class_docstr: The criterion corresponding to the SimCLR loss as defined in the paper
  https://arxiv.org/abs/2002.05709.
  
  Args:
      temperature (float): the temperature to be applied on the logits
      buffer_params:
          world_size (int): total number of trainers in training
          embedding_dim (int): output dimensions of the features projects
          effective_batch_size (int): total batch size used (includes positives)
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code: def __repr__(self):
      num_negatives = self.buffer_params.effective_batch_size - 2
      T = self.temperature
      num_pos = self.num_pos
      repr_dict = {
          "name": self._get_name(),
          "temperature": T,
          "num_negatives": num_negatives,
          "num_pos": num_pos,
          "dist_rank": self.dist_rank,
      }
      return pprint.pformat(repr_dict, indent=2)
  
imports: import logging
  import pprint
  import numpy
  import torch
  from classy_vision.generic.distributed_util import get_cuda_device_index, get_rank
  from classy_vision.losses import ClassyLoss, register_loss
  from torch import nn
  from vissl.config import AttrDict
  from vissl.utils.distributed_utils import gather_from_all
label_desc: Use image node_id 4 for calling the SimclrInfoNCECriterion obj's underlying member method code with example usage: obj.__repr__() and returns: pprint