qualia_codegen_core.DataConverter module

class qualia_codegen_core.DataConverter.DataConverter

Bases: object

dtype2ctype: Final[dict[DTypeLike, str]] = {<class 'numpy.float16'>: 'float', <class 'numpy.float32'>: 'float', <class 'numpy.float64'>: 'float', <class 'numpy.int16'>: 'int16_t', <class 'numpy.int32'>: 'int32_t', <class 'numpy.int64'>: 'int64_t', <class 'numpy.int8'>: 'int8_t', <class 'numpy.uint16'>: 'uint16_t', <class 'numpy.uint32'>: 'uint32_t', <class 'numpy.uint64'>: 'uint64_t', <class 'numpy.uint8'>: 'uint8_t'}

qtype2ctype(number_type: type[int | float], width: int) → str

ndarray2cinitializer(arr: NDArrayFloatOrInt) → str

tensor2carray(arr: NDArrayFloatOrInt, name: str) → dict[str, str | tuple[int, ...]]