docstr: Differentiable quantization function
docstr_tok: ["Differentiable","quantization","function"]
code: def quantize(cls, base, itype=int4, axis=None):
      """Differentiable quantization function"""
      return AffineQuantizer.apply(base, itype, axis)
  
imports: from dataclasses import dataclass
  from typing import Optional
  import torch
  from torch.autograd import Function
  from torch.utils import _pytree
label_desc: Use image node_id 4 for calling the QBitsTensor obj's underlying member method code with example usage: obj.quantize(cls, base, itype, axis) and returns: AffineQuantizer