code: def _infer(model, img):
      img = img.permute((2, 0, 1))
      img = img / 255.0
      img = img - bias.reshape((1, -1, 1, 1))
      img = img / scale.reshape((1, -1, 1, 1))
      return model.forward(img).realize()
  
file_path: tinygrad/examples/efficientnet.py
imports: import sys
  import ast
  import time
  import numpy
  from PIL import Image
  from tinygrad.tensor import Tensor
  from tinygrad.helpers import getenv, fetch, Timing
  from tinygrad.jit import TinyJit
  from extra.models.efficientnet import EfficientNet
label_desc: Use image node_id 1 for calling a global function with example usage: _infer(model, img) and returns: model