Fix R2 bucket name: voicebox (not voicebox-releases)

test_cuda.py

@@ -0,0 +1,77 @@
+"""Test CUDA detection in voicebox backend"""
+import sys
+import torch
+
+print("=" * 60)
+print("PyTorch CUDA Detection Test")
+print("=" * 60)
+
+# Basic torch info
+print(f"\nPyTorch version: {torch.__version__}")
+print(f"CUDA available: {torch.cuda.is_available()}")
+
+if torch.cuda.is_available():
+    print(f"CUDA version: {torch.version.cuda}")
+    print(f"GPU count: {torch.cuda.device_count()}")
+    print(f"Current GPU: {torch.cuda.current_device()}")
+    print(f"GPU name: {torch.cuda.get_device_name(0)}")
+    print(f"GPU memory: {torch.cuda.get_device_properties(0).total_memory / 1024**3:.2f} GB")
+else:
+    print("\nNo CUDA available - would run on CPU")
+
+# Test backend device selection
+print("\n" + "=" * 60)
+print("Backend Device Selection")
+print("=" * 60)
+
+# Simulate the _get_device method from pytorch_backend.py
+def _get_device() -> str:
+    """Get the best available device."""
+    if torch.cuda.is_available():
+        return "cuda"
+    elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
+        # MPS can have issues, use CPU for stability
+        return "cpu"
+    return "cpu"
+
+selected_device = _get_device()
+print(f"\nSelected device: {selected_device}")
+print(f"Would use dtype: {'torch.bfloat16' if selected_device != 'cpu' else 'torch.float32'}")
+
+# Test actual tensor creation on device
+print("\n" + "=" * 60)
+print("Testing Tensor Creation on Device")
+print("=" * 60)
+
+try:
+    test_tensor = torch.randn(1000, 1000).to(selected_device)
+    print(f"\n[OK] Successfully created tensor on {selected_device}")
+    print(f"  Tensor device: {test_tensor.device}")
+    print(f"  Tensor dtype: {test_tensor.dtype}")
+
+    # Test computation
+    result = test_tensor @ test_tensor.T
+    print(f"[OK] Successfully performed computation on {selected_device}")
+
+    if selected_device == "cuda":
+        print(f"\nCUDA memory allocated: {torch.cuda.memory_allocated() / 1024**2:.2f} MB")
+        print(f"CUDA memory reserved: {torch.cuda.memory_reserved() / 1024**2:.2f} MB")
+
+except Exception as e:
+    print(f"\n[ERROR] {e}")
+
+print("\n" + "=" * 60)
+print("Summary")
+print("=" * 60)
+
+if selected_device == "cuda":
+    print("\n[SUCCESS] CUDA IS WORKING!")
+    print("  The backend will use your NVIDIA GPU for inference")
+    print(f"  GPU: {torch.cuda.get_device_name(0)}")
+    print(f"  This will be significantly faster than CPU")
+else:
+    print("\n[FAIL] CUDA is not available")
+    print("  The backend will use CPU for inference")
+    print("  This will be slower than GPU")
+
+print("\n" + "=" * 60)