code: def schedule_conv3d_transpose_ncdhw(outs):
      """Create schedule for tensors"""
      outs = [outs] if isinstance(outs, te.tensor.Tensor) else outs
      s = schedule_conv3d_ncdhw(outs)
  
      def _callback(op):
          if "unpack_ncdhwc" in op.tag:
              conv_out = op.input_tensors[0]
              # retrieve data
              data_vec = conv_out.op.input_tensors[0]
              data_pad = data_vec.op.input_tensors[0]
              data_dilate = data_pad.op.input_tensors[0]
              s[data_dilate].compute_inline()
              s[data_pad].compute_inline()
              # retrieve kernel
              kernel_vec = conv_out.op.input_tensors[1]
              kernel_transform = kernel_vec.op.input_tensors[0]
              s[kernel_transform].compute_inline()
  
      traverse_inline(s, outs[0].op, _callback)
      return s
  
imports: from tvm import te
  from ..utils import traverse_inline
  from ..None import nn
  from .conv3d import conv3d_ncdhw, schedule_conv3d_ncdhw
label_desc: Use image node_id 2 for calling a global function with example usage: schedule_conv3d_transpose_ncdhw(outs) and returns: s