code: def build_attention(config: Union[Dict[str, Any], AttentionConfig]):
      """Builds an attention from a config.
  
      This assumes a 'name' key in the config which is used to determine what
      attention class to instantiate. For instance, a config `{"name": "my_attention",
      "foo": "bar"}` will find a class that was registered as "my_attention"
      (see :func:`register_attention`) and call .from_config on it."""
  
      if not isinstance(config, AttentionConfig):
          try:
              config_instance = generate_matching_config(
                  config, ATTENTION_REGISTRY[config["name"]].config
              )
          except KeyError as e:
              name = config["name"]
              logger.warning(
                  f"{name} not available among {ATTENTION_REGISTRY.keys()}"
              )
              raise e
      else:
          config_instance = config
  
      return ATTENTION_REGISTRY[
          config_instance.name
      ].constructor.from_config(config_instance)
  
file_path: xformers/xformers/components/attention/__init__.py
imports: import logging
  from pathlib import Path
  from typing import Any, Callable, Dict, Set, Union
  import torch
  from xformers.utils import generate_matching_config, get_registry_decorator, import_all_modules
  from ._sputnik_sparse import SparseCS
  from .attention_mask import AttentionMask
  from .base import Attention, AttentionConfig
  from .favor import FavorAttention
  from .global_tokens import GlobalAttention
  from .linformer import LinformerAttention
  from .local import LocalAttention
  from .nystrom import NystromAttention
  from .ortho import OrthoFormerAttention
  from .random import RandomAttention
  from .scaled_dot_product import ScaledDotProduct
label_desc: Use image node_id 1 for calling a global function with example usage: build_attention(config) and returns: ATTENTION_REGISTRY