class_docstr: Allow to decode a subset of features.
  
  See guide:
  https://www.tensorflow.org/datasets/decode#only_decode_a_sub-set_of_the_features
docstr: Constructor.
  
  Args:
    features: A nested dict of `tfds.features.FeatureConnector`
    decoders: Optional additional decoders to apply (e.g.
      `tfds.decode.SkipDecoding()`)
docstr_tok: ["Constructor",".","Args",":","features",":","A","nested","dict","of","`","tfds.features.FeatureConnector","`","decoders",":","Optional","additional","decoders","to","apply","(","e.g",".","`","tfds.decode.SkipDecoding","(",")","`",")"]
code: def __init__(
      self,
      features: FeatureSpecs,
      decoders: Optional[utils.TreeDict[base.Decoder]] = None,
  ):
      """Constructor.
  
      Args:
        features: A nested dict of `tfds.features.FeatureConnector`
        decoders: Optional additional decoders to apply (e.g.
          `tfds.decode.SkipDecoding()`)
      """
      self.decoders = decoders
      self._feature_specs = features
  
file_path: datasets/tensorflow_datasets/core/decode/partial_decode.py
imports: import typing
  from typing import Any, Callable, Optional, Union
  from tensorflow_datasets.core import features
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.decode import base
  from tensorflow_datasets.core.features import features_dict
  from tensorflow_datasets.core.utils import dtype_utils
label_desc: Use image node_id 1 to create a new PartialDecoding object  with example: obj = PartialDecoding(features, decoders)