class_docstr: Computes PredictionDifference.
class_docstr_tok: ["Computes","PredictionDifference","."]
code: def __init__(
      self,
      eval_config: config_pb2.EvalConfig,
      baseline_model_name: str,
      model_name: str,
      output_name: str,
      key: metric_types.MetricKey,
      example_weighted: bool,
  ):
      self._eval_config = eval_config
      self._baseline_model_name = baseline_model_name
      self._model_name = model_name
      self._output_name = output_name
      self._key = key
      self._example_weighted = example_weighted
  
file_path: model-analysis/tensorflow_model_analysis/metrics/prediction_difference_metrics.py
imports: import dataclasses
  from typing import Optional, Dict, Iterable, List
  import apache_beam
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.utils import model_util
label_desc: Use image node_id 1 to create a new _SymmetricPredictionDifferenceCombiner object from inherited base classes: beam with example: obj = _SymmetricPredictionDifferenceCombiner(eval_config, baseline_model_name, model_name, output_name, key, example_weighted)