Summary: Enhanced the PyTorch CUDA memory visualizer to display user_metadata alongside stack frames when inspecting allocations. The user_metadata field is now shown in all views (Allocator State History, Active Memory Timeline, etc.) with consistent formatting. The implementation handles both string and object metadata types, displaying strings directly and objects as key-value pairs.

Test Plan:
1. Generate a memory snapshot with user_metadata:
   ```python
   import torch
   torch.cuda.memory._record_memory_history(enabled=True)
   # Add allocations with user_metadata
   x = torch.randn(1000, 1000, device='cuda')
   torch.cuda.memory._dump_snapshot("snapshot.pickle")
   ```
2. Open the memory visualizer in a browser
3. Load the snapshot file
4. Verify user_metadata appears
5. Test with both string metadata ("testing") and object metadata ({"key": "value"})
6. Verify formatting shows "User Metadata:\n  <value>" for strings

 {F1982860439}

Differential Revision: D85095152