Uploaded sanitized BC250/ROCm Repository.

Scripts and Tests/test_transfer2.sh

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