code: def _getitem_nocheck(a, item, convert_bool_to_fancy=None):
      index = process_index(
          a.ndim, item, convert_bool_to_fancy=convert_bool_to_fancy
      )
      if convert_bool_to_fancy is False:
          # come from __setitem__, the bool index is not converted to fancy index
          # if multiple bool indexes or bool + fancy indexes exist,
          # thus the shape will be wrong,
          # here we just convert when calculating shape,
          # refer to issue #1282.
          shape = calc_shape(a.shape, process_index(a.ndim, index))
      else:
          shape = calc_shape(a.shape, index)
      tensor_order = _calc_order(a, index)
      op = TensorIndex(
          dtype=a.dtype,
          sparse=a.issparse(),
          indexes=list(index),
          create_view=_is_create_view(index),
      )
      return op(a, index, tuple(shape), order=tensor_order)
  
imports: from numbers import Integral
  import numpy
  from ...None import opcodes
  from ...core import ENTITY_TYPE
  from ...core.operand import OperandStage
  from ...serialization.serializables import FieldTypes, KeyField, ListField, TupleField, Int32Field
  from ..core import TENSOR_TYPE, TensorOrder
  from ..utils import split_indexes_into_chunks, calc_pos, filter_inputs
  from ..operands import TensorHasInput, TensorOperandMixin, TensorMapReduceOperand
  from ..array_utils import get_array_module
  from .core import process_index, calc_shape
  from .index_lib import TensorIndexesHandler
label_desc: Use image node_id 5 for calling a global function with example usage: _getitem_nocheck(a, item, convert_bool_to_fancy) and returns: op