transformers/utils/check_dummies.py
Arthur 25b7f27234
Add llama4 (#37307)
* remove one of the last deps

* update fast image processor after refactor

* styling

* more quality of life improvements

* nit

* update

* cleanups

* some cleanups

* vllm updates

* update fake image token

* [convert] Fix typo

* [convert] Strip extraneous bytes from shards

* [convert] Minor fixes

* [convert] Use num_experts

* multi-image fixes in modeling + processor

* fixup size

* 128 experts

* Use default rope

* Unfuse mlp

* simplify a lot inputs embeds merging

* remove .item() 👀

* fix from review

* Address feedback

* Use None "default" for rope_scaling. Add eot.

* set seed

* return aspect ratios and bug fixes

* Moe 128 rebased (#8)

* 128 experts

* Use default rope

* Unfuse mlp

* Address feedback

* Use None "default" for rope_scaling. Add eot.

* Meta/llama quant compat (#7)

* add quant compatible model & conversion code for llama4

* fix a few issues

* fix a few issues

* minor type mapping fix

---------

Co-authored-by: Lu Fang <fanglu@fb.com>

* use a new config parameter to determine which model definition to use for MoE

---------

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Lu Fang <fanglu@fb.com>

* un-comment write_tokenizer from converting script

* remove un-used imports

* [llama4] Pop aspect_ratios from image processor output in Llama4Processor

Signed-off-by: Jon Swenson <jmswen@gmail.com>

* Fix parameter_count name

* Update src/transformers/models/llama4/configuration_llama4.py

* nit

* Add changes for no_rope, moe_layers, chunked attention. Just need to test all

* Update src/transformers/models/llama4/image_processing_llama4_fast.py

* nit

* fix post merge with main

* support flex attention

* fixes

* fix

* add layer

* small updates

* rebase and delete llm_compressor

* nit

* [llama4/mm] Add back <|image|> token that delimits global tile

* [llama4/mm] Fix Llama 4 image processing unit tests

* add explicit dtype

Signed-off-by: Jon Swenson <jmswen@gmail.com>

* sdpa works

* comment todo small

* fix model loading

Signed-off-by: Zijing Liu <liuzijing2014@gmail.com>

* revert

* nits

* small fix for TP on 1 node

* Read new params from config

* Add <|eom|>

* lol don't know how this got here

* adding fp8

* Save processor, fix chat template

* style

* Add boi/eoi tokens

We don't use them.

* fixes for now flex seems to work :)

* updates

* nits

* updates

* missking keys

* add context parallel

* update

* update

* fix

* nits

* add worldsize and make eager attn work for vision

* Ignore new key present in base models

* add tp_plan

* fix nope

Signed-off-by: Zijing Liu <liuzijing2014@gmail.com>

* minor fix

Signed-off-by: Zijing Liu <liuzijing2014@gmail.com>

* Clean up Llama4 vision model

* current updates

* add support for `attn_temperature_tuning`

* add floor scale

* add missing attn scales

* push what works, dirty trick for the device synch

* oups

* Fix pad_token_id

See
https://huggingface.co/ll-re/Llama-4-Scout-17B-16E/discussions/2/files
Confirmed in the original codebase.

* fix causallml loading

* rm

* fix tied-weights

* fix sdpa

* push current version

* should work with both short and long

* add compressed_tensos & fix fbgemm tp

* Fix flex impl

* style

* chunking

* try to revert the potentially breaking change

* fix auto factory

* fix shapes in general

* rm processing

* commit cache utils cleanup

* Fix context length

* fix

* allocate

* update tp_plan

* fix SDPA!

* Add support for sparse `Llama4TextMoe` layer from the kernel hub

* cleanup

* better merge

* update

* still broken fixing now

* nits

* revert print

* Write max_position_embeddings and max_model_length

* Update modeling_llama4.py

* Save attention_chunk_size

* Sync eos terminators

* Read initializer_range

* style

* remove `dict`

* fix

* eager should use `chunked_attention_mask`

* revert

* fixup

* fix config

* Revert "Merge pull request #36 from huggingface/sparse-llama4-moe"

This reverts commit ccda19f050, reversing
changes made to a515579aed.

* Fix typo and remove warning with compiled flex and chunked prefill

* Fix MoE vs FF (#41)

* fix

* Use correct no_rope_layers if provided one is empty list

* update tests

* fix

* skipping some tests

* fix fp8 loading

Signed-off-by: Zijing Liu <liuzijing2014@gmail.com>

* fix text geneartion pipeline

Signed-off-by: Zijing Liu <liuzijing2014@gmail.com>

* eager needs 4D mask

* fix

* Some cleanup

* fix

* update

* fix

* replace correctly module

* patch

* modulelist

* update

* update

* clean up

* Don't move to `cuda:0` in distributed mode

* restrict to compressed tensors for now

* rm print

* Docs!

* Fixes

* Update docs/source/en/model_doc/llama4.md

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Fixes

* cuda graph fix

* revert some stuff

* fixup

* styling

* Update src/transformers/models/llama4/modeling_llama4.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fixup

* commit licence, cleanup here and there and style

* more styling changes

* fix dummies

* fix and clean docstrings

* remove comment

* remove warning

* Only fast image processor is supported

* nit

* trigger CI

* fix issue with flex encoder

* fix dynamic cache

* Code quality

* Code quality

* fix more tests for now

* Code quality

* Code quality

* Nuke bunch of failing stuff

* Code quality

* Code quality

* cleanup removal of slow image processor

* ruff fix fast image processor

* fix

* fix styling

* Docs

* Repo consistency

* Repo consistency

* fix sliding window issue

* separate llama cache

* styling

* Repo consistency

* Repo consistency

* push waht works

* L4 Repo consistency

* Docs

* fix last last alst alst alst alstsaltlsltlaslt

---------

Signed-off-by: Jon Swenson <jmswen@gmail.com>
Signed-off-by: Zijing Liu <liuzijing2014@gmail.com>
Co-authored-by: yonigozlan <yoni.gozlan10@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pablo Montalvo <pablo.montalvo.leroux@gmail.com>
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
Co-authored-by: Keyun Tong <tongkeyun@gmail.com>
Co-authored-by: Zijing Liu <liuzijing2014@users.noreply.github.com>
Co-authored-by: Lu Fang <fanglu@fb.com>
Co-authored-by: Zijing Liu <liuzijing2014@gmail.com>
Co-authored-by: Jon Swenson <jmswen@gmail.com>
Co-authored-by: jmswen <jmswen@users.noreply.github.com>
Co-authored-by: MekkCyber <mekk.cyber@gmail.com>
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
Co-authored-by: Mohit Sharma <mohit21sharma.ms@gmail.com>
Co-authored-by: Yong Hoon Shin <yhshin@meta.com>
Co-authored-by: Marc Sun <marc@huggingface.co>
Co-authored-by: drisspg <drisspguessous@gmail.com>
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
Co-authored-by: Daniël de Kok <me@danieldk.eu>
Co-authored-by: Lysandre <hi@lysand.re>
Co-authored-by: Ye (Charlotte) Qi <ye.charlotte.qi@gmail.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
2025-04-05 22:02:22 +02:00

