diff --git a/launcher/src/main.rs b/launcher/src/main.rs index 560ce181..146d83d6 100644 --- a/launcher/src/main.rs +++ b/launcher/src/main.rs @@ -716,6 +716,11 @@ fn download_convert_model(args: &Args, running: Arc) -> Result<(), L download_args.push(revision.to_string()) } + // Trust remote code for automatic peft fusion + if args.trust_remote_code { + download_args.push("--trust-remote-code".to_string()); + } + // Copy current process env let mut envs: Vec<(OsString, OsString)> = env::vars_os().collect(); diff --git a/server/poetry.lock b/server/poetry.lock index 16da22f5..ccbb7661 100644 --- a/server/poetry.lock +++ b/server/poetry.lock @@ -1,10 +1,15 @@ +# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. + [[package]] name = "accelerate" version = "0.19.0" description = "Accelerate" -category = "main" -optional = true +optional = false python-versions = ">=3.7.0" +files = [ + {file = "accelerate-0.19.0-py3-none-any.whl", hash = "sha256:2866b0bf9fff08f51e6384c95fa96725838b70f1988d1cce42e56b820d8a91dd"}, + {file = "accelerate-0.19.0.tar.gz", hash = "sha256:84920226b9e642e453ef37593ee55b956b08d8200dea4087c546c34e26157e76"}, +] [package.dependencies] numpy = ">=1.17" @@ -18,1057 +23,18 @@ dev = ["black (>=23.1,<24.0)", "datasets", "deepspeed", "evaluate", "hf-doc-buil quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.0.241)", "urllib3 (<2.0.0)"] rich = ["rich"] sagemaker = ["sagemaker"] -test_dev = ["datasets", "deepspeed", "evaluate", "scikit-learn", "scipy", "tqdm", "transformers"] -test_prod = ["parameterized", "pytest", "pytest-subtests", "pytest-xdist"] -test_trackers = ["comet-ml", "tensorboard", "wandb"] +test-dev = ["datasets", "deepspeed", "evaluate", "scikit-learn", "scipy", "tqdm", "transformers"] +test-prod = ["parameterized", "pytest", "pytest-subtests", "pytest-xdist"] +test-trackers = ["comet-ml", "tensorboard", "wandb"] testing = ["datasets", "deepspeed", "evaluate", "parameterized", "pytest", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "tqdm", "transformers"] [[package]] name = "aiohttp" version = "3.8.5" description = "Async http client/server framework (asyncio)" -category = "main" optional = true python-versions = ">=3.6" - -[package.dependencies] -aiosignal = ">=1.1.2" -async-timeout = ">=4.0.0a3,<5.0" -attrs = ">=17.3.0" -charset-normalizer = ">=2.0,<4.0" -frozenlist = ">=1.1.1" -multidict = ">=4.5,<7.0" -yarl = ">=1.0,<2.0" - -[package.extras] -speedups = ["Brotli", "aiodns", "cchardet"] - -[[package]] -name = "aiosignal" -version = "1.3.1" -description = "aiosignal: a list of registered asynchronous callbacks" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.dependencies] -frozenlist = ">=1.1.0" - -[[package]] -name = "async-timeout" -version = "4.0.2" -description = "Timeout context manager for asyncio programs" -category = "main" -optional = true -python-versions = ">=3.6" - -[[package]] -name = "attrs" -version = "23.1.0" -description = "Classes Without Boilerplate" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.extras] -cov = ["attrs[tests]", "coverage[toml] (>=5.3)"] -dev = ["attrs[docs,tests]", "pre-commit"] -docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"] -tests = ["attrs[tests-no-zope]", "zope-interface"] -tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] - -[[package]] -name = "backoff" -version = "2.2.1" -description = "Function decoration for backoff and retry" -category = "main" -optional = false -python-versions = ">=3.7,<4.0" - -[[package]] -name = "bitsandbytes" -version = "0.38.1" -description = "8-bit optimizers and matrix multiplication routines." -category = "main" -optional = true -python-versions = "*" - -[[package]] -name = "certifi" -version = "2023.5.7" -description = "Python package for providing Mozilla's CA Bundle." -category = "main" -optional = false -python-versions = ">=3.6" - -[[package]] -name = "charset-normalizer" -version = "3.1.0" -description = "The Real First Universal Charset Detector. 