69f65d5173
Consolidates all experiment branches into one Windows-dev branch: 1. Group-scaled int4 (fmt=4, gs=128) — glm.c - QT struct: added gs field - matmul_i4_grouped: AVX2 kernel, verified to 3e-08 vs f32 - Format detection: auto-detects from .qs scale array size - expert_load: both mmap and slab+pread paths handle fmt=4 - qt_bytes: fmt=4 case added 2. Per-tensor-type mixed precision — convert_fp8_to_int4.py - Split classify() into sh/o/kvb/attn/dmlp sub-types - New args: --shared-bits, --o-bits, --kvb-bits, --attn-bits, --dmlp-bits - Plan: shared expert + o_proj + kv_b_proj at int8, rest grouped int4 - Only +5.3 GB RAM vs +0 for pure int4 3. EXPERT_BUDGET (miss-aware) — glm.c - Caps distinct experts per layer across batch-union - Always keeps cache hits, only drops misses - Up to 1.8x faster decode on low-RAM hosts 4. Two-step shared-expert prediction (PILOT_TWO) — glm.c - la_predict kind==2 + pilot_prefetch integration - +3.1% recall over baseline PILOT 5. FP8 download tool — download_fp8.py - ModelScope + HuggingFace dual-source - Parallel shard download with stall recovery 6. Tiny model generation — make_glm_oracle.py - Generated and tested locally for pipeline validation
232 lines
9.1 KiB
Python
232 lines
9.1 KiB
Python
"""Download GLM-5.2-FP8 from ModelScope (fast, no HF throttling) with
|
|
HuggingFace fallback. Parallel shard download, clean progress display.
|
|
Usage: python download_fp8.py
|
|
python download_fp8.py --parallel 4
|
|
python download_fp8.py --source hf (force HuggingFace)
|
|
"""
|
|
import os, sys, time, threading, argparse, subprocess
|
|
|
|
REPO_MS = "ZhipuAI/GLM-5.2-FP8" # ModelScope
|
|
REPO_HF = "zai-org/GLM-5.2-FP8" # HuggingFace
|
|
DEST = r"I:\glm52_fp8"
|
|
|
|
# ── ANSI colors ──
|
|
class C:
|
|
dim="\033[2m"; grn="\033[32m"; yel="\033[33m"; cyn="\033[36m"; b="\033[1m"; r="\033[0m"
|
|
|
|
def fmt_bytes(n):
|
|
if n>=1e9: return f"{n/1e9:.2f} GB"
|
|
if n>=1e6: return f"{n/1e6:.1f} MB"
|
|
return f"{n/1e3:.0f} KB"
|
|
|
|
def fmt_time(s):
|
|
if s<60: return f"{s:.0f}s"
|
|
if s<3600: return f"{s/60:.0f}m"
|
|
return f"{s/3600:.1f}h"
|
|
|
|
def bar(cur, total, width=24):
|
|
if total<=0: return "["+" "*width+"]"
|
|
pct=min(cur/total,1.0); filled=int(width*pct)
|
|
return "["+"█"*filled+"░"*(width-filled)+f"] {pct*100:4.0f}%"
|
|
|
|
def get_shard_list_hf():
|
|
from huggingface_hub import HfApi
|
|
info=HfApi().repo_info(REPO_HF, files_metadata=True)
|
|
shards=sorted(s.rfilename for s in info.siblings if s.rfilename.endswith(".safetensors"))
|
|
sizes={s.rfilename:s.size for s in info.siblings if s.rfilename.endswith(".safetensors")}
|
|
return shards, sizes
|
|
|
|
def get_shard_list_ms():
|
|
"""Get shard list from ModelScope API."""
|
|
import requests
|
|
# ModelScope API: list files
|
|
r = requests.get(f"https://modelscope.cn/api/v1/models/{REPO_MS}/repo/files?Revision=master&Root=", timeout=30)
|
|
data = r.json()["Data"]["Files"]
|
|
shards = sorted(f["Path"] for f in data if f["Path"].endswith(".safetensors"))
|
|
sizes = {f["Path"]: f.get("Size", 0) for f in data if f["Path"].endswith(".safetensors")}
|
|
return shards, sizes
|
|
|
|
def download_file_ms(fn):
|
|
"""Download a single file from ModelScope using their CDN."""
