code: def __call__(self, a):
      shape = list(a.shape)
      shape[self._axis] = min(a.shape[self._axis], self._k)
      kws = []
      if self._return_value:
          kws.append(
              {
                  "shape": tuple(shape),
                  "order": a.order,
                  "dtype": a.dtype,
                  "type": "topk",
              }
          )
      if self._return_indices:
          kws.append(
              {
                  "shape": tuple(shape),
                  "order": TensorOrder.C_ORDER,
                  "dtype": np.dtype(np.int64),
                  "type": "argtopk",
              }
          )
      ret = self.new_tensors([a], kws=kws)
      if len(kws) == 1:
          return ret[0]
      return ExecutableTuple(ret)
  
imports: import itertools
  import numpy
  from ...None import opcodes
  from ...config import options
  from ...core import ExecutableTuple, recursive_tile
  from ...core.operand import OperandStage
  from ...serialization.serializables import FieldTypes, KeyField, Int64Field, Int32Field, BoolField, StringField, ListField
  from ...utils import ceildiv, flatten
  from ..array_utils import as_same_device, device
  from ..core import TensorOrder
  from ..datasource import tensor
  from ..operands import TensorOperand, TensorOperandMixin
  from ..utils import validate_axis, validate_order
  from .sort import _validate_sort_psrs_kinds
label_desc: Use image node_id 15 for calling the TensorTopk obj's underlying member method code with example usage: obj.__call__(a) and returns: ExecutableTuple, ret