class_docstr: CoordConv layer as in the paper.
  
  MIT License
  Copyright (c) 2018 Walsvid
  
  Link to the paper: https://arxiv.org/abs/1807.03247
  Link to the PyTorch implementation: https://github.com/walsvid/CoordConv
class_docstr_tok: ["CoordConv","layer","as","in","the","paper",".","MIT","License","Copyright","(","c",")","2018","Walsvid","Link","to","the","paper",":","https",":","\/\/arxiv.org\/abs\/1807.03247","Link","to","the","PyTorch","implementation",":","https",":","\/\/github.com\/walsvid\/CoordConv"]
docstr: Forward pass.
  
  Args:
      input_tensor (Tensor): Input tensor.
  
  Returns:
      Tensor: Output tensor after applying the CoordConv layer.
docstr_tok: ["Forward","pass",".","Args",":","input_tensor","(","Tensor",")",":","Input","tensor",".","Returns",":","Tensor",":","Output","tensor","after","applying","the","CoordConv","layer","."]
code: def forward(
      self, input_tensor: Tensor
  ) -> Tensor:  # pylint: disable=arguments-renamed
      """Forward pass.
  
      Args:
          input_tensor (Tensor): Input tensor.
  
      Returns:
          Tensor: Output tensor after applying the CoordConv layer.
      """
      out = self.add_coords(input_tensor)
      out = self.conv2d(out)
      return out
  
imports: from __future__ import annotations
  import torch
  import torch.nn.functional
  import torchvision
  from einops import rearrange
  from sklearn.cluster import KMeans
  from torch import Tensor, nn
  from torch.fx.graph_module import GraphModule
  from torch.nn.common_types import _size_2_t
  from torch.utils.data import DataLoader
  from torchvision.models.feature_extraction import create_feature_extractor
  from tqdm import tqdm
  from anomalib.models.cfa.anomaly_map import AnomalyMapGenerator
  from anomalib.models.components import DynamicBufferModule
  from anomalib.models.components.feature_extractors import dryrun_find_featuremap_dims
label_desc: Use image node_id 2 for calling the CoordConv2d obj's underlying member method code with example usage: obj.forward(input_tensor) and returns: out