class_docstr: Feature extractor based on ResNet (or others) backbones.
class_docstr_tok: ["Feature","extractor","based","on","ResNet","(","or","others",")","backbones","."]
code: def normalize_features(self, features, **kwargs):
      return [
          self.feature_normalizations[i](feature)
          for i, feature in enumerate(features)
      ]
  
file_path: anomalib/src/anomalib/models/uflow/feature_extraction.py
imports: from typing import Tuple
  import timm
  import torch
  import torch.nn.functional
  from torch import nn
  from anomalib.models.components.feature_extractors import TimmFeatureExtractor
label_desc: Use image node_id 4 for calling the FeatureExtractor obj's underlying member method code with example usage: obj.normalize_features(features) and returns: unknown