code: def _compute_fid_from_features(
      features_real: Tensor,
      features_fake: Tensor,
  ) -> Tensor:
      stat_1 = fid_features_to_statistics(features_real)
      stat_2 = fid_features_to_statistics(features_fake)
  
      metric = fid_statistics_to_metric(stat_1, stat_2, False)[
          "frechet_inception_distance"
      ]
  
      return torch.tensor(metric)
  
file_path: NeuralCompression/neuralcompression/metrics/_fid.py
imports: from typing import Any, List
  import torch
  from torch import Tensor
  from torch.nn import Module
  from torch_fidelity.metric_fid import fid_features_to_statistics, fid_statistics_to_metric
  from torchmetrics.image.fid import NoTrainInceptionV3
  from torchmetrics.metric import Metric
label_desc: Use image node_id 1 for calling a global function with example usage: _compute_fid_from_features(features_real, features_fake) and returns: torch