code: def get_virtual_batch(
      self, data, num_samples, global_batch_size, resolution
  ):
      preds, spatial_preds, clip_preds, batch = self.get_activations(
          data, num_samples, global_batch_size, pr_samples=10000
      )
      if self.is_root:
          fid_stats = self.get_statistics(preds, resolution)
          spatial_stats = self.get_statistics(spatial_preds, resolution)
          clip_stats = self.get_statistics(clip_preds, resolution)
          return batch, dict(
              mu=fid_stats.mu,
              sigma=fid_stats.sigma,
              mu_s=spatial_stats.mu,
              sigma_s=spatial_stats.sigma,
              mu_clip=clip_stats.mu,
              sigma_clip=clip_stats.sigma,
          )
      else:
          return None, dict()
  
imports: from .inception_v3 import InceptionV3
  import blobfile
  import torch
  import torch.distributed
  import torch.nn
  from cm import dist_util
  import numpy
  import warnings
  from scipy import linalg
  from PIL import Image
  from tqdm import tqdm
label_desc: Use image node_id 7 for calling the FIDAndIS obj's underlying member method code with example usage: obj.get_virtual_batch(data, num_samples, global_batch_size, resolution) and returns: batch,  dict, None,  dict