code: def tile(cls, op: "TensorMapChunk"):
      inp = op.inputs[0]
      out = op.outputs[0]
  
      new_inputs = [op.inputs[0]]
      if has_unknown_shape(*op.inputs[1:]):
          yield
      for other_inp in op.inputs[1:]:
          other_inp = yield from recursive_tile(
              other_inp.rechunk(other_inp.shape)
          )
          new_inputs.append(other_inp)
  
      chunks = []
      for c in inp.chunks:
          params = c.params
          params["dtype"] = out.dtype
          if not op.elementwise:
              params["shape"] = (np.nan,) * out.ndim
              params["index"] = params["index"][: out.ndim]
  
          new_op = op.copy().reset_key()
          new_op.tileable_op_key = out.key
          chunk_inputs = [c]
          for other_inp in new_inputs[1:]:
              chunk_inputs.append(other_inp.chunks[0])
          chunks.append(new_op.new_chunk(chunk_inputs, **params))
  
      new_op = op.copy().reset_key()
      params = out.params
      nsplits = inp.nsplits[: out.ndim]
      if not op.elementwise:
          nsplits = tuple((np.nan,) * len(sp) for sp in nsplits)
      return new_op.new_tileables(
          op.inputs, chunks=chunks, nsplits=nsplits, **params
      )
  
imports: import numpy
  from ...None import opcodes
  from ...core import ENTITY_TYPE, CHUNK_TYPE, recursive_tile
  from ...core.custom_log import redirect_custom_log
  from ...serialization.serializables import FunctionField, BoolField, TupleField, DictField
  from ...utils import enter_current_session, quiet_stdio, find_objects, replace_objects, has_unknown_shape
  from ..operands import TensorOperand, TensorOperandMixin
label_desc: Use image node_id 9 for calling the TensorMapChunk obj's underlying member method code with example usage: obj.tile(cls, op) and returns: new_op