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 +1,95 @@
+#!/usr/bin/env python3
+"""
+BC-250: Test CLIP on CPU only (bypass GPU kernel compilation).
+"""
+import os, sys, time
+
+os.environ["HSA_OVERRIDE_GFX_VERSION"] = "10.1.0"
+os.environ["HSA_ENABLE_SDMA"] = "0"
+os.environ["HIP_VISIBLE_DEVICES"] = "0"
+os.environ["BC250_SOFTMAX_THRESHOLD"] = "512"
+
+sys.path.insert(0, "/home/fabian/ComfyUI")
+
+print("[T] Importing...", flush=True)
+import bc250_softmax_patch
+import torch
+import safetensors.torch
+
+# Check file size
+clip_path = "/home/fabian/ComfyUI/models/text_encoders/gemma2_2b_lumina2.safetensors"
+fsize = os.path.getsize(clip_path) / (1024*1024*1024)
+print(f"[T] CLIP file: {fsize:.2f} GB", flush=True)
+
+# Load directly to see what's in it
+print(f"[T] Loading safetensors headers...", flush=True)
+t0 = time.time()
+with safetensors.torch.safe_open(clip_path, framework="pt", device="cpu") as f:
+    keys = list(f.keys())
+    print(f"[T] Keys: {len(keys)}", flush=True)
+    print(f"[T] First 5 keys: {keys[:5]}", flush=True)
+    
+    # Check dtype and shapes of first key
+    first_tensor = f.get_tensor(keys[0])
+    print(f"[T] First tensor: {keys[0]} shape={first_tensor.shape} dtype={first_tensor.dtype}", flush=True)
+    
+    # Check total parameter count
+    total_params = 0
+    for k in keys:
+        t = f.get_tensor(k)
+        total_params += t.numel()
+    print(f"[T] Total params: {total_params/1e9:.2f}B", flush=True)
+
+dt = time.time() - t0
+print(f"[T] Loaded headers in {dt:.1f}s", flush=True)
+
+# Now try loading CLIP with ComfyUI but force CPU
+print(f"\n[T] Loading CLIP through ComfyUI (on CPU)...", flush=True)
+import comfy.sd
+import comfy.model_management
+import folder_paths
+
+# Monkey-patch to force CPU loading for CLIP
+_orig_get_torch_device = comfy.model_management.get_torch_device
+_orig_text_encoder_device = comfy.model_management.text_encoder_device
+_orig_text_encoder_offload = comfy.model_management.text_encoder_offload_device
+
+# Force text encoder to CPU
+comfy.model_management.text_encoder_device = lambda: torch.device("cpu")
+comfy.model_management.text_encoder_offload_device = lambda: torch.device("cpu")
+
+t1 = time.time()
+try:
+    clip = comfy.sd.load_clip(
+        ckpt_paths=[clip_path],
+        embedding_directory=None,
+        clip_type=comfy.sd.CLIPType.LUMINA2,
+    )
+    dt = time.time() - t1
+    print(f"[T] CLIP loaded in {dt:.1f}s", flush=True)
+    
+    # Test encoding
+    print(f"[T] Testing text encoding on CPU...", flush=True)
+    t2 = time.time()
+    tokens = clip.tokenize({"g": "a photo of a cat sitting on a windowsill"})
+    print(f"[T] Tokenized in {time.time()-t2:.3f}s", flush=True)
+    
+    t3 = time.time()
+    output = clip.encode_from_tokens_scheduled(tokens)
+    cond = output[0]
+    dt = time.time() - t3
+    print(f"[T] CLIP encoded in {dt:.1f}s", flush=True)
+    print(f"[T] Output shape: {cond.shape}, dtype: {cond.dtype}", flush=True)
+    print(f"\n[T] === CLIP ON CPU WORKS! ===", flush=True)
+    
+except Exception as e:
+    print(f"[T] ERROR: {e}", flush=True)
+    import traceback
+    traceback.print_exc()
+
+# Restore
+comfy.model_management.text_encoder_device = _orig_text_encoder_device
+comfy.model_management.text_encoder_offload_device = _orig_text_encoder_offload
+
+print(f"[T] Total: {time.time()-t0:.1f}s", flush=True)
+os._exit(0)