code: def schedule_conv2d_transpose_nchw(outs):
      """Create schedule for tensors"""
      outs = [outs] if isinstance(outs, te.tensor.Tensor) else outs
      s = schedule_conv2d_nchw(outs)
  
      def _callback(op):
          if "unpack_nchwc" in op.tag:
              conv_out = op.input_tensors[0]
              # retrieve data
              data_vec = conv_out.op.input_tensors[0]
              if isinstance(data_vec, te.ComputeOp):
                  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]
              if isinstance(kernel_vec, te.ComputeOp):
                  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 .conv2d import conv2d_nchw, schedule_conv2d_nchw
label_desc: Use image node_id 2 for calling a global function with example usage: schedule_conv2d_transpose_nchw(outs) and returns: s