Uploaded sanitized BC250/ROCm Repository.

2026-08-20 00:45:43 +02:00
parent 7d2184f1e8
commit d7d22e93b3
678 changed files with 65963 additions and 1 deletions
@@ -0,0 +1,128 @@
+#!/bin/bash
+export HSA_OVERRIDE_GFX_VERSION=10.1.0
+export HSA_ENABLE_SDMA=0
+export HIP_VISIBLE_DEVICES=0
+
+cd /home/fabian/ComfyUI
+source venv/bin/activate
+
+python3 << 'PYEOF'
+import torch
+import time
+import os
+
+print(f'PyTorch: {torch.__version__}')
+print(f'CUDA: {torch.cuda.is_available()}')
+if torch.cuda.is_available():
+    print(f'Device: {torch.cuda.get_device_name(0)}')
+else:
+    print('NO CUDA')
+    os._exit(1)
+
+print()
+
+# Test 1: Small matmul
+print('=== Test 1: Small matmul 256x256 fp32 ===')
+try:
+    a = torch.randn(256, 256, device='cuda', dtype=torch.float32)
+    b = torch.randn(256, 256, device='cuda', dtype=torch.float32)
+    torch.cuda.synchronize()
+    t = time.time()
+    for _ in range(10):
+        c = torch.mm(a, b)
+    torch.cuda.synchronize()
+    print(f'  OK: {time.time()-t:.3f}s')
+    del a, b, c
+except Exception as e:
+    print(f'  FAIL: {e}')
+
+# Test 2: Medium matmul
+print('=== Test 2: matmul 1024x1024 fp32 ===')
+try:
+    a = torch.randn(1024, 1024, device='cuda', dtype=torch.float32)
+    b = torch.randn(1024, 1024, device='cuda', dtype=torch.float32)
+    torch.cuda.synchronize()
+    t = time.time()
+    c = torch.mm(a, b)
+    torch.cuda.synchronize()
+    print(f'  OK: {time.time()-t:.3f}s')
+    del a, b, c
+except Exception as e:
+    print(f'  FAIL: {e}')
+
+# Test 3: Large matmul
+print('=== Test 3: matmul 2048x2048 fp32 ===')
+try:
+    a = torch.randn(2048, 2048, device='cuda', dtype=torch.float32)
+    b = torch.randn(2048, 2048, device='cuda', dtype=torch.float32)
+    torch.cuda.synchronize()
+    t = time.time()
+    c = torch.mm(a, b)
+    torch.cuda.synchronize()
+    print(f'  OK: {time.time()-t:.3f}s')
+    del a, b, c
+except Exception as e:
+    print(f'  FAIL: {e}')
+
+# Test 4: fp16
+print('=== Test 4: matmul 2048x2048 fp16 ===')
+try:
+    a = torch.randn(2048, 2048, device='cuda', dtype=torch.float16)
+    b = torch.randn(2048, 2048, device='cuda', dtype=torch.float16)
+    torch.cuda.synchronize()
+    t = time.time()
+    c = torch.mm(a, b)
+    torch.cuda.synchronize()
+    print(f'  OK: {time.time()-t:.3f}s')
+    del a, b, c
+except Exception as e:
+    print(f'  FAIL: {e}')
+
+# Test 5: Conv2d
+print('=== Test 5: Conv2d 32ch fp32 ===')
+try:
+    conv = torch.nn.Conv2d(32, 32, 3, padding=1).cuda().float()
+    x = torch.randn(1, 32, 32, 32, device='cuda', dtype=torch.float32)
+    torch.cuda.synchronize()
+    t = time.time()
+    y = conv(x)
+    torch.cuda.synchronize()
+    print(f'  OK: {time.time()-t:.3f}s')
+    del conv, x, y
+except Exception as e:
+    print(f'  FAIL: {e}')
+
+# Test 6: BMM (attention)
+print('=== Test 6: BMM 4x512x64 fp32 ===')
+try:
+    q = torch.randn(1, 4, 512, 64, device='cuda', dtype=torch.float32)
+    k = torch.randn(1, 4, 512, 64, device='cuda', dtype=torch.float32)
+    torch.cuda.synchronize()
+    t = time.time()
+    attn = torch.matmul(q, k.transpose(-2, -1))
+    torch.cuda.synchronize()
+    print(f'  OK: {time.time()-t:.3f}s')
+    del q, k, attn
+except Exception as e:
+    print(f'  FAIL: {e}')
+
+# Test 7: Linear (typical model layer)
+print('=== Test 7: Linear 3072->3072 fp32 ===')
+try:
+    lin = torch.nn.Linear(3072, 3072).cuda().float()
+    x = torch.randn(1, 256, 3072, device='cuda', dtype=torch.float32)
+    torch.cuda.synchronize()
+    t = time.time()
+    y = lin(x)
+    torch.cuda.synchronize()
+    print(f'  OK: {time.time()-t:.3f}s')
+    del lin, x, y
+except Exception as e:
+    print(f'  FAIL: {e}')
+
+print()
+print('=== ALL TESTS COMPLETE ===')
+torch.cuda.synchronize()
+os._exit(0)
+PYEOF
+echo "Script exit: $?"