docstr: Checks that the values stored within a tensor are correct.
  
  Args:
    expected_step: The expected step.
    expected_precision: A list of float values.
    expected_recall: A list of float values.
    expected_true_positives: A list of int values.
    expected_false_positives: A list of int values.
    expected_true_negatives: A list of int values.
    expected_false_negatives: A list of int values.
    expected_thresholds: A list of floats ranging from 0 to 1.
    pr_curve_entry: The PR curve entry to evaluate.
docstr_tok: ["Checks","that","the","values","stored","within","a","tensor","are","correct",".","Args",":","expected_step",":","The","expected","step",".","expected_precision",":","A","list","of","float","values",".","expected_recall",":","A","list","of","float","values",".","expected_true_positives",":","A","list","of","int","values",".","expected_false_positives",":","A","list","of","int","values",".","expected_true_negatives",":","A","list","of","int","values",".","expected_false_negatives",":","A","list","of","int","values",".","expected_thresholds",":","A","list","of","floats","ranging","from","0","to","1.","pr_curve_entry",":","The","PR","curve","entry","to","evaluate","."]
code: def validatePrCurveEntry(
      self,
      expected_step,
      expected_precision,
      expected_recall,
      expected_true_positives,
      expected_false_positives,
      expected_true_negatives,
      expected_false_negatives,
      expected_thresholds,
      pr_curve_entry,
  ):
      """Checks that the values stored within a tensor are correct.
  
      Args:
        expected_step: The expected step.
        expected_precision: A list of float values.
        expected_recall: A list of float values.
        expected_true_positives: A list of int values.
        expected_false_positives: A list of int values.
        expected_true_negatives: A list of int values.
        expected_false_negatives: A list of int values.
        expected_thresholds: A list of floats ranging from 0 to 1.
        pr_curve_entry: The PR curve entry to evaluate.
      """
      self.assertEqual(expected_step, pr_curve_entry["step"])
      assert_allclose(expected_precision, pr_curve_entry["precision"])
      assert_allclose(expected_recall, pr_curve_entry["recall"])
      self.assertListEqual(
          expected_true_positives, pr_curve_entry["true_positives"]
      )
      self.assertListEqual(
          expected_false_positives, pr_curve_entry["false_positives"]
      )
      self.assertListEqual(
          expected_true_negatives, pr_curve_entry["true_negatives"]
      )
      self.assertListEqual(
          expected_false_negatives, pr_curve_entry["false_negatives"]
      )
      assert_allclose(expected_thresholds, pr_curve_entry["thresholds"])
  
imports: import collections.abc
  import functools
  import os.path
  import numpy
  import tensorflow
  from tensorboard import context
  from tensorboard.backend.event_processing import plugin_event_multiplexer
  from tensorboard.backend.event_processing import data_provider
  from tensorboard.plugins import base_plugin
  from tensorboard.plugins.pr_curve import pr_curve_demo
  from tensorboard.plugins.pr_curve import pr_curves_plugin
label_desc: Use image node_id 2 for calling the PrCurvesPluginTest obj's underlying member method code with example usage: obj.validatePrCurveEntry(expected_step, expected_precision, expected_recall, expected_true_positives, expected_false_positives, expected_true_negatives, expected_false_negatives, expected_thresholds, pr_curve_entry) without return types