ... @typing.overload def num_streams(arg0: typing.Any) -> tuple[str, openvino._pyopenvino.OVAny]: ... def optimal_batch_size() -> str: ... def optimal_number_of_infer_requests() -> str: ... def range_for_async_infer_requests() -> str: ... def range_for_streams() -> str: ... def supported_properties() -> str: ... @typing.overload def value_cache_group_size() -> str: ... @typing.overload def value_cache_group_size(arg0: typing.SupportsInt) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def value_cache_precision() -> str: ... @typing.overload def value_cache_precision(arg0: openvino._pyopenvino.Type) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def weights_path() -> str: ... @typing.overload def weights_path(arg0: str) -> tuple[str, openvino._pyopenvino.OVAny]: ... @typing.overload def workload_type() -> str: ... @typing.overload def workload_type(arg0: WorkloadType) -> tuple[str, openvino._pyopenvino.OVAny]: ...