Function from_dlpack

numpy/core/src/multiarray/dlpack.c:289–434

}

NPY_NO_EXPORT PyObject *
from_dlpack(PyObject *NPY_UNUSED(self), PyObject *obj) {
    PyObject *capsule = PyObject_CallMethod((PyObject *)obj->ob_type,
            "__dlpack__", "O", obj);
    if (capsule == NULL) {
        return NULL;
    }

    DLManagedTensor *managed =
        (DLManagedTensor *)PyCapsule_GetPointer(capsule,
        NPY_DLPACK_CAPSULE_NAME);

    if (managed == NULL) {
        Py_DECREF(capsule);
        return NULL;
    }

    const int ndim = managed->dl_tensor.ndim;
    if (ndim > NPY_MAXDIMS) {
        PyErr_SetString(PyExc_RuntimeError,
                "maxdims of DLPack tensor is higher than the supported "
                "maxdims.");
        Py_DECREF(capsule);
        return NULL;
    }

    DLDeviceType device_type = managed->dl_tensor.device.device_type;
    if (device_type != kDLCPU &&
            device_type != kDLCUDAHost &&
            device_type != kDLROCMHost &&
            device_type != kDLCUDAManaged) {
        PyErr_SetString(PyExc_RuntimeError,
                "Unsupported device in DLTensor.");
        Py_DECREF(capsule);
        return NULL;
    }

    if (managed->dl_tensor.dtype.lanes != 1) {
        PyErr_SetString(PyExc_RuntimeError,
                "Unsupported lanes in DLTensor dtype.");
        Py_DECREF(capsule);
        return NULL;
    }

    int typenum = -1;
    const uint8_t bits = managed->dl_tensor.dtype.bits;
    const npy_intp itemsize = bits / 8;
    switch (managed->dl_tensor.dtype.code) {
    case kDLBool:
        if (bits == 8) {
            typenum = NPY_BOOL;
        }
        break;
    case kDLInt:
        switch (bits)
        {
            case 8: typenum = NPY_INT8; break;
            case 16: typenum = NPY_INT16; break;