code: def space_to_batch_nd(
      data, block_shape, pad_before, pad_after, pad_value=0.0
  ):
      """Perform batch to space transformation on the data
  
      Parameters
      ----------
      data : tvm.te.Tensor
          N-D Tensor with shape [batch, spatial_shape, remaining_shapes],
          where spatial_shape has M dimensions.
  
      block_shape : list of ints
          list of size [M] where M is number of spatial dims, specifies block
          size for each spatial dimension.
  
      pad_before : list of ints
          list of shape [M] where M is number of spatial dims, specifies
          zero-padding size before each spatial dimension.
  
      pad_after : list of ints
          list of shape [M] where M is number of spatial dims, specifies
          zero-padding size after each spatial dimension.
  
      pad_value : float, optional
          The value used for padding.
  
      Returns
      -------
      output : tvm.te.Tensor
      """
  
      return cpp.nn.space_to_batch_nd(
          data, block_shape, pad_before, pad_after, pad_value
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: space_to_batch_nd(data, block_shape, pad_before, pad_after, pad_value) and returns: cpp