class_docstr: The criterion corresponding to the expandion SimCLR loss (as defined in the paper
  https://arxiv.org/abs/2002.05709) using the multi-crop augmentaion proposed
  in SwAV paper. The multi-crop augmentation allows using more positives
  per image.
  
  Args:
      temperature (float): the temperature to be applied on the logits
      num_crops (int): number of positives
      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 __init__(self, buffer_params, temperature: float, num_crops: int):
      self.num_crops = num_crops
      super(MultiCropSimclrInfoNCECriterion, self).__init__(
          buffer_params, temperature
      )
      logging.info(f"Setting multicrop num_crops: {num_crops}")
  
file_path: vissl/vissl/losses/multicrop_simclr_info_nce_loss.py
imports: import logging
  import pprint
  import numpy
  import torch
  from classy_vision.losses import register_loss
  from vissl.config import AttrDict
  from vissl.losses.simclr_info_nce_loss import SimclrInfoNCECriterion, SimclrInfoNCELoss
label_desc: Use image node_id 1 to create a new MultiCropSimclrInfoNCECriterion object from inherited base classes: SimclrInfoNCECriterion with example: obj = MultiCropSimclrInfoNCECriterion(buffer_params, temperature, num_crops)