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"""
Phase 0: Hardware Validation for Quillan-Ronin Transplant
Verifies source models, RAM, GPU, and dependencies.
"""
import os
import sys
import time
import json
import logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(message)s",
handlers=[
logging.FileHandler("quillan_build.log"),
logging.StreamHandler()
]
)
logger = logging.getLogger("HardwareCheck")
RESULTS = {}
def check_dependencies():
"""Check required Python packages."""
logger.info("=== CHECKING DEPENDENCIES ===")
required = {
"torch": "PyTorch",
"numpy": "NumPy",
"safetensors": "SafeTensors",
}
optional = {
"psutil": "psutil (Phoenix affinity)",
"scipy": "scipy (E_ICE Monte Carlo)",
"lancedb": "LanceDB (memory)",
"pyarrow": "PyArrow (LanceDB)",
"pyopencl": "PyOpenCL (OpenCL swarm)",
}
missing_req = []
missing_opt = []
for pkg, name in required.items():
try:
mod = __import__(pkg)
ver = getattr(mod, "__version__", "unknown")
logger.info(f" [OK] {name}: {ver}")
except ImportError:
missing_req.append(name)
logger.error(f" [FAIL] {name}: MISSING (required)")
for pkg, name in optional.items():
try:
mod = __import__(pkg)
ver = getattr(mod, "__version__", "unknown")
logger.info(f" [OK] {name}: {ver}")
except ImportError:
missing_opt.append(name)
logger.warning(f" [WARN] {name}: MISSING (optional)")
RESULTS["dependencies"] = {
"required_missing": missing_req,
"optional_missing": missing_opt,
}
if missing_req:
logger.error(f"FATAL: Missing required packages: {missing_req}")
return False
return True
def check_ram():
"""Check available RAM."""
logger.info("=== CHECKING RAM ===")
try:
import psutil
mem = psutil.virtual_memory()
total_gb = mem.total / 1e9
avail_gb = mem.available / 1e9
logger.info(f" Total: {total_gb:.1f} GB")
logger.info(f" Available: {avail_gb:.1f} GB")
logger.info(f" Used: {mem.used / 1e9:.1f} GB")
RESULTS["ram"] = {"total_gb": total_gb, "available_gb": avail_gb}
return avail_gb > 12 # Need at least 12GB free
except ImportError:
logger.warning(" psutil not available, skipping RAM check")
RESULTS["ram"] = {"status": "skipped"}
return True
def check_gpu():
"""Check GPU availability."""
logger.info("=== CHECKING GPU ===")
import torch
cuda_available = torch.cuda.is_available()
if cuda_available:
gpu_name = torch.cuda.get_device_name(0)
vram = torch.cuda.get_device_properties(0).total_memory / 1e9
logger.info(f" CUDA GPU: {gpu_name} ({vram:.1f} GB VRAM)")
RESULTS["gpu"] = {"name": gpu_name, "vram_gb": vram, "cuda": True}
else:
logger.info(" No CUDA GPU detected")
RESULTS["gpu"] = {"cuda": False}
# Check OpenCL
try:
import pyopencl as cl
platforms = cl.get_platforms()
for p in platforms:
devices = p.get_devices(cl.device_type.GPU)
for d in devices:
logger.info(f" OpenCL GPU: {d.name}")
RESULTS["gpu"]["opencl"] = True
except (ImportError, Exception) as e:
logger.warning(f" OpenCL not available: {e}")
RESULTS["gpu"]["opencl"] = False
return True
def check_source_models():
"""Verify all source models exist and can be loaded."""
