code: def addmm_replace(
      input: Optional[Tensor],
      mat1: Tensor,
      mat2: Tensor,
      beta=1.0,
      alpha=1.0,
  ) -> Tensor:
      m_padded_length = get_padded_length(
          mat1.shape[0], get_alignment_size(mat1)
      )
      k_padded_length = get_padded_length(
          mat1.shape[1], get_alignment_size(mat1)
      )
      n_padded_length = get_padded_length(
          mat2.shape[1], get_alignment_size(mat2)
      )
  
      if (
          m_padded_length != 0
          or k_padded_length != 0
          or n_padded_length != 0
      ):
          return pad_addmm(
              input,
              mat1,
              mat2,
              m_padded_length,
              k_padded_length,
              n_padded_length,
              beta,
              alpha,
          )
  
      return aten.addmm(input, mat1, mat2, beta=beta, alpha=alpha)
  
imports: import functools
  from typing import List, Optional
  import torch
  from torch import Tensor
  from torch._inductor import utils
  from torch.utils._mode_utils import no_dispatch
  from torch.utils._triton import has_triton
  from ..pattern_matcher import fwd_only, joint_fwd_bwd, Match, register_replacement
label_desc: Use image node_id 11 for calling a global function with example usage: addmm_replace(input, mat1, mat2, beta, alpha) and returns: aten, pad_addmm