258 lines
9.2 KiB
Python

# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This script is responsible for making sure the dummies in utils/dummies_xxx.py are up to date with the main init.
Why dummies? This is to make sure that a user can always import all objects from `transformers`, even if they don't
have the necessary extra libs installed. Those objects will then raise helpful error message whenever the user tries
to access one of their methods.
Usage (from the root of the repo):
Check that the dummy files are up to date (used in `make repo-consistency`):
```bash
python utils/check_dummies.py
```
Update the dummy files if needed (used in `make fix-copies`):
```bash
python utils/check_dummies.py --fix_and_overwrite
```
"""
import argparse
import os
import re
from typing import Dict, List, Optional
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
PATH_TO_TRANSFORMERS = "src/transformers"
# Matches is_xxx_available()
_re_backend = re.compile(r"is\_([a-z_]*)_available()")
# Matches from xxx import bla
_re_single_line_import = re.compile(r"\s+from\s+\S*\s+import\s+([^\(\s].*)\n")
# Matches if not is_xxx_available()
_re_test_backend = re.compile(r"^\s+if\s+not\s+\(?is\_[a-z_]*\_available\(\)")
# Template for the dummy objects.
DUMMY_CONSTANT = """
{0} = None
"""
DUMMY_CLASS = """
class {0}(metaclass=DummyObject):
_backends = {1}
def __init__(self, *args, **kwargs):
requires_backends(self, {1})
"""
DUMMY_FUNCTION = """
def {0}(*args, **kwargs):
requires_backends({0}, {1})
"""
def find_backend(line: str) -> Optional[str]:
"""
Find one (or multiple) backend in a code line of the init.
Args:
line (`str`): A code line in an init file.
Returns:
Optional[`str`]: If one (or several) backend is found, returns it. In the case of multiple backends (the line
contains `if is_xxx_available() and `is_yyy_available()`) returns all backends joined on `_and_` (so
`xxx_and_yyy` for instance).
"""
if _re_test_backend.search(line) is None:
return None
backends = [b[0] for b in _re_backend.findall(line)]
backends.sort()
return "_and_".join(backends)
def read_init() -> Dict[str, List[str]]:
"""
Read the init and extract backend-specific objects.
Returns:
Dict[str, List[str]]: A dictionary mapping backend name to the list of object names requiring that backend.
"""
with open(os.path.join(PATH_TO_TRANSFORMERS, "__init__.py"), "r", encoding="utf-8", newline="\n") as f:
lines = f.readlines()
# Get to the point we do the actual imports for type checking
line_index = 0
while not lines[line_index].startswith("if TYPE_CHECKING"):
line_index += 1
backend_specific_objects = {}
# Go through the end of the file
while line_index < len(lines):
# If the line is an if is_backend_available, we grab all objects associated.
backend = find_backend(lines[line_index])
if backend is not None:
while not lines[line_index].startswith(" else:"):
line_index += 1
line_index += 1
objects = []
# Until we unindent, add backend objects to the list
while len(lines[line_index]) <= 1 or lines[line_index].startswith(" " * 8):
line = lines[line_index]
single_line_import_search = _re_single_line_import.search(line)
if single_line_import_search is not None:
# Single-line imports
objects.extend(single_line_import_search.groups()[0].split(", "))
elif line.startswith(" " * 12):
# Multiple-line imports (with 3 indent level)
objects.append(line[12:-2])
line_index += 1
backend_specific_objects[backend] = objects
else:
line_index += 1
return backend_specific_objects
def create_dummy_object(name: str, backend_name: str) -> str:
"""
Create the code for a dummy object.
Args:
name (`str`): The name of the object.
backend_name (`str`): The name of the backend required for that object.
Returns:
`str`: The code of the dummy object.
"""
if name.isupper():
return DUMMY_CONSTANT.format(name)
elif name.islower():
return DUMMY_FUNCTION.format(name, backend_name)
else:
return DUMMY_CLASS.format(name, backend_name)
def create_dummy_files(backend_specific_objects: Optional[Dict[str, List[str]]] = None) -> Dict[str, str]:
"""
Create the content of the dummy files.
Args:
backend_specific_objects (`Dict[str, List[str]]`, *optional*):
The mapping backend name to list of backend-specific objects. If not passed, will be obtained by calling
`read_init()`.
Returns:
`Dict[str, str]`: A dictionary mapping backend name to code of the corresponding backend file.
"""
if backend_specific_objects is None:
backend_specific_objects = read_init()
dummy_files = {}
for backend, objects in backend_specific_objects.items():
backend_name = "[" + ", ".join(f'"{b}"' for b in backend.split("_and_")) + "]"
dummy_file = "# This file is autogenerated by the command `make fix-copies`, do not edit.\n"
dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
dummy_file += "\n".join([create_dummy_object(o, backend_name) for o in objects])
dummy_files[backend] = dummy_file
return dummy_files
def check_dummies(overwrite: bool = False):
"""
Check if the dummy files are up to date and maybe `overwrite` with the right content.
Args:
overwrite (`bool`, *optional*, default to `False`):
Whether or not to overwrite the content of the dummy files. Will raise an error if they are not up to date
when `overwrite=False`.
"""
dummy_files = create_dummy_files()
# For special correspondence backend name to shortcut as used in utils/dummy_xxx_objects.py
short_names = {"torch": "pt"}
# Locate actual dummy modules and read their content.
path = os.path.join(PATH_TO_TRANSFORMERS, "utils")
dummy_file_paths = {
backend: os.path.join(path, f"dummy_{short_names.get(backend, backend)}_objects.py")
for backend in dummy_files.keys()
}
actual_dummies = {}
for backend, file_path in dummy_file_paths.items():
if os.path.isfile(file_path):
with open(file_path, "r", encoding="utf-8", newline="\n") as f:
actual_dummies[backend] = f.read()
else:
actual_dummies[backend] = ""
# Compare actual with what they should be.
for backend in dummy_files.keys():
if dummy_files[backend] != actual_dummies[backend]:
if overwrite:
print(
f"Updating transformers.utils.dummy_{short_names.get(backend, backend)}_objects.py as the main "
"__init__ has new objects."
)
with open(dummy_file_paths[backend], "w", encoding="utf-8", newline="\n") as f:
f.write(dummy_files[backend])
else:
# Temporary fix to help people identify which objects introduced are not correctly protected.
found = False
for _actual, _dummy in zip(
actual_dummies["torch"].split("class"), dummy_files["torch"].split("class")
):
if _actual != _dummy:
actual_broken = _actual
dummy_broken = _dummy
found = True
break
if not found:
print("A transient error was found with the dummies, please investigate.")
continue
raise ValueError(
"The main __init__ has objects that are not present in "
f"transformers.utils.dummy_{short_names.get(backend, backend)}_objects.py.\n"
f" It is likely the following objects are responsible, see these excerpts: \n"
f"---------------------------------- Actual -------------------------------------\n"
f" \n {actual_broken} \n"
f"---------------------------------- Dummy -------------------------------------\n"
f" \n {dummy_broken} \n"
"Run `make fix-copies` to fix this."
)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
args = parser.parse_args()
check_dummies(args.fix_and_overwrite)