code: def __init__(
      self,
      opts: argparse.Namespace = None,
      is_distributed: bool = False,
      pred: str = None,
      target: str = None,
  ):
      super().__init__(opts, is_distributed, pred, target)
      self.num_bins = getattr(
          self.opts, "stats.metrics.prob_hist.num_bins"
      )
  
file_path: ml-cvnets/metrics/probability_histograms.py
imports: import argparse
  from numbers import Number
  from typing import Dict, Union
  import numpy
  from torch import Tensor
  from torch.nn import functional
  from metrics import METRICS_REGISTRY
  from metrics.metric_base import EpochMetric
  from utils import logger
label_desc: Use image node_id 1 to create a new ProbabilityHistogramMetric object from inherited base classes: EpochMetric with example: obj = ProbabilityHistogramMetric(opts, is_distributed, pred, target)