code: def squared_euclidean_distance(a, b):
      b = b.T
      a2 = np.sum(np.square(a), axis=1)
      b2 = np.sum(np.square(b), axis=0)
      ab = np.matmul(a, b)
      d = a2[:, None] - 2 * ab + b2[None, :]
      return d
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/imagegpt/feature_extraction_imagegpt.py
imports: from typing import List, Optional, Union
  import numpy
  from PIL import Image
  from transformers.image_utils import PILImageResampling
  from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
  from ...image_utils import ImageFeatureExtractionMixin, is_torch_tensor
  from ...utils import TensorType, logging
label_desc: Use image node_id 1 for calling a global function with example usage: squared_euclidean_distance(a, b) and returns: d