code: def tile(cls, op):
      x = astensor(op.input)
      axis = op.axis
      ord = op.ord
      keepdims = op.keepdims
  
      axis_chunk_shapes = tuple(x.chunk_shape[i] for i in axis)
      can_apply_norm = all(s == 1 for s in axis_chunk_shapes)
  
      if can_apply_norm:
          axis_set = set(axis)
          get_shape = lambda shape: tuple(
              s if i not in axis_set else 1
              for i, s in enumerate(shape)
              if i not in axis_set or keepdims
          )
  
          out_chunk_shape = get_shape(x.chunk_shape)
          out_chunks = []
          for idx in itertools.product(
              *[range(s) for s in out_chunk_shape]
          ):
              idx_iter = iter(idx)
              in_idx = tuple(
                  0
                  if i in axis_set and not keepdims
                  else next(idx_iter)
                  for i in range(x.ndim)
              )
  
              c = x.cix[in_idx]
              chunk_op = op.copy().reset_key()
              out_chunk = chunk_op.new_chunk(
                  [c], shape=get_shape(c.shape), index=idx
              )
              out_chunks.append(out_chunk)
  
          nsplits = [
              tuple(
                  c.shape[i]
                  for c in out_chunks
                  if all(
                      idx == 0
                      for j, idx in enumerate(c.index)
                      if j != i
                  )
              )
              for i in range(len(out_chunks[0].shape))
          ]
          new_op = op.copy()
          return new_op.new_tensors(
              op.inputs,
              op.outputs[0].shape,
              chunks=out_chunks,
              nsplits=nsplits,
          )
  
      r = yield from recursive_tile(
          cls._norm(
              x.astype(op.outputs[0].dtype, copy=False),
              ord,
              axis,
              keepdims,
          )
      )
      new_op = op.copy()
      return new_op.new_tensors(
          op.inputs,
          op.outputs[0].shape,
          chunks=r.chunks,
          nsplits=r.nsplits,
      )
  
imports: import itertools
  from collections.abc import Iterable
  import numpy
  from ...None import opcodes
  from ...core import recursive_tile
  from ...serialization.serializables import FieldTypes, KeyField, AnyField, TupleField, BoolField
  from ..utils import validate_axis
  from ..array_utils import device, as_same_device
  from ..operands import TensorHasInput, TensorOperandMixin
  from ..arithmetic import sqrt
  from ..datasource import tensor
  from .svd import svd
label_desc: Use image node_id 7 for calling the TensorNorm obj's underlying member method code with example usage: obj.tile(cls, op) and returns: new_op, new_op