ml_switcheroo.frameworks.numpy

Numpy Framework Adapter.

Refactor: Definitions populated for NumPy specific Ops.

Classes

NumpyAdapter

Adapter for generic NumPy.

Module Contents

class ml_switcheroo.frameworks.numpy.NumpyAdapter

Adapter for generic NumPy.

display_name: str = 'NumPy'

inherits_from: str | None = None

ui_priority: int = 20

property search_modules: List[str]

property import_alias: Tuple[str, str]

property import_namespaces: Dict[str, Dict[str, str]]

property discovery_heuristics: Dict[str, List[str]]

property test_config: Dict[str, str]

Test templates for NumPy.

property supported_tiers: List[ml_switcheroo.enums.SemanticTier]

property structural_traits: ml_switcheroo.frameworks.base.StructuralTraits

property definitions: Dict[str, ml_switcheroo.frameworks.base.StandardMap]

property rng_seed_methods: List[str]

collect_api(category: ml_switcheroo.frameworks.base.StandardCategory) → List[ml_switcheroo.core.ghost.GhostRef]

classmethod get_example_code() → str

Returns the primary example code used for instant demos.

get_tiered_examples() → Dict[str, str]

Returns NumPy idiomatic examples.

get_device_syntax(device_type: str, device_index: str | None = None) → str

get_serialization_imports() → List[str]

get_serialization_syntax(op: str, file_arg: str, object_arg: str | None = None) → str

apply_wiring(snapshot: Dict[str, Any]) → None

convert(data)