code: def _execute_inverse_reduce(cls, ctx, op: "TensorUnique"):
      out = op.outputs[0]
      inputs = list(op.iter_mapper_data(ctx))
      unique_sizes = [inp[0] for inp in inputs]
      cum_unique_sizes = np.cumsum([0] + unique_sizes)
      invs, device_id, xp = as_same_device(
          [inp[1] for inp in inputs], device=op.device, ret_extra=True
      )
      with device(device_id):
          ret = xp.empty(out.shape, dtype=out.dtype)
          for i, inv in enumerate(invs):
              ret[inv[0]] = cum_unique_sizes[i] + inv[1]
          ctx[out.key] = ret
  
imports: import itertools
  import numpy
  from ...None import opcodes
  from ...config import options
  from ...core import recursive_tile
  from ...core.operand import OperandStage
  from ...lib import sparse
  from ...lib.sparse.core import get_array_module
  from ...serialization.serializables import BoolField, Int32Field, Int64Field
  from ...utils import has_unknown_shape
  from ..operands import TensorMapReduceOperand, TensorOperandMixin, TensorShuffleProxy
  from ..array_utils import as_same_device, device
  from ..core import TensorOrder
  from ..utils import validate_axis, hash_on_axis
label_desc: Use image node_id 16 for calling the TensorUnique obj's underlying member method code with example usage: obj._execute_inverse_reduce(cls, ctx, op) without return types