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"sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2"}, ] -wrapt = [ + +[package.extras] +dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"] + +[[package]] +name = "wrapt" +version = "1.15.0" +description = "Module for decorators, wrappers and monkey patching." +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7" +files = [ {file = "wrapt-1.15.0-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:ca1cccf838cd28d5a0883b342474c630ac48cac5df0ee6eacc9c7290f76b11c1"}, {file = "wrapt-1.15.0-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:e826aadda3cae59295b95343db8f3d965fb31059da7de01ee8d1c40a60398b29"}, {file = "wrapt-1.15.0-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:5fc8e02f5984a55d2c653f5fea93531e9836abbd84342c1d1e17abc4a15084c2"}, @@ -2244,7 +2166,14 @@ wrapt = [ {file = "wrapt-1.15.0-py3-none-any.whl", hash = "sha256:64b1df0f83706b4ef4cfb4fb0e4c2669100fd7ecacfb59e091fad300d4e04640"}, {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"}, ] -xxhash = [ + +[[package]] +name = "xxhash" +version = "3.2.0" +description = "Python binding for xxHash" +optional = true +python-versions = ">=3.6" +files = [ {file = "xxhash-3.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:af44b9e59c4b2926a4e3c7f9d29949ff42fcea28637ff6b8182e654461932be8"}, {file = "xxhash-3.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1bdd57973e2b802ef32553d7bebf9402dac1557874dbe5c908b499ea917662cd"}, {file = "xxhash-3.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b7c9aa77bbce61a5e681bd39cb6a804338474dcc90abe3c543592aa5d6c9a9b"}, @@ -2344,7 +2273,14 @@ xxhash = [ {file = "xxhash-3.2.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:9d3f686e3d1c8900c5459eee02b60c7399e20ec5c6402364068a343c83a61d90"}, {file = "xxhash-3.2.0.tar.gz", hash = "sha256:1afd47af8955c5db730f630ad53ae798cf7fae0acb64cebb3cf94d35c47dd088"}, ] -yarl = [ + 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--hash=sha256:eef4d64c650f33347c1f9266fa5ae001440b232ad9b98f1f43dfe7a79435c0a6 \ + --hash=sha256:f2e69b3ed24544b0d3dbe2c5c0ba5153ce50dcebb576fdc4696d52aa22db6034 \ + --hash=sha256:f87ec75864c37c4c6cb908d282e1969e79763e0d9becdfe9fe5473b7bb1e5f09 \ + --hash=sha256:fbec11614dba0424ca72f4e8ba3c420dba07b4a7c206c8c8e4e73f2e98f4c559 \ + --hash=sha256:fd69666217b62fa5d7c6aa88e507493a34dec4fa20c5bd925e4bc12fce586639 diff --git a/server/text_generation_server/cli.py b/server/text_generation_server/cli.py index e74c0331..3037f21c 100644 --- a/server/text_generation_server/cli.py +++ b/server/text_generation_server/cli.py @@ -6,6 +6,7 @@ from pathlib import Path from loguru import logger from typing import Optional from enum import Enum +from huggingface_hub import hf_hub_download app = typer.Typer() @@ -88,6 +89,7 @@ def download_weights( auto_convert: bool = True, logger_level: str = "INFO", json_output: bool = False, + trust_remote_code: bool = False, ): # Remove default handler logger.remove() @@ -118,6 +120,12 @@ def download_weights( ) is not None if not is_local_model: + try: + adapter_config_filename = hf_hub_download(model_id, revision=revision, filename="adapter_config.json") + utils.download_and_unload_peft(model_id, revision, adapter_config_filename, trust_remote_code=trust_remote_code) + except utils.LocalEntryNotFoundError: + pass + # Try to download weights from the hub try: filenames = utils.weight_hub_files(model_id, revision, extension) diff --git a/server/text_generation_server/models/flash_rw.py b/server/text_generation_server/models/flash_rw.py index 7d655945..2fc7c53d 100644 --- a/server/text_generation_server/models/flash_rw.py +++ b/server/text_generation_server/models/flash_rw.py @@ -54,7 +54,7 @@ class FlashRWSharded(FlashCausalLM): device, dtype, process_group=self.process_group, - aliases={"transformer.word_embeddings.weight": ["lm_head.weight"]}, + aliases={"lm_head.weight": ["transformer.word_embeddings.weight"]}, ) config.quantize = quantize diff --git a/server/text_generation_server/utils/__init__.py b/server/text_generation_server/utils/__init__.py index befedcf0..08ba808d 100644 --- a/server/text_generation_server/utils/__init__.py +++ b/server/text_generation_server/utils/__init__.py @@ -1,6 +1,7 @@ from text_generation_server.utils.convert import convert_file, convert_files from text_generation_server.utils.dist import initialize_torch_distributed from text_generation_server.utils.weights import Weights +from text_generation_server.utils.peft import download_and_unload_peft from text_generation_server.utils.hub import ( weight_files, weight_hub_files, @@ -26,6 +27,7 @@ __all__ = [ "weight_files", "weight_hub_files", "download_weights", + "download_and_unload_peft", "EntryNotFoundError", "HeterogeneousNextTokenChooser", "LocalEntryNotFