|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| """Bisect: base+adapter (no merge) vs merged checkpoint.
|
|
|
| If base+adapter emits real newlines, the MERGE is what breaks decoding.
|
| If it also emits literal backslash-n, the ADAPTER (i.e. the training) is at fault.
|
| """
|
| import os
|
| import re
|
| import sys
|
|
|
| import torch
|
| from peft import PeftModel
|
| from transformers import (AutoModelForCausalLM, AutoTokenizer,
|
| BitsAndBytesConfig)
|
|
|
| BASE = "unsloth/Qwen3-Coder-30B-A3B-Instruct"
|
| ADAPTER = "Taimwe/securecoder-30b-pro-v2"
|
|
|
| PROMPTS = [
|
| "Write a Python function `def is_palindrome(s: str) -> bool:` that checks whether a string reads the same forwards and backwards, ignoring case and non-alphanumeric characters.",
|
| "Write a Python function `def two_sum(nums: list[int], target: int) -> list[int]:` returning the indices of the two numbers adding to target, or an empty list.",
|
| "Write a Python function `def flatten(nested: list) -> list:` that flattens an arbitrarily nested list.",
|
| ]
|
|
|
| token = os.environ.get("HF_TOKEN")
|
| tok = AutoTokenizer.from_pretrained(BASE, token=token)
|
| bnb = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_quant_type="nf4",
|
| bnb_4bit_compute_dtype=torch.bfloat16,
|
| bnb_4bit_use_double_quant=True)
|
| model = AutoModelForCausalLM.from_pretrained(
|
| BASE, token=token, quantization_config=bnb,
|
| dtype=torch.bfloat16, device_map="auto")
|
| model = PeftModel.from_pretrained(model, ADAPTER, token=token)
|
| model.eval()
|
|
|
| ok = 0
|
| for i, p in enumerate(PROMPTS, 1):
|
| text = tok.apply_chat_template([{"role": "user", "content": p}],
|
| tokenize=False, add_generation_prompt=True)
|
| ids = tok(text, return_tensors="pt", add_special_tokens=False).input_ids.to(model.device)
|
| with torch.no_grad():
|
| gen = model.generate(ids, max_new_tokens=1024, do_sample=False,
|
| eos_token_id=tok.eos_token_id, pad_token_id=tok.eos_token_id)
|
| new_ids = gen[0, ids.shape[-1]:]
|
| reply = tok.decode(new_ids, skip_special_tokens=True)
|
|
|
| has_real_nl = "\n" in reply
|
| has_lit = "\\n" in reply
|
| blocks = re.findall(r"```(?:python)?\s*\n(.*?)```", reply, re.S)
|
| block = max(blocks, key=len) if blocks else None
|
| if block is None:
|
| s = reply.find("def ")
|
| block = reply[s:] if s >= 0 else None
|
| err = None
|
| if block:
|
| try:
|
| compile(block, "<t>", "exec")
|
| except Exception as exc:
|
| err = "%s: %s" % (type(exc).__name__, exc)
|
| if not err:
|
| ok += 1
|
| print("\n" + "=" * 72)
|
| print("PROMPT %d new_tokens=%d fenced=%d real_nl=%s literal_backslash_n=%s"
|
| % (i, len(new_ids), len(blocks), has_real_nl, has_lit))
|
| print("COMPILE:", err or "OK")
|
| print("-" * 72)
|
| print(reply[:1200])
|
|
|
| print("\n\nSUMMARY base+adapter: %d/%d compiled cleanly" % (ok, len(PROMPTS))) |
