code: def generate_model_output_negative_sessions() -> (
      Dict[str, torch._tensor.Tensor]
  ):
      return {
          "predictions": torch.tensor(
              [[0.1, 0.2, 0.3, 0.4, 0.5, 0.1, 0.2, 0.3]]
          ),
          "session_ids": torch.tensor([[1, 1, 1, 1, 1, 2, 2, 2]]),
          "labels": torch.tensor(
              [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]
          ),
          "weights": torch.tensor(
              [[1.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 3.0]]
          ),
          "expected_ndcg_exp": torch.tensor([2.5]),
          "expected_ndcg_non_exp": torch.tensor([2.5]),
      }
  
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 3 for calling a global function with example usage: generate_model_output_negative_sessions() and returns: dict