105 lines
3.4 KiB
Python
105 lines
3.4 KiB
Python
#!/usr/bin/env python3
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"""
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Test AMD GPU compatibility and suggest fixes
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"""
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import torch
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import sys
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print("=" * 80)
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print("AMD GPU Compatibility Test")
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print("=" * 80)
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# System info
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print(f"\nPyTorch Version: {torch.__version__}")
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print(f"ROCm Version: {torch.version.hip if hasattr(torch.version, 'hip') and torch.version.hip else 'Not available'}")
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print(f"CUDA/ROCm Available: {torch.cuda.is_available()}")
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if torch.cuda.is_available():
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print(f"Device Name: {torch.cuda.get_device_name(0)}")
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print(f"Device Count: {torch.cuda.device_count()}")
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# Test 1: Simple tensor creation
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print("\n" + "=" * 80)
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print("Test 1: Simple Tensor Creation")
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print("=" * 80)
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try:
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x = torch.tensor([1.0, 2.0, 3.0]).cuda()
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print("✓ PASSED: Simple tensor creation on GPU")
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except Exception as e:
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print(f"✗ FAILED: {e}")
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sys.exit(1)
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# Test 2: Matrix multiplication
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print("\n" + "=" * 80)
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print("Test 2: Matrix Multiplication")
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print("=" * 80)
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try:
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a = torch.randn(100, 100).cuda()
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b = torch.randn(100, 100).cuda()
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c = torch.matmul(a, b)
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print("✓ PASSED: Matrix multiplication on GPU")
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except Exception as e:
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print(f"✗ FAILED: {e}")
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sys.exit(1)
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# Test 3: Linear layer (This is where gfx1151 fails)
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print("\n" + "=" * 80)
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print("Test 3: Neural Network Linear Layer (Critical Test)")
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print("=" * 80)
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try:
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x = torch.randn(10, 20).cuda()
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linear = torch.nn.Linear(20, 10).cuda()
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y = linear(x)
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print("✓ PASSED: Linear layer on GPU")
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print("✓ Your GPU is fully compatible!")
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except RuntimeError as e:
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if "invalid device function" in str(e):
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print(f"✗ FAILED: {e}")
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print("\n" + "=" * 80)
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print("DIAGNOSIS: GPU Architecture Not Supported")
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print("=" * 80)
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print("\nYour AMD GPU architecture (likely gfx1151) is not supported by this PyTorch build.")
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print("\nRECOMMENDED ACTIONS:")
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print("1. The application will automatically use CPU mode")
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print("2. For GPU support, try: export HSA_OVERRIDE_GFX_VERSION=11.0.0")
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print("3. Or reinstall PyTorch nightly: pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/rocm6.4")
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print("\nSee AMD_GPU_FIX.md for detailed instructions")
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sys.exit(1)
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else:
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raise
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# Test 4: Conv2d layer
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print("\n" + "=" * 80)
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print("Test 4: Convolutional Layer")
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print("=" * 80)
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try:
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x = torch.randn(1, 3, 32, 32).cuda()
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conv = torch.nn.Conv2d(3, 16, 3).cuda()
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y = conv(x)
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print("✓ PASSED: Convolutional layer on GPU")
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except Exception as e:
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print(f"✗ FAILED: {e}")
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# Test 5: Transformer layer
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print("\n" + "=" * 80)
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print("Test 5: Transformer Layer")
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print("=" * 80)
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try:
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x = torch.randn(1, 10, 512).cuda()
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transformer = torch.nn.TransformerEncoderLayer(d_model=512, nhead=8).cuda()
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y = transformer(x)
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print("✓ PASSED: Transformer layer on GPU")
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except Exception as e:
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print(f"✗ FAILED: {e}")
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print("\n" + "=" * 80)
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print("ALL TESTS PASSED - GPU IS FULLY FUNCTIONAL!")
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print("=" * 80)
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else:
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print("\n" + "=" * 80)
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print("No CUDA/ROCm device detected")
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print("=" * 80)
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print("Application will run in CPU mode")
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