original_docstring: 
      Takes in a "class_index" from 0 to 9 and plots the corresponding
      precision-recall curve
      
docstring: Takes in a "class_index" from 0 to 9 and plots the corresponding
  precision-recall curve
docstring_tokens: Takes in a " class_index " from 0 to 9 and plots the corresponding precision - recall curve
code: def add_pr_curve_tensorboard(class_index, test_probs,
                               test_label, writer, global_step=0):
      '''
      Takes in a "class_index" from 0 to 9 and plots the corresponding
      precision-recall curve
      '''
      tensorboard_truth = test_label == class_index
      if class_index == 0:
          tensorboard_probs = 1 - test_probs
      else:
          tensorboard_probs = test_probs
  
      writer.add_pr_curve(classes[class_index],
                          tensorboard_truth,
                          tensorboard_probs,
                          global_step=global_step)
      writer.close()
code_tokens: def add_pr_curve_tensorboard ( class_index , test_probs , test_label , writer , global_step = 0 ) : tensorboard_truth = test_label == class_index if class_index == 0 : tensorboard_probs = 1 - test_probs else : tensorboard_probs = test_probs writer . add_pr_curve ( classes [ class_index ] , tensorboard_truth , tensorboard_probs , global_step = global_step ) writer . close ( )
short_docstring: Takes in a "class_index" from 0 to 9 and plots the corresponding
  precision-recall curve
short_docstring_tokens: Takes in a " class_index " from 0 to 9 and plots the corresponding precision - recall curve
comment: '''
      Takes in a "class_index" from 0 to 9 and plots the corresponding
      precision-recall curve
      '''