code: def sample_step_core(
      self,
      image: Tensor,
      cond: Optional[cond_type],
      step: int,
      total_step: int,
      get_denoised: IGetDenoised,
      *,
      quantize: bool,
      unconditional_cond: Optional[Any],
      unconditional_guidance_scale: float,
      **kwargs: Any,
  ) -> Tensor:
      pass
  
imports: import torch
  import numpy
  from abc import abstractmethod
  from abc import ABCMeta
  from torch import Tensor
  from typing import Any
  from typing import Dict
  from typing import List
  from typing import Tuple
  from typing import Optional
  from typing import Protocol
  from .utils import append_dims
  from .utils import append_zero
  from .schema import ISampler
  from .schema import IQSampler
  from .schema import IDiffusion
  from .schema import UncondSamplerMixin
  from ..utils import cond_type
  from ..utils import extract_to
label_desc: Use image node_id 2 for calling the IKSampler obj's underlying member method code with example usage: obj.sample_step_core(image, cond, step, total_step, get_denoised) without return types