scripts/compare-logprobs.py

import argparse
import requests
import json
from pathlib import Path
import logging

logger = logging.getLogger("compare-logprobs")
logging.basicConfig(level=logging.INFO)


DESCRIPTION = """
Compare logits between llama.cpp and another inference engine using OpenAI-compatible server endpoints.

Unlike compare-logits.py, it allows dumping logits from a hosted API endpoint. Useful when it's not possible to run both models locally.

Example usage:
    Step 1: Dump logits from two different servers
        python scripts/compare-logprobs.py dump logits_llama.log http://localhost:8080/v1/completions
        python scripts/compare-logprobs.py dump logits_other.log http://other-engine:8000/v1/completions

        (optionally, you can add --api-key <key> if the endpoint requires authentication)

    Step 2: Compare the dumped logits
        python scripts/compare-logprobs.py compare logits_llama.log logits_other.log report.md
"""


def get_remote_corpus(url: str, length: int) -> list[str]:
    response = requests.get(url)
    response.raise_for_status()
    corpus = response.text
    words = [w.strip() for w in corpus.strip().split(" ")]
    words = [w for w in words if "<" not in w] # make sure nothing looks like special tokens
    words = [w for w in words if len(w) > 0]  # filter out empty strings
    while len(words) < length:
        words += words
    return words[:length]


def dump_logits(
    endpoint: str,
    output_path: Path,
    input_words: list[str],
    pattern: list[tuple[bool, int]],
    api_key=None,
):
    logger.info(f"Dumping logits to {output_path} from endpoint {endpoint}...")
    words = input_words
    curr_text = ""
    n_total = sum(n for get, n in pattern if get)
    n_done = 0
    i_cur = 0
    i_total = len(words)
    with output_path.open("w") as f:
        for get, n in pattern:
            if not get:
                # skip n words
                for i in range(n):
                    curr_text += words.pop(0) + " "
                    i_cur += 1
                continue
            # get n words
            for i in range(n):
                curr_text += words.pop(0) + " "
                payload = {
                    "prompt": curr_text.strip(),
                    "temperature": 0.0,
                    "top_k": 1,
                    "max_tokens": 1,
                    "logprobs": 1,
                    "stream": False,
                }
                response = requests.post(
                    endpoint,
                    json=payload,
                    headers={"Authorization": f"Bearer {api_key}"} if api_key else {},
                )
                response.raise_for_status()
                data = response.json()
                data["__index"] = i_cur  # add index for easier debugging later
                data = json.dumps(data)
                f.write(f"{data}\n")
                n_done += 1
                i_cur += 1
                logger.info(
                    f"\n\n{data}\n\n[Step: {n_done}/{n_total} | Word: {i_cur}/{i_total}]"
                )
    logger.info(f"Logits dumped to {output_path}")


def get_token_logprobs(data: dict):
    logprobs = data["choices"][0]["logprobs"]
    if "content" in logprobs:
        # llama.cpp case
        top = logprobs["content"][0]["top_logprobs"][0]
        return top["token"], top["logprob"]
    else:
        # vllm case
        tokens = logprobs["tokens"]
        token_logprobs = logprobs["token_logprobs"]
        return tokens[0], token_logprobs[0]


def clean_text(text: str) -> str:
    return (
        "'"
        + text.replace("\n", "\\n")
        .replace("\t", "\\t")
        .replace("\r", "\\r")
        .replace("|", "\\|")
        + "'"
    )


def compare_logits(input1: Path, input2: Path, output_path: Path):
    with input1.open("r") as f1, input2.open("r") as f2, output_path.open("w") as fout:
        lines1 = f1.readlines()
        lines2 = f2.readlines()

        tab_header = [
            "idx",
            input1.name,
            "logprob_1",
            input2.name,
            "logprob_2",
            "diff (abs)",
        ]
        tab_entries = []
        tab_max_widths = [len(h) for h in tab_header]

        assert len(lines1) == len(
            lines2
        ), "Input files must have the same number of lines."

        fout.write("# Logits Comparison Report\n\n")
        for i, (line1, line2) in enumerate(zip(lines1, lines2)):
            if not line1.strip() or not line2.strip():
                continue  # skip empty lines

            data1 = json.loads(line1)
            data2 = json.loads(line2)

            idx1 = data1.get("__index", -1)
            idx2 = data2.get("__index", -1)
            if idx1 != idx2:
                logger.warning(
                    f"Warning: Mismatched indices at line {i}: {idx1} vs {idx2}"
                )

            token1, logprob1 = get_token_logprobs(data1)
            token2, logprob2 = get_token_logprobs(data2)

            token1 = clean_text(token1)
            token2 = clean_text(token2)
            abs_diff = abs(logprob1 - logprob2)

            tab_entries.append(
                (
                    str(idx1 + 1),
                    token1,
                    f"{logprob1:.4f}",
                    token2,
                    f"{logprob2:.4f}",
                    f"{(abs_diff):.4f}",
                )
            )

        for i in range(len(tab_entries)):
            for j in range(len(tab_header)):
                tab_max_widths[j] = max(tab_max_widths[j], len(tab_entries[i][j]))

        output = ""
        for j in range(len(tab_header)):
            output += f"| {tab_header[j]:<{tab_max_widths[j]}} "
        output += "|\n"
        for j in range(len(tab_header)):
            output += f"|{'-' * (tab_max_widths[j] + 2)}"
        output += "|\n"
        for entry in tab_entries:
            for j in range(len(tab_header)):
                output += f"| {entry[j]:<{tab_max_widths[j]}} "
            output += "|\n"

        logger.info("\n" + output)
        fout.write(output)
        logger.info(f"Report written to {output_path}")


def parse_pattern(pattern: str) -> list[tuple[bool, int]]:
    parts = pattern.split(",")
    result = []
    for i, part in enumerate(parts):
        n = int(part)
        if i % 2 == 0:
            result.append((True, n))  # get n words
        else:
            result.append((False, n))  # skip n words
    return result


def parse_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser(
        description=DESCRIPTION, formatter_class=argparse.RawTextHelpFormatter
    )
    subparsers = parser.add_subparsers(
        dest="verb", required=True, help="action to perform"
    )

    # dump subcommand
    parser_dump = subparsers.add_parser("dump", help="dump logits from an endpoint")
    parser_dump.add_argument(
        "output", type=Path, help="output path for dumped logits (.log)"
    )
    parser_dump.add_argument(
        "endpoint", type=str, help="OAI-compat /completions endpoint"
    )
    parser_dump.add_argument(
        "--api-key",
        type=str,
        default=None,
        help="API key for authentication (if required)",
    )
    parser_dump.add_argument(
        "--file",
        type=str,
        default="https://raw.githubusercontent.com/ggml-org/llama.cpp/eaba92c3dcc980ebe753348855d4a5d75c069997/tools/server/README.md",
        help="File containing prompt to use instead of the default (can also be an URL)",
    )
    parser_dump.add_argument(
        "--pattern",
        type=str,
        default="10,1000,10,4000,10",
        help="Pattern n_get,n_skip,... where n_get is number of words to get and n_skip is number of words to skip (num of words, NOT num of tokens)",
    )

    # compare subcommand
    parser_compare = subparsers.add_parser(
        "compare", help="compare two dumped logits files"
    )
    parser_compare.add_argument("input1", type=Path, help="first input file (.log)")
    parser_compare.add_argument("input2", type=Path, help="second input file (.log)")
    parser_compare.add_argument(
        "output", type=Path, help="output path for comparison report (.md)"
    )

    try:
        return parser.parse_args()
    except Exception as e:
        parser.print_help()
        raise e


def main():
    args = parse_args()

    if args.verb == "dump":
        pattern = parse_pattern(args.pattern)
        required_words = sum(n for _, n in pattern)
        if args.file.startswith("http"):
            input_words = get_remote_corpus(args.file, required_words)
            logger.info(f"Fetched {len(input_words)} words from remote {args.file}")
        else:
            with open(args.file, "r") as f:
                input_words = f.read().strip().split(" ")
                input_words = [w for w in input_words if len(w) > 0]  # filter out empty strings
                if len(input_words) < required_words:
                    raise ValueError(
                        f"Input file has only {len(input_words)} words, but pattern requires at least {required_words} words."
                    )
        logger.info(f"Using {len(input_words)} words")
        dump_logits(args.endpoint, args.output, input_words, pattern, args.api_key)
    elif args.verb == "compare":
        compare_logits(args.input1, args.input2, args.output)
    else:
        raise ValueError(f"Unknown verb: {args.verb}")


if __name__ == "__main__":
    main()