code: def _local_2d_distance(H, W, p=2.0):
      # axial is a special case with p=0 and distance=2
      i, j = _generate_2d_grid(H, W)
      ij = torch.stack([i.flatten(), j.flatten()], 1).float()
      d = torch.cdist(ij, ij, p=p)
      return d
  
imports: import itertools
  import pytest
  import torch
  import xformers.components.attention.attention_patterns
  from xformers.components.attention.sparsity_config import BigBirdSparsityConfig, BSLongformerSparsityConfig, DenseSparsityConfig, FixedSparsityConfig, VariableSparsityConfig
label_desc: Use image node_id 5 for calling a global function with example usage: _local_2d_distance(H, W, p) and returns: d