class_docstr: This is the loss which was proposed in SimCLR https://arxiv.org/abs/2002.05709 paper.
  See the paper for the details on the loss.
  
  Config params:
      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)
class_docstr_tok: ["This","is","the","loss","which","was","proposed","in","SimCLR","https",":","\/\/arxiv.org\/abs\/2002.05709","paper",".","See","the","paper","for","the","details","on","the","loss",".","Config","params",":","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",")"]
code: def __repr__(self):
      repr_dict = {
          "name": self._get_name(),
          "info_average": self.info_criterion,
      }
      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 SimclrInfoNCELoss obj's underlying member method code with example usage: obj.__repr__() and returns: pprint