code: def _get_confidence_interval_params(
      eval_config: config_pb2.EvalConfig,
      metrics_specs: Iterable[config_pb2.MetricsSpec],
  ) -> _ConfidenceIntervalParams:
      """Helper method for extracting confidence interval info from configs.
  
      Args:
        eval_config: The eval_config.
        metrics_specs: The metrics_specs containing either all metrics, or the ones
          which share a query key.
  
      Returns:
        A _ConfidenceIntervalParams object containing the number of jacknife samples
        to use for computing a jackknife confidence interval, the number of
        bootstrap samples to use for computing Poisson bootstrap confidence
        intervals, and the set of metric keys which should not have confidence
        intervals displayed in the output.
      """
      skip_ci_metric_keys = (
          metric_specs.metric_keys_to_skip_for_confidence_intervals(
              metrics_specs, eval_config=eval_config
          )
      )
      num_jackknife_samples = 0
      num_bootstrap_samples = 0
      ci_method = eval_config.options.confidence_intervals.method
      if eval_config.options.compute_confidence_intervals.value:
          if (
              ci_method
              == config_pb2.ConfidenceIntervalOptions.JACKKNIFE
          ):
              num_jackknife_samples = _DEFAULT_NUM_JACKKNIFE_BUCKETS
          elif (
              ci_method
              == config_pb2.ConfidenceIntervalOptions.POISSON_BOOTSTRAP
          ):
              num_bootstrap_samples = _DEFAULT_NUM_BOOTSTRAP_SAMPLES
      return _ConfidenceIntervalParams(
          num_jackknife_samples,
          num_bootstrap_samples,
          skip_ci_metric_keys,
      )
  
imports: import copy
  import datetime
  import itertools
  import numbers
  from typing import Any, Dict, Iterable, Iterator, List, NamedTuple, Optional, Tuple, Type, TypeVar, Union
  import apache_beam
  import numpy
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.evaluators import counter_util
  from tensorflow_model_analysis.evaluators import eval_saved_model_util
  from tensorflow_model_analysis.evaluators import evaluator
  from tensorflow_model_analysis.evaluators import jackknife
  from tensorflow_model_analysis.evaluators import keras_util
  from tensorflow_model_analysis.evaluators import metrics_validator
  from tensorflow_model_analysis.evaluators import poisson_bootstrap
  from tensorflow_model_analysis.extractors import slice_key_extractor
  from tensorflow_model_analysis.metrics import metric_specs
  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.slicer import slicer_lib
  from tensorflow_model_analysis.utils import model_util
  from tensorflow_model_analysis.utils import util
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 10 for calling a global function with example usage: _get_confidence_interval_params(eval_config, metrics_specs) and returns: _ConfidenceIntervalParams