Fabian
96 lines
2.6 KiB
Bash
96 lines
2.6 KiB
Bash
#!/bin/bash
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# Test basic tensor.to(cuda) with explicit flushing
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cd /home/fabian/ComfyUI
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source venv/bin/activate
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export HSA_OVERRIDE_GFX_VERSION=10.1.0
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export HSA_ENABLE_SDMA=0
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export HIP_VISIBLE_DEVICES=0
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export PYTORCH_HIP_ALLOC_CONF=garbage_collection_threshold:0.8
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# Kill any remaining python processes first
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pkill -9 -f "python.*main.py" 2>/dev/null
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sleep 1
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timeout 120 python3 -u -c "
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import sys, torch, time, os
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sys.stdout.flush()
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print('Starting transfer test...', flush=True)
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print(f'CUDA available: {torch.cuda.is_available()}', flush=True)
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print(f'Device: {torch.cuda.get_device_name(0)}', flush=True)
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# Test 1: Create on GPU
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print('Test 1: torch.randn(10) on GPU...', flush=True)
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t0 = time.time()
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a = torch.randn(10, device='cuda')
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torch.cuda.synchronize()
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dt = time.time()-t0
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print(f' PASS in {dt:.3f}s', flush=True)
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# Test 2: Small CPU to GPU
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print('Test 2: small .to(cuda)...', flush=True)
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b = torch.randn(10)
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t0 = time.time()
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c = b.to('cuda')
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torch.cuda.synchronize()
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dt = time.time()-t0
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print(f' PASS in {dt:.3f}s', flush=True)
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# Test 3: 1MB float
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print('Test 3: 1MB float .to(cuda)...', flush=True)
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d = torch.randn(256*1024)
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t0 = time.time()
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e = d.to('cuda')
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torch.cuda.synchronize()
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dt = time.time()-t0
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print(f' PASS in {dt:.3f}s', flush=True)
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# Test 4: 1MB uint8
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print('Test 4: 1MB uint8 .to(cuda)...', flush=True)
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f = torch.randint(0, 255, (1024*1024,), dtype=torch.uint8)
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t0 = time.time()
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g = f.to('cuda')
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torch.cuda.synchronize()
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dt = time.time()-t0
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print(f' PASS in {dt:.3f}s', flush=True)
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# Test 5: 10MB uint8
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print('Test 5: 10MB uint8 .to(cuda)...', flush=True)
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h = torch.randint(0, 255, (10*1024*1024,), dtype=torch.uint8)
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t0 = time.time()
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i = h.to('cuda')
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torch.cuda.synchronize()
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dt = time.time()-t0
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print(f' PASS in {dt:.3f}s', flush=True)
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# Test 6: 100MB uint8
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print('Test 6: 100MB uint8 .to(cuda)...', flush=True)
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j = torch.randint(0, 255, (100*1024*1024,), dtype=torch.uint8)
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t0 = time.time()
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k = j.to('cuda')
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torch.cuda.synchronize()
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dt = time.time()-t0
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print(f' PASS in {dt:.3f}s', flush=True)
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# Test 7: GGMLTensor-like subclass
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print('Test 7: Custom subclass .to(cuda)...', flush=True)
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class FakeTensor(torch.Tensor):
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def __new__(cls, data):
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return torch.Tensor._make_subclass(cls, data)
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def to(self, *args, **kwargs):
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new = super().to(*args, **kwargs)
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return new
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raw = torch.randint(0, 255, (1024*1024,), dtype=torch.uint8)
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ft = FakeTensor(raw)
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t0 = time.time()
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ft2 = ft.to('cuda')
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torch.cuda.synchronize()
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dt = time.time()-t0
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print(f' PASS in {dt:.3f}s', flush=True)
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print('ALL TESTS PASSED!', flush=True)
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os._exit(0)
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" 2>&1
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echo "Exit code: $?"
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