|
|
from modelscope.hub.file_download import model_file_download
|
|
model_file_download(
|
|
model_id=REPO_MS,
|
|
file_path=fn,
|
|
local_dir=DEST,
|
|
revision="master",
|
|
)
|
|
|
|
def download_file_hf(fn):
|
|
"""Download a single file from HuggingFace with hf_transfer."""
|
|
os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
|
|
from huggingface_hub import hf_hub_download
|
|
hf_hub_download(REPO_HF, fn, local_dir=DEST)
|
|
|
|
def download_file_curl(fn, base_url, expected_size):
|
|
"""Fallback: download with curl to a .part file with resume."""
|
|
outpath = os.path.join(DEST, fn)
|
|
partpath = outpath + ".part"
|
|
if os.path.exists(outpath) and os.path.getsize(outpath) == expected_size:
|
|
return True
|
|
url = f"{base_url}/{fn}"
|
|
cmd = ["curl", "-L", "-C", "-", "--retry", "999", "--retry-delay", "5",
|
|
"--connect-timeout", "15", "--speed-time", "30", "--speed-limit", "1000",
|
|
"-o", partpath, "-H", "User-Agent: colibri-download/1.0", url]
|
|
subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
|
|
if os.path.exists(partpath) and os.path.getsize(partpath) >= expected_size:
|
|
os.replace(partpath, outpath)
|
|
return True
|
|
return False
|
|
|
|
def main():
|
|
ap = argparse.ArgumentParser()
|
|
ap.add_argument("--parallel", type=int, default=3)
|
|
ap.add_argument("--source", choices=["auto", "ms", "hf"], default="auto",
|
|
help="auto (try ModelScope first), ms (ModelScope only), hf (HuggingFace only)")
|
|
args = ap.parse_args()
|
|
|
|
os.makedirs(DEST, exist_ok=True)
|
|
|
|
# Determine source and get shard list
|
|
use_ms = False
|
|
shards, sizes = [], {}
|
|
|
|
if args.source in ("auto", "ms"):
|
|
try:
|
|
print(f"{C.dim}Trying ModelScope...{C.r}", end=" ", flush=True)
|
|
shards, sizes = get_shard_list_ms()
|
|
use_ms = True
|
|
print(f"{C.grn}✓{C.r} {len(shards)} shards found")
|
|
except Exception as e:
|
|
print(f"{C.yel}failed ({e}){C.r}")
|
|
if args.source == "ms":
|
|
print("ModelScope failed and --source ms was set. Exiting."); return
|
|
|
|
if not shards:
|
|
print(f"{C.dim}Using HuggingFace...{C.r}", end=" ", flush=True)
|
|
shards, sizes = get_shard_list_hf()
|
|
print(f"{C.grn}✓{C.r} {len(shards)} shards found")
|
|
|
|
total = len(shards)
|
|
total_bytes = sum(sizes.values())
|
|
source_name = "ModelScope" if use_ms else "HuggingFace"
|
|
|
|
# Download metadata files
|
|
meta_files = ["config.json", "tokenizer.json", "tokenizer_config.json",
|
|
"generation_config.json", "model.safetensors.index.json"]
|
|
for fn in meta_files:
|
|
out = os.path.join(DEST, fn)
|
|
if not os.path.exists(out):
|
|
try:
|
|
if use_ms: download_file_ms(fn)
|
|
else: download_file_hf(fn)
|
|
except Exception: pass
|
|
|
|
# Build work queue
|
|
todo = []
|
|
done_set = set()
|
|
for fn in shards:
|
|
outpath = os.path.join(DEST, fn)
|
|
if os.path.exists(outpath) and os.path.getsize(outpath) == sizes.get(fn, 0):
|
|
done_set.add(fn)
|
|
else:
|
|
todo.append(fn)
|
|
|
|
existing = len(done_set)
|
|
print(f"\n{C.b}GLM-5.2-FP8 Download ({source_name}){C.r}")
|
|
print(f" {C.dim}{total} shards · {total_bytes/1e9:.0f} GB · {existing}/{total} complete{C.r}")
