code: def check_sdpa_support_list():
      with open(
          os.path.join(
              REPO_PATH, "docs/source/en/perf_infer_gpu_one.md"
          ),
          "r",
      ) as f:
          doctext = f.read()
  
          doctext = doctext.split(
              "For now, Transformers supports SDPA inference and training for the following architectures:"
          )[1]
          doctext = doctext.split(
              "Note that FlashAttention can only be used for models using the"
          )[0]
  
      patterns = glob(
          os.path.join(
              REPO_PATH, "src/transformers/models/**/modeling_*.py"
          )
      )
      patterns_tf = glob(
          os.path.join(
              REPO_PATH, "src/transformers/models/**/modeling_tf_*.py"
          )
      )
      patterns_flax = glob(
          os.path.join(
              REPO_PATH, "src/transformers/models/**/modeling_flax_*.py"
          )
      )
      patterns = list(
          set(patterns) - set(patterns_tf) - set(patterns_flax)
      )
      archs_supporting_sdpa = []
      for filename in patterns:
          with open(filename, "r") as f:
              text = f.read()
  
              if "_supports_sdpa = True" in text:
                  model_name = (
                      os.path.basename(filename)
                      .replace(".py", "")
                      .replace("modeling_", "")
                  )
                  archs_supporting_sdpa.append(model_name)
  
      for arch in archs_supporting_sdpa:
          if arch not in doctext:
              raise ValueError(
                  f"{arch} should be in listed in the SDPA documentation but is not. Please update the documentation."
              )
  
imports: import os
  from glob import glob
label_desc: Use image node_id 2 for calling a global function with example usage: check_sdpa_support_list() without return types