class_docstr: - **homepage**: https://cocodataset.org/
  - **dependencies**:
      - <pycocotools `https://github.com/cocodataset/cocoapi`>_
class_docstr_tok: ["-","*","*","homepage","*","*",":","https",":","\/\/cocodataset.org\/","-","*","*","dependencies","*","*",":","-","<","pycocotools","`","https",":","\/\/github.com\/cocodataset\/cocoapi","`",">","_"]
code: def _filter_meta_files(self, data: Tuple[str, Any]) -> bool:
      match = self._META_FILE_PATTERN.match(pathlib.Path(data[0]).name)
      return bool(
          match
          and match["split"] == self._split
          and match["year"] == self._year
          and match["annotations"] == self._annotations
      )
  
imports: import pathlib
  import re
  from collections import defaultdict, OrderedDict
  from typing import Any, BinaryIO, cast, Dict, List, Optional, Tuple, Union
  import torch
  from torchdata.datapipes.iter import Demultiplexer, Filter, Grouper, IterDataPipe, IterKeyZipper, JsonParser, Mapper, UnBatcher
  from torchvision.prototype.datasets.utils import Dataset, EncodedImage, HttpResource, OnlineResource
  from torchvision.prototype.datasets.utils._internal import getitem, hint_sharding, hint_shuffling, INFINITE_BUFFER_SIZE, MappingIterator, path_accessor, read_categories_file
  from torchvision.prototype.tv_tensors import Label
  from torchvision.tv_tensors import BoundingBoxes, Mask
  from .._api import register_dataset, register_info
label_desc: Use image node_id 6 for calling the Coco obj's underlying member method code with example usage: obj._filter_meta_files(data) and returns: bool