code: def build_ngram_suggester(sizes: List[int]) -> Suggester:
      """Suggest all spans of the given lengths. Spans are returned as a ragged
      array of integers. The array has two columns, indicating the start and end
      position."""
  
      return partial(ngram_suggester, sizes=sizes)
  
imports: from dataclasses import dataclass
  from functools import partial
  from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Union, cast
  import numpy
  from thinc.api import Config, Model, Ops, Optimizer, get_current_ops, set_dropout_rate
  from thinc.types import Floats2d, Ints1d, Ints2d, Ragged
  from ..compat import Protocol, runtime_checkable
  from ..errors import Errors
  from ..language import Language
  from ..scorer import Scorer
  from ..tokens import Doc, Span, SpanGroup
  from ..training import Example, validate_examples
  from ..util import registry
  from ..vocab import Vocab
  from .trainable_pipe import TrainablePipe
label_desc: Use image node_id 3 for calling a global function with example usage: build_ngram_suggester(sizes) and returns: partial