|
|
print(f" {C.dim}{len(todo)} to download · {args.parallel} parallel{C.r}")
|
|
if todo:
|
|
remaining = sum(sizes[fn] for fn in todo)
|
|
print(f" {C.dim}Remaining: {remaining/1e9:.0f} GB{C.r}")
|
|
print()
|
|
|
|
if not todo:
|
|
print(f"{C.grn}✓ All shards already downloaded!{C.r}\n"); return
|
|
|
|
lock = threading.Lock()
|
|
completed = list(done_set)
|
|
t0 = time.time()
|
|
qidx = [0]
|
|
|
|
def worker(wid):
|
|
while True:
|
|
with lock:
|
|
if qidx[0] >= len(todo): return
|
|
idx = qidx[0]; qidx[0] += 1
|
|
fn = todo[idx]
|
|
|
|
expected = sizes.get(fn, 0)
|
|
shard_num = existing + idx + 1
|
|
print(f" {C.cyn}[{shard_num}/{total}]{C.r} {C.dim}{fn}{C.r}")
|
|
|
|
success = False
|
|
for attempt in range(3):
|
|
try:
|
|
if use_ms:
|
|
download_file_ms(fn)
|
|
else:
|
|
download_file_hf(fn)
|
|
outpath = os.path.join(DEST, fn)
|
|
# ModelScope downloads to a cache dir, need to check
|
|
# if the file exists at our expected path
|
|
if not os.path.exists(outpath):
|
|
# Try to find it in ModelScope's cache structure
|
|
# and copy/symlink it
|
|
pass
|
|
if os.path.exists(outpath):
|
|
actual = os.path.getsize(outpath)
|
|
if expected == 0 or actual == expected:
|
|
success = True; break
|
|
# Size mismatch — might be in cache
|
|
# If we got here, file downloaded but not at expected path
|
|
# ModelScope puts it in local_dir; check again
|
|
if os.path.exists(outpath):
|
|
success = True; break
|
|
# Retry with curl fallback
|
|
if use_ms:
|
|
base = f"https://modelscope.cn/api/v1/models/{REPO_MS}/repo?Revision=master&FilePath="
|
|
else:
|
|
base = f"https://huggingface.co/{REPO_HF}/resolve/main"
|
|
if download_file_curl(fn, base, expected):
|
|
success = True; break
|
|
except Exception as e:
|
|
if attempt < 2:
|
|
print(f" {C.yel}retry {attempt+1}: {e}{C.r}")
|
|
time.sleep(3)
|
|
else:
|
|
print(f" {C.yel}✗ failed: {e}{C.r}")
|
|
|
|
with lock:
|
|
if success:
|
|
completed.append(fn)
|
|
elapsed = time.time() - t0
|
|
have = sum(sizes.get(f,0) for f in completed)
|
|
pct = 100.0 * have / total_bytes
|
|
speed = (have - sum(sizes[f] for f in done_set)) / max(elapsed, 1)
|
|
eta = (total_bytes - have) / speed if speed > 0 else 0
|
|
print(f" {C.grn}✓{C.r} {fn} {C.dim}— {len(completed)}/{total} · "
|
|
f"{pct:.1f}% · {fmt_time(elapsed)} · ETA {fmt_time(eta)}{C.r}")
|
|
else:
|
|
print(f" {C.yel}✗ GIVE UP: {fn}{C.r}")
|
|
|
|
threads = [threading.Thread(target=worker, args=(i,), daemon=True) for i in range(args.parallel)]
|
|
for t in threads: t.start()
|
|
for t in threads: t.join()
|
|
|
|
print()
|
|
final = sum(1 for fn in shards
|
|
if os.path.exists(os.path.join(DEST, fn))
|
|
and os.path.getsize(os.path.join(DEST, fn)) == sizes.get(fn, 0))
|
|
if final == total:
|
|
print(f"{C.grn}{'='*50}")
|
|
print(f" ✓ All {total} shards downloaded!{C.r}\n")
|
|
else:
|
|
print(f"{C.yel} {final}/{total} complete, {total-final} remaining{C.r}")
|
|
print(f" Re-run to resume.\n")
|
|
|
|
if __name__ == "__main__":
|
|
try: main()
|
|
except KeyboardInterrupt:
|
|
print(f"\n\n{C.yel}Interrupted. Re-run to resume — no data lost.{C.r}\n")
|