class_docstr: A TFGraphRecordDecoder that decodes ExampleListWithContext proto.
class_docstr_tok: ["A","TFGraphRecordDecoder","that","decodes","ExampleListWithContext","proto","."]
code: def __init__(
      self,
      name: str,
      context_features: List[Feature],
      example_features: List[Feature],
      size_feature_name: Optional[str] = None,
      label_feature: Optional[Feature] = None,
  ):
      self._context_features = context_features
      self._example_features = example_features
      self._size_feature_name = size_feature_name
      self._label_feature = label_feature
  
file_path: tfx/tfx/examples/ranking/struct2tensor_parsing_utils.py
imports: import itertools
  from typing import Dict, List, Optional, Union
  from struct2tensor import calculate
  from struct2tensor import calculate_options
  from struct2tensor import path
  from struct2tensor import prensor_util
  from struct2tensor.expression_impl import proto
  import tensorflow
  from tfx_bsl.public import tfxio
  from tensorflow_serving.apis import input_pb2
label_desc: Use image node_id 1 to create a new ELWCDecoder object from inherited base classes: tfxio with example: obj = ELWCDecoder(name, context_features, example_features, size_feature_name, label_feature)