code: def generate_model_output_single_session() -> (
      Dict[str, torch._tensor.Tensor]
  ):
      return {
          "predictions": torch.tensor([[0.1, 0.2, 0.3, 0.4, 0.5]]),
          "session_ids": torch.tensor([[1, 1, 1, 1, 1]]),
          "labels": torch.tensor([[0.0, 1.0, 0.0, 0.0, 2.0]]),
          "weights": torch.tensor([[1.0, 1.0, 1.0, 1.0, 2.0]]),
          "expected_ndcg_exp": torch.tensor([0.1103]),
          "expected_ndcg_non_exp": torch.tensor([0.1522]),
      }
  
file_path: torchrec/torchrec/metrics/tests/test_ndcg.py
imports: import unittest
  from typing import Dict
  import torch
  from torchrec.metrics.metrics_config import DefaultTaskInfo
  from torchrec.metrics.ndcg import NDCGMetric, SESSION_KEY
label_desc: Use image node_id 1 for calling a global function with example usage: generate_model_output_single_session() and returns: dict