code: def schedule_depthwise_conv2d_NCHWc(cfg, outs):
      """CPU schedule for depthwise conv2d in NCHW[x]c layout"""
      outs = [outs] if isinstance(outs, te.tensor.Tensor) else outs
      s = te.create_schedule([x.op for x in outs])
  
      def _callback(op):
          """Traverse operators from computation graph"""
          if "depthwise_conv2d_NCHWc" in op.tag:
              conv_out = op.output(0)
              data = conv_out.op.input_tensors[0]
              kernel = conv_out.op.input_tensors[1]
              _schedule_depthwise_conv2d_NCHWc_impl(
                  s, cfg, data, kernel, conv_out, outs[0]
              )
  
      traverse_inline(s, outs[0].op, _callback)
      return s
  
file_path: tvm/python/tvm/topi/x86/depthwise_conv2d.py
imports: import tvm
  from tvm import autotvm, te
  from tvm.autotvm.task.space import OtherOptionEntity, SplitEntity
  from tvm.target.x86 import get_simd_32bit_lanes
  from ..nn.conv2d import unpack_NCHWc_to_nchw
  from ..nn.depthwise_conv2d import _get_workload, depthwise_conv2d_infer_layout
  from ..nn.pad import pad
  from ..nn.utils import get_pad_tuple
  from ..utils import get_const_tuple, traverse_inline
label_desc: Use image node_id 6 for calling a global function with example usage: schedule_depthwise_conv2d_NCHWc(cfg, outs) and returns: s