docstr: Compute activation statistics for a batch of images.
  
  :param activations: an [N x D] batch of activations.
  :return: an FIDStatistics object.
docstr_tok: ["Compute","activation","statistics","for","a","batch","of","images",".",":","param","activations",":","an","[","N","x","D","]","batch","of","activations",".",":","return",":","an","FIDStatistics","object","."]
code: def get_statistics(self, activations: np.ndarray, resolution: int):
      """
      Compute activation statistics for a batch of images.
  
      :param activations: an [N x D] batch of activations.
      :return: an FIDStatistics object.
      """
      mu = np.mean(activations, axis=0)
      sigma = np.cov(activations, rowvar=False)
      return FIDStatistics(mu, sigma, resolution)
  
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 2 for calling the FIDAndIS obj's underlying member method code with example usage: obj.get_statistics(activations, resolution) and returns: FIDStatistics