code: def _schedule_dense_nopack_template(cfg, s, C):
      y, x = s[C].op.axis
      (kk,) = s[C].op.reduce_axis
      yo, yi = cfg["tile_y"].apply(s, C, y)
      xo, xi = cfg["tile_x"].apply(s, C, x)
      s[C].reorder(yo, xo, yi, xi)
      xyo = s[C].fuse(yo, xo)
      s[C].parallel(xyo)
      s[C].unroll(kk)
  
      (CC,) = s[C].op.input_tensors
      s[CC].compute_at(s[C], xyo)
      z, y, x = s[CC].op.axis
      (k,) = s[CC].op.reduce_axis
      yz = s[CC].fuse(z, y)
      s[CC].reorder(k, yz, x)
      s[CC].unroll(yz)
      s[CC].vectorize(x)
      return s
  
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 2 for calling a global function with example usage: _schedule_dense_nopack_template(cfg, s, C) and returns: s