code: def matmul_blas_common(
      cfg,
      tensor_a,
      tensor_b,
      bias,
      out_dtype,
      transpose_a,
      transpose_b,
      lib,
  ):
      """Compute matmul/dense using a BLAS library"""
      M, K = get_const_tuple(tensor_a.shape)
      N, _ = get_const_tuple(tensor_b.shape)
      if (
          isinstance(M, int)
          and isinstance(K, int)
          and isinstance(N, int)
      ):
          cfg.add_flop(M * K * N * 2)
      if (
          tensor_a.dtype == "uint8"
          and tensor_b.dtype == "int8"
          and out_dtype == "int32"
      ):
          if not hasattr(lib, "matmul_u8s8s32"):
              raise NotImplementedError(
                  f"Matmul/Dense with {lib.__name__} for {tensor_a.dtype} is not supported "
                  "(matmulu8s8s32 not imlemented)"
              )
          C = lib.matmul_u8s8s32(
              tensor_a,
              tensor_b,
              transpose_a,
              transpose_b,
              dtype=out_dtype,
          )
      elif tensor_a.dtype == "float32" or tensor_a.dtype == "float64":
          C = lib.matmul(tensor_a, tensor_b, transpose_a, transpose_b)
      else:
          raise NotImplementedError(
              f"Matmul/Dense with {lib.__name__} for {tensor_a.dtype} is not supported"
          )
  
      if bias is not None:
          C = te.compute(
              C.shape,
              lambda i, j: C[i, j] + bias[j].astype(out_dtype),
              tag=tag.BROADCAST,
          )
      return C
  
imports: from __future__ import absolute_import
  import tvm
  from tvm import autotvm, te
  from tvm.autotvm.task.space import SplitEntity
  from tvm.contrib import cblas, dnnl, mkl
  from tvm.target.x86 import get_simd_32bit_lanes
  from tvm.target.codegen import target_has_features
  from ..None import generic, tag
  from ..utils import get_const_tuple, traverse_inline
  from .tensor_intrin import acc_32x32_int32_sapphirerapids, dot_16x1x16_uint8_int8_int32, dot_32x128x32_u8s8s32_sapphirerapids
label_desc: Use image node_id 14 for calling a global function with example usage: matmul_blas_common(cfg, tensor_a, tensor_b, bias, out_dtype, transpose_a, transpose_b, lib) and returns: C