code: def optimize_bsr_dense_addmm(
      m,
      k,
      n,
      bm,
      bk,
      beta=1,
      alpha=1,
      dtype=torch.float16,
      device="cuda",
      sparsity=0.5,
      force=False,
      verbose=False,
  ):
      torch.manual_seed(0)
      bsr = create_blocked_tensor(
          0, m, k, (bm, bk), sparsity, dtype, device
      ).to_sparse_bsr((bm, bk))
      dense = make_tensor(k, n, dtype=dtype, device=device)
      input = make_tensor(m, n, dtype=dtype, device=device)
      tune_bsr_dense_addmm(
          input,
          bsr,
          dense,
          beta=beta,
          alpha=alpha,
          store=True,
          force=force,
          verbose=verbose,
      )
  
file_path: pytorch/torch/sparse/_triton_ops_meta.py
imports: import inspect
  import itertools
  import re
  import warnings
  from typing import Any, Dict
  import torch
  from torch.hub import tqdm
  from torch.testing import make_tensor
label_desc: Use image node_id 8 for calling a global function with example usage: optimize_bsr_dense_addmm(m, k, n, bm, bk, beta, alpha, dtype, device, sparsity, force, verbose) without return types