class_docstr: Computes query statistics metrics.
class_docstr_tok: ["Computes","query","statistics","metrics","."]
code: def __init__(
      self,
      total_queries_key: metric_types.MetricKey,
      total_documents_key: metric_types.MetricKey,
      min_documents_key: metric_types.MetricKey,
      max_documents_key: metric_types.MetricKey,
      eval_config: config_pb2.EvalConfig,
      model_name: str,
      output_name: str,
      example_weighted: bool,
  ):
      self._total_queries_key = total_queries_key
      self._total_documents_key = total_documents_key
      self._min_documents_key = min_documents_key
      self._max_documents_key = max_documents_key
      self._eval_config = eval_config
      self._model_name = model_name
      self._output_name = output_name
      self._example_weighted = example_weighted
  
file_path: model-analysis/tensorflow_model_analysis/metrics/query_statistics.py
imports: from typing import Dict, Iterable, Optional
  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
label_desc: Use image node_id 1 to create a new _QueryStatisticsCombiner object from inherited base classes: beam with example: obj = _QueryStatisticsCombiner(total_queries_key, total_documents_key, min_documents_key, max_documents_key, eval_config, model_name, output_name, example_weighted)