code: def tile(cls, op: "TensorRechunk"):
      from ..indexing.slice import TensorSlice
      from ..merge.concatenate import TensorConcatenate
  
      if has_unknown_shape(*op.inputs):
          yield
  
      out = op.outputs[0]
      tensor = astensor(op.inputs[0])
      chunk_size = get_nsplits(
          tensor, op.chunk_size, tensor.dtype.itemsize
      )
      if chunk_size == tensor.nsplits:
          return [tensor]
  
      rechunk_infos = gen_rechunk_infos(tensor, chunk_size)
      out_chunks = []
      for rechunk_info in rechunk_infos:
          chunk_index = rechunk_info.out_index
          shape = rechunk_info.shape
          inp_chunks = rechunk_info.input_chunks
          inp_chunk_slices = rechunk_info.input_slices
          inp_slice_chunks = []
          for inp_chunk, inp_chunk_slice in zip(
              inp_chunks, inp_chunk_slices
          ):
              if all(slc == slice(None) for slc in inp_chunk_slice):
                  inp_slice_chunks.append(inp_chunk)
              else:
                  slc_chunk = TensorSlice(
                      slices=list(inp_chunk_slice)
                  ).new_chunk(
                      [inp_chunk],
                      dtype=inp_chunk.dtype,
                      shape=tuple(
                          calc_sliced_size(s, slc)
                          for s, slc in zip(
                              inp_chunk.shape, inp_chunk_slice
                          )
                      ),
                      index=inp_chunk.index,
                  )
                  inp_slice_chunks.append(slc_chunk)
  
          if (
              len(inp_slice_chunks) > 1
              or inp_slice_chunks[0].index != chunk_index
          ):
              chunk_op = TensorConcatenate()
              out_chunk = chunk_op.new_chunk(
                  inp_slice_chunks,
                  shape=shape,
                  index=chunk_index,
                  dtype=out.dtype,
                  order=out.order,
              )
              out_chunks.append(out_chunk)
          else:
              out_chunks.append(inp_slice_chunks[0])
  
      new_op = op.copy()
      params = out.params
      params["nsplits"] = chunk_size
      params["chunks"] = out_chunks
      tensor = new_op.new_tileable(op.inputs, kws=[params])
  
      if op.reassign_worker:
          for c in tensor.chunks:
              c.op.reassign_worker = True
  
      return [tensor]
  
file_path: mars/mars/tensor/rechunk/rechunk.py
imports: import numpy
  from ...None import opcodes
  from ...serialization.serializables import AnyField
  from ...utils import has_unknown_shape
  from ..core import Tensor
  from ..datasource import tensor
  from ..operands import TensorOperand, TensorOperandMixin
  from ..utils import calc_sliced_size
  from .core import chunk_size_type, get_nsplits, gen_rechunk_infos
label_desc: Use image node_id 2 for calling the TensorRechunk obj's underlying member method code with example usage: obj.tile(cls, op) and returns: list, list