code: def quantize_numpy(weight, scale, zero_point, out_dtype_np):
      iinfo = np.iinfo(out_dtype_np)
      clip_min = iinfo.min
      clip_max = iinfo.max
      if len(scale.shape) > 0:
          scale = np.reshape(
              scale, [weight.shape[0]] + [1] * (len(weight.shape) - 1)
          )
      transformed = zero_point + weight / scale
      return np.clip(np.round(transformed), clip_min, clip_max).astype(
          out_dtype_np
      )
  
imports: import numpy
  import tvm
  from tvm import relay
  from tvm.relay import expr
  from tvm.relay import op
  from tvm.relay.frontend.common import infer_shape
  from .common import logger
  from .pytorch_utils import is_version_greater_than
label_desc: Use image node_id 5 for calling a global function with example usage: quantize_numpy(weight, scale, zero_point, out_dtype_np) and returns: np