Fabian
54 lines
1.5 KiB
Bash
54 lines
1.5 KiB
Bash
#!/bin/bash
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# Test basic tensor.to(cuda) - does hipMemcpy work at all?
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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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timeout 30 python3 -c "
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import torch, time, os
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print(f'CUDA available: {torch.cuda.is_available()}')
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print(f'Device: {torch.cuda.get_device_name(0)}')
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# Test 1: Create on GPU (already works)
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print('Test 1: torch.randn on GPU...')
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t0 = time.time()
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a = torch.randn(10, device='cuda')
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print(f' OK in {time.time()-t0:.2f}s: {a[:3]}')
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# Test 2: CPU to GPU transfer (the problematic path)
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print('Test 2: tensor.to(cuda) small...')
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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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print(f' OK in {time.time()-t0:.2f}s: {c[:3]}')
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# Test 3: Larger transfer
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print('Test 3: tensor.to(cuda) 1MB...')
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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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print(f' OK in {time.time()-t0:.2f}s, shape={e.shape}')
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# Test 4: uint8 transfer (like GGUF)
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print('Test 4: uint8 tensor.to(cuda)...')
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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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print(f' OK in {time.time()-t0:.2f}s, shape={g.shape}')
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# Test 5: Large uint8 (like a GGUF weight)
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print('Test 5: 10MB uint8 tensor.to(cuda)...')
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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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print(f' OK in {time.time()-t0:.2f}s, shape={i.shape}')
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print('ALL TESTS PASSED - hipMemcpy works!')
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os._exit(0)
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" 2>&1
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echo "Exit code: $?"
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