logger.info("=== CHECKING SOURCE MODELS ===")
base = r"C:\Users\Admin\Quillan-Ronin\Quillan-v4.2-model"
models = {
"llama": os.path.join(base, "llama model.safetensors"),
"qwen": os.path.join(base, "qwen model.safetensors"),
"bitnet": os.path.join(base, "bitnet model.safetensors"),
"bitnet_copy": os.path.join(base, "model.safetensors"),
}
from safetensors import safe_open
model_info = {}
for name, path in models.items():
if not os.path.exists(path):
logger.error(f" [FAIL] {name}: NOT FOUND at {path}")
return False
size_gb = os.path.getsize(path) / 1e9
logger.info(f" Loading {name} ({size_gb:.2f} GB)...")
try:
with safe_open(path, framework='pt') as f:
keys = list(f.keys())
# Get first tensor to check shape
first_key = keys[0]
first_tensor = f.get_tensor(first_key)
# Get embedding shape
emb_keys = [k for k in keys if 'embed' in k.lower()]
emb_shape = None
if emb_keys:
emb_tensor = f.get_tensor(emb_keys[0])
emb_shape = list(emb_tensor.shape)
# Get layer count
layer_nums = set()
for k in keys:
if 'layers.' in k:
parts = k.split('.')
for i, p in enumerate(parts):
if p == 'layers' and i+1 < len(parts):
try:
layer_nums.add(int(parts[i+1]))
except ValueError:
pass
model_info[name] = {
"size_gb": size_gb,
"num_tensors": len(keys),
"num_layers": len(layer_nums),
"embedding_shape": emb_shape,
"dtype": str(first_tensor.dtype),
}
logger.info(f" [OK] {name}: {len(keys)} tensors, {len(layer_nums)} layers, embedding={emb_shape}")
except Exception as e:
logger.error(f" [FAIL] {name}: FAILED to load - {e}")
return False
RESULTS["source_models"] = model_info
# Verify total RAM needed
total_model_gb = sum(m["size_gb"] for m in model_info.values())
logger.info(f" Total model size: {total_model_gb:.2f} GB")
RESULTS["total_model_gb"] = total_model_gb
return True
def check_pytorch():
"""Check PyTorch configuration."""
logger.info("=== CHECKING PYTORCH ===")
import torch
logger.info(f" Version: {torch.__version__}")
logger.info(f" CUDA available: {torch.cuda.is_available()}")
logger.info(f" CPU threads: {torch.get_num_threads()}")
logger.info(f" CPU count: {torch.get_num_interop_threads()}")
# Set threads for i5-7500 (4 cores)
torch.set_num_threads(2) # Cores 2-3 via Phoenix affinity
torch.set_num_interop_threads(2)
logger.info(f" Threads set to: {torch.get_num_threads()} (Phoenix affinity)")
RESULTS["pytorch"] = {
"version": torch.__version__,
"cuda": torch.cuda.is_available(),
"threads": torch.get_num_threads(),
}
return True
def main():
logger.info("=" * 60)
logger.info("QUILLAN-RONIN PHASE 0: HARDWARE VALIDATION")
logger.info("=" * 60)
start = time.time()
steps = [
("Dependencies", check_dependencies),
("RAM", check_ram),
("GPU", check_gpu),
("PyTorch", check_pytorch),
("Source Models", check_source_models),
]
all_pass = True
for name, check_fn in steps:
try:
passed = check_fn()
if not passed:
all_pass = False
logger.error(f" FAILED: {name}")
except Exception as e:
all_pass = False
logger.error(f" ERROR in {name}: {e}")
elapsed = time.time() - start
logger.info("=" * 60)
logger.info(f"PHASE 0 COMPLETE: {'PASS' if all_pass else 'FAIL'} ({elapsed:.1f}s)")
logger.info("=" * 60)
# Save results
RESULTS["status"] = "PASS" if all_pass else "FAIL"
RESULTS["elapsed_seconds"] = elapsed
with open("hardware_check_results.json", "w") as f:
json.dump(RESULTS, f, indent=2, default=str)
logger.info(f"Results saved to hardware_check_results.json")
return 0 if all_pass else 1
if __name__ == "__main__":
sys.exit(main())
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