class_docstr: Compute precision / recall in binary classification, given the
  prediction vector and the label vector.
docstr: Args:
      pred_tensor_name(str): name of the 0/1 prediction tensor.
      label_tensor_name(str): name of the 0/1 label tensor.
code: def __init__(self, pred_tensor_name, label_tensor_name, prefix="val"):
      """
      Args:
          pred_tensor_name(str): name of the 0/1 prediction tensor.
          label_tensor_name(str): name of the 0/1 label tensor.
      """
      self.pred_tensor_name = pred_tensor_name
      self.label_tensor_name = label_tensor_name
      self.prefix = prefix
  
imports: import numpy
  from abc import ABCMeta
  import six
  from ..tfutils.common import get_op_tensor_name
  from ..utils import logger
  from ..utils.stats import BinaryStatistics, RatioCounter
  from .base import Callback
label_desc: Use image node_id 1 to create a new BinaryClassificationStats object from inherited base classes: Inferencer with example: obj = BinaryClassificationStats(pred_tensor_name, label_tensor_name, prefix)