File size: 4,216 Bytes
fa2d87b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 | #!/usr/bin/env python3
from __future__ import annotations
import argparse
import gc
import json
import os
import resource
import time
from pathlib import Path
from typing import Any
import torch
import orbitquant # noqa: F401 - registers the HF integrations
from orbitquant.adaln import RTNInt4Linear
from orbitquant.layers import OrbitQuantLinear
from verification_policy import inventory_failure
COMPONENTS = {
"transformer": ("diffusers", "MiniMaxH3Transformer3DModel"),
"transformer_ref": ("diffusers", "MiniMaxH3Transformer3DModel"),
"vae": ("diffusers", "AutoencoderKLMiniMaxH3"),
"audio_vae": ("diffusers", "AutoencoderKLMiniMaxH3Audio"),
"text_encoder": ("transformers", "Qwen3VLForConditionalGeneration"),
}
def resolve_class(framework: str, class_name: str) -> type[torch.nn.Module]:
module = __import__(framework, fromlist=[class_name])
return getattr(module, class_name)
def bytes_for_state(module: torch.nn.Module) -> int:
return sum(value.numel() * value.element_size() for value in module.state_dict().values())
def main() -> int:
parser = argparse.ArgumentParser()
parser.add_argument("--release", type=Path, required=True)
parser.add_argument("--component", choices=sorted(COMPONENTS), required=True)
parser.add_argument("--output", type=Path, required=True)
args = parser.parse_args()
framework, class_name = COMPONENTS[args.component]
cls = resolve_class(framework, class_name)
component_dir = args.release / args.component
manifest = json.loads((args.release / "quantization_manifest.json").read_text())
component_record = next(
item for item in manifest["components"] if item["component"] == args.component
)
component_mode = component_record["component_mode"]
started = time.perf_counter()
torch.cuda.reset_peak_memory_stats()
model = cls.from_pretrained(component_dir, low_cpu_mem_usage=True)
load_seconds = time.perf_counter() - started
model.eval().requires_grad_(False)
orbit_names: list[str] = []
adaln_names: list[str] = []
linear_names: list[str] = []
full_cache_names: list[str] = []
for name, module in model.named_modules():
if isinstance(module, OrbitQuantLinear):
orbit_names.append(name)
cache = getattr(module, "_dequantized_weight_cache", None)
if isinstance(cache, torch.Tensor) and cache.numel():
full_cache_names.append(name)
elif isinstance(module, RTNInt4Linear):
adaln_names.append(name)
elif isinstance(module, torch.nn.Linear):
linear_names.append(name)
config = getattr(model, "config", None)
config_dict: dict[str, Any] = config.to_dict() if hasattr(config, "to_dict") else {}
quant_config = config_dict.get("quantization_config")
report = {
"status": "pass",
"component": args.component,
"component_mode": component_mode,
"framework": framework,
"class_name": type(model).__name__,
"load_seconds": load_seconds,
"orbitquant_module_count": len(orbit_names),
"adaln_int4_module_count": len(adaln_names),
"bf16_linear_module_count": len(linear_names),
"full_dequantized_cache_count": len(full_cache_names),
"resident_state_bytes": bytes_for_state(model),
"quantization_config": quant_config,
"rss_peak_bytes": resource.getrusage(resource.RUSAGE_SELF).ru_maxrss * 1024,
"gpu_peak_allocated_bytes": torch.cuda.max_memory_allocated(),
"gpu": torch.cuda.get_device_name(),
"pid": os.getpid(),
}
failure = inventory_failure(
component_mode,
orbit_count=len(orbit_names),
adaln_count=len(adaln_names),
cache_count=len(full_cache_names),
)
if failure:
report["status"] = "fail"
report["reason"] = failure
args.output.parent.mkdir(parents=True, exist_ok=True)
args.output.write_text(json.dumps(report, indent=2) + "\n")
print(json.dumps(report))
del model
gc.collect()
torch.cuda.empty_cache()
return 0 if report["status"] == "pass" else 1
if __name__ == "__main__":
raise SystemExit(main())
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