docstr: Compute Image-Level Anomaly Score for one nearest_neighbor distance map.
          
docstr_tok: ["Compute","Image-Level","Anomaly","Score","for","one","nearest_neighbor","distance","map","."]
code: def compute_image_anomaly_score(distance):
      """Compute Image-Level Anomaly Score for one nearest_neighbor distance map."""
      # distances[n_neighbors, B, HW]
      max_scores = paddle.argmax(distance[0, :])
      confidence = distance[
          :, max_scores
      ]  # paddle.index_select(distances, max_scores, -1)
      weights = 1 - (
          paddle.max(paddle.exp(confidence))
          / paddle.sum(paddle.exp(confidence))
      )
      score = weights * paddle.max(distance[0, :])
      return score.item()
  
imports: import numpy
  from tqdm import tqdm
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.vision.models.resnet import resnet18, resnet50, wide_resnet50_2
  from scipy.ndimage import gaussian_filter
  from qinspector.cvlib.workspace import register
  from qinspector.uad.utils.utils import cdist, cholesky_inverse, mahalanobis, mahalanobis_einsum, orthogonal, svd_orthogonal
  from qinspector.uad.utils.k_center_greedy import KCenterGreedy
label_desc: Use image node_id 13 for calling the PatchCore obj's underlying member method code with example usage: obj.compute_image_anomaly_score(distance) and returns: score