vbatts/llama.cpp
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*.py: fix flake8 warnings

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This commit is contained in:
brian khuu 2024-04-30 02:36:00 +10:00
parent 5e5e74e3b8
commit fcc5a5e0fe
6 changed files with 101 additions and 93 deletions
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2
.flake8
View file

@ -1,4 +1,4 @@
[flake8]
max-line-length = 125
ignore = E203,E211,E221,E225,E231,E241,E251,E261,E266,E501,E701,E704,W503
exclude = examples/*,examples/*/**,*/**/__init__.py,convert-hf-to-gguf-update.py
exclude = examples/*,examples/*/**,*/**/__init__.py

130
convert-hf-to-gguf-update.py
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@ -21,6 +21,7 @@
# TODO: automate the update of convert-hf-to-gguf.py
#
import logging
import os
import requests
import sys
@ -28,12 +29,17 @@ import json
from hashlib import sha256
from enum import IntEnum, auto
from transformers import AutoTokenizer
logger = logging.getLogger("convert-hf-to-gguf-update")
class TOKENIZER_TYPE(IntEnum):
SPM = auto()
BPE = auto()
WPM = auto()
# TODO: this string has to exercise as much pre-tokenizer functionality as possible
# will be updated with time - contributions welcome
chktxt = '\n \n\n \n\n\n \t \t\t \t\n \n \n \n \n🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български \'\'\'\'\'\'```````\"\"\"\"......!!!!!!?????? I\'ve been \'told he\'s there, \'RE you sure? \'M not sure I\'ll make it, \'D you like some tea? We\'Ve a\'lL'
@ -41,7 +47,7 @@ chktxt = '\n \n\n \n\n\n \t \t\t \t\n \n \n \n \n🚀 (normal) 😶‍
if len(sys.argv) == 2:
token = sys.argv[1]
else:
print("Usage: python convert-hf-to-gguf-update.py <huggingface_token>")
logger.info("Usage: python convert-hf-to-gguf-update.py <huggingface_token>")
sys.exit(1)
# TODO: add models here, base models preferred
@ -62,15 +68,17 @@ models = [
if not os.path.exists("models/tokenizers"):
os.makedirs("models/tokenizers")
def download_file_with_auth(url, token, save_path):
headers = {"Authorization": f"Bearer {token}"}
response = requests.get(url, headers=headers)
if response.status_code == 200:
with open(save_path, 'wb') as f:
f.write(response.content)
print(f"File {save_path} downloaded successfully")
logger.info(f"File {save_path} downloaded successfully")
else:
print(f"Failed to download file. Status code: {response.status_code}")
logger.info(f"Failed to download file. Status code: {response.status_code}")
# download the tokenizer models
for model in models:
@ -81,10 +89,10 @@ for model in models:
if not os.path.exists(f"models/tokenizers/{name}"):
os.makedirs(f"models/tokenizers/{name}")
else:
print(f"Directory models/tokenizers/{name} already exists - skipping")
logger.info(f"Directory models/tokenizers/{name} already exists - skipping")
continue
print(f"Downloading {name} to models/tokenizers/{name}")
logger.info(f"Downloading {name} to models/tokenizers/{name}")
url = f"{repo}/raw/main/config.json"
save_path = f"models/tokenizers/{name}/config.json"
@ -115,76 +123,75 @@ for model in models:
continue
# create the tokenizer
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
chktok = tokenizer.encode(chktxt)
chkhsh = sha256(str(chktok).encode()).hexdigest()
print(f"model: {name}")
print(f"tokt: {tokt}")
print(f"repo: {model['repo']}")
print(f"chktok: {chktok}")
print(f"chkhsh: {chkhsh}")
logger.info(f"model: {name}")
logger.info(f"tokt: {tokt}")
logger.info(f"repo: {model['repo']}")
logger.info(f"chktok: {chktok}")
logger.info(f"chkhsh: {chkhsh}")
# print the "pre_tokenizer" content from the tokenizer.json
with open(f"models/tokenizers/{name}/tokenizer.json", "r", encoding="utf-8") as f:
cfg = json.load(f)
pre_tokenizer = cfg["pre_tokenizer"]
print("pre_tokenizer: " + json.dumps(pre_tokenizer, indent=4))
logger.info("pre_tokenizer: " + json.dumps(pre_tokenizer, indent=4))
print(f"\n")
logger.info("")
src_ifs += f" if chkhsh == \"{chkhsh}\":\n"
src_ifs += f" # ref: {model['repo']}\n"
src_ifs += f" res = \"{name}\"\n"
src_func = ""
src_func += " def get_vocab_base_pre(self, tokenizer) -> str:\n"
src_func += " # encoding this string and hashing the resulting tokens would (hopefully) give us a unique identifier that\n"
src_func += " # is specific for the BPE pre-tokenizer used by the model\n"
src_func += " # we will use this unique identifier to write a \"tokenizer.ggml.pre\" entry in the GGUF file which we can\n"
src_func += " # use in llama.cpp to implement the same pre-tokenizer\n"
src_func += "\n"
src_func += f" chktxt = {repr(chktxt)}\n"
src_func += "\n"
src_func += " chktok = tokenizer.encode(chktxt)\n"
src_func += " chkhsh = sha256(str(chktok).encode()).hexdigest()\n"
src_func += "\n"
src_func += " print(f\"chktok: {chktok}\")\n"
src_func += " print(f\"chkhsh: {chkhsh}\")\n"
src_func += "\n"
src_func += " res = None\n"
src_func += "\n"
src_func += " # NOTE: if you get an error here, you need to update the convert-hf-to-gguf-update.py script\n"
src_func += " # or pull the latest version of the model from Huggingface\n"
src_func += " # don't edit the hashes manually!\n"
src_func += f"{src_ifs}\n"
src_func += " if res is None:\n"
src_func += " print(\"\\n\")\n"
src_func += " print(\"**************************************************************************************\")\n"
src_func += " print(\"** WARNING: The BPE pre-tokenizer was not recognized!\")\n"
src_func += " print(\"** There are 2 possible reasons for this:\")\n"
src_func += " print(\"** - the model has not been added to convert-hf-to-gguf-update.py yet\")\n"
src_func += " print(\"** - the pre-tokenization config has changed upstream\")\n"
src_func += " print(\"** Check your model files and convert-hf-to-gguf-update.py and update them accordingly.\")\n"
src_func += " print(\"** ref: https://github.com/ggerganov/llama.cpp/pull/6920\")\n"
src_func += " print(\"**\")\n"
src_func += " print(f\"** chkhsh: {chkhsh}\")\n"
src_func += " print(\"**************************************************************************************\")\n"
src_func += " print(\"\\n\")\n"
src_func += " raise NotImplementedError(\"BPE pre-tokenizer was not recognized - update get_vocab_base_pre()\")\n"
src_func += "\n"
src_func += " print(f\"tokenizer.ggml.pre: {res}\")\n"
src_func += " print(f\"chkhsh: {chkhsh}\")\n"
src_func += "\n"
src_func += " return res\n"
src_func = "" # noqa: E222
src_func += " def get_vocab_base_pre(self, tokenizer) -> str:\n" # noqa: E222
src_func += " # encoding this string and hashing the resulting tokens would (hopefully) give us a unique identifier that\n" # noqa: E222
src_func += " # is specific for the BPE pre-tokenizer used by the model\n" # noqa: E222
src_func += " # we will use this unique identifier to write a \"tokenizer.ggml.pre\" entry in the GGUF file which we can\n" # noqa: E222
src_func += " # use in llama.cpp to implement the same pre-tokenizer\n" # noqa: E222
src_func += "\n" # noqa: E222
src_func += f" chktxt = {repr(chktxt)}\n" # noqa: E222
src_func += "\n" # noqa: E222
src_func += " chktok = tokenizer.encode(chktxt)\n" # noqa: E222
src_func += " chkhsh = sha256(str(chktok).encode()).hexdigest()\n" # noqa: E222
src_func += "\n" # noqa: E222
src_func += " print(f\"chktok: {chktok}\")\n" # noqa: E222
src_func += " print(f\"chkhsh: {chkhsh}\")\n" # noqa: E222
src_func += "\n" # noqa: E222
src_func += " res = None\n" # noqa: E222
src_func += "\n" # noqa: E222
src_func += " # NOTE: if you get an error here, you need to update the convert-hf-to-gguf-update.py script\n" # noqa: E222
src_func += " # or pull the latest version of the model from Huggingface\n" # noqa: E222
src_func += " # don't edit the hashes manually!\n" # noqa: E222
src_func += f"{src_ifs}\n" # noqa: E222
src_func += " if res is None:\n" # noqa: E222
src_func += " print(\"\\n\")\n" # noqa: E222
src_func += " print(\"**************************************************************************************\")\n" # noqa: E222
src_func += " print(\"** WARNING: The BPE pre-tokenizer was not recognized!\")\n" # noqa: E222
src_func += " print(\"** There are 2 possible reasons for this:\")\n" # noqa: E222
src_func += " print(\"** - the model has not been added to convert-hf-to-gguf-update.py yet\")\n" # noqa: E222
src_func += " print(\"** - the pre-tokenization config has changed upstream\")\n" # noqa: E222
src_func += " print(\"** Check your model files and convert-hf-to-gguf-update.py and update them accordingly.\")\n" # noqa: E222
src_func += " print(\"** ref: https://github.com/ggerganov/llama.cpp/pull/6920\")\n" # noqa: E222
src_func += " print(\"**\")\n" # noqa: E222
src_func += " print(f\"** chkhsh: {chkhsh}\")\n" # noqa: E222
src_func += " print(\"**************************************************************************************\")\n" # noqa: E222
src_func += " print(\"\\n\")\n" # noqa: E222
src_func += " raise NotImplementedError(\"BPE pre-tokenizer was not recognized - update get_vocab_base_pre()\")\n" # noqa: E222
src_func += "\n" # noqa: E222
src_func += " print(f\"tokenizer.ggml.pre: {res}\")\n" # noqa: E222
src_func += " print(f\"chkhsh: {chkhsh}\")\n" # noqa: E222
src_func += "\n" # noqa: E222
src_func += " return res\n" # noqa: E222
print(src_func)
print(src_func) # noqa: NP100
print("\n")
print("!!! Copy-paste the function above into convert-hf-to-gguf.py !!!")
print("\n")
logger.info("\n")
logger.info("!!! Copy-paste the function above into convert-hf-to-gguf.py !!!")
logger.info("\n")
# generate tests for each tokenizer model
@ -250,7 +257,6 @@ for model in models:
tokt = model["tokt"]
# create the tokenizer
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
with open(f"models/ggml-vocab-{name}.gguf.inp", "w", encoding="utf-8") as f:
@ -265,15 +271,15 @@ for model in models:
f.write(f" {r}")
f.write("\n")
print(f"Tests for {name} written in ./models/ggml-vocab-{name}.gguf.*")
logger.info(f"Tests for {name} written in ./models/ggml-vocab-{name}.gguf.*")
# generate commands for creating vocab files
print("\nRun the following commands to generate the vocab files for testing:\n")
logger.info("\nRun the following commands to generate the vocab files for testing:\n")
for model in models:
name = model["name"]
print(f"python3 convert-hf-to-gguf.py models/tokenizers/{name}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only")
logger.info(f"python3 convert-hf-to-gguf.py models/tokenizers/{name}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only")
print("\n")
logger.info("\n")

32
convert-hf-to-gguf.py
View file

@ -276,8 +276,8 @@ class Model(ABC):
chktok = tokenizer.encode(chktxt)
chkhsh = sha256(str(chktok).encode()).hexdigest()
print(f"chktok: {chktok}")
print(f"chkhsh: {chkhsh}")
logger.debug(f"chktok: {chktok}")
logger.debug(f"chkhsh: {chkhsh}")
res = None
@ -310,22 +310,22 @@ class Model(ABC):
res = "gpt-2"
if res is None:
print("\n")
print("**************************************************************************************")
print("** WARNING: The BPE pre-tokenizer was not recognized!")
print("** There are 2 possible reasons for this:")
print("** - the model has not been added to convert-hf-to-gguf-update.py yet")
print("** - the pre-tokenization config has changed upstream")
print("** Check your model files and convert-hf-to-gguf-update.py and update them accordingly.")
print("** ref: https://github.com/ggerganov/llama.cpp/pull/6920")
print("**")
print(f"** chkhsh: {chkhsh}")
print("**************************************************************************************")
print("\n")
logger.warning("\n")
logger.warning("**************************************************************************************")
logger.warning("** WARNING: The BPE pre-tokenizer was not recognized!")
logger.warning("** There are 2 possible reasons for this:")
logger.warning("** - the model has not been added to convert-hf-to-gguf-update.py yet")
logger.warning("** - the pre-tokenization config has changed upstream")
logger.warning("** Check your model files and convert-hf-to-gguf-update.py and update them accordingly.")
logger.warning("** ref: https://github.com/ggerganov/llama.cpp/pull/6920")
logger.warning("**")
logger.warning(f"** chkhsh: {chkhsh}")
logger.warning("**************************************************************************************")
logger.warning("\n")
raise NotImplementedError("BPE pre-tokenizer was not recognized - update get_vocab_base_pre()")
print(f"tokenizer.ggml.pre: {res}")
print(f"chkhsh: {chkhsh}")
logger.debug(f"tokenizer.ggml.pre: {res}")
logger.debug(f"chkhsh: {chkhsh}")
return res

4
gguf-py/gguf/gguf_reader.py
View file

@ -4,6 +4,7 @@
#
from __future__ import annotations
import logging
import os
from collections import OrderedDict
from typing import Any, Literal, NamedTuple, TypeVar, Union
@ -27,6 +28,7 @@ from gguf.constants import (
GGUFValueType,
)
logger = logging.getLogger(__name__)
READER_SUPPORTED_VERSIONS = [2, GGUF_VERSION]
@ -142,7 +144,7 @@ class GGUFReader:
# TODO: add option to generate error on duplicate keys
# raise KeyError(f'Duplicate {field.name} already in list at offset {field.offset}')
print(f'Warning: Duplicate key {field.name} at offset {field.offset}')
logger.warning(f'Duplicate key {field.name} at offset {field.offset}')
self.fields[field.name + '_{}'.format(field.offset)] = field
else:
self.fields[field.name] = field

2
tests/test-tokenizer-0-bpe.py
View file

@ -12,7 +12,7 @@ import argparse
from transformers import AutoTokenizer
logger = logging.getLogger("convert")
logger = logging.getLogger("test-tokenizer-0-bpe")
parser = argparse.ArgumentParser()
parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file")

2
tests/test-tokenizer-0-spm.py
View file

@ -12,7 +12,7 @@ import argparse
from sentencepiece import SentencePieceProcessor
logger = logging.getLogger("test-tokenizer-0-llama")
logger = logging.getLogger("test-tokenizer-0-spm")
parser = argparse.ArgumentParser()
parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file")