class_docstr: Generate Anomaly Heatmap and segmentation.
class_docstr_tok: ["Generate","Anomaly","Heatmap","and","segmentation","."]
code: def __init__(self, input_size: ListConfig | tuple) -> None:
      super().__init__()
      self.input_size = (
          input_size
          if isinstance(input_size, tuple)
          else tuple(input_size)
      )
  
file_path: anomalib/src/anomalib/models/uflow/anomaly_map.py
imports: from __future__ import annotations
  from typing import List
  import numpy
  import scipy.stats
  import torch
  import torch.nn.functional
  from mpmath import binomial, mp
  from omegaconf import ListConfig
  from scipy import integrate
  from torch import Tensor, nn
label_desc: Use image node_id 1 to create a new AnomalyMapGenerator object from inherited base classes: nn with example: obj = AnomalyMapGenerator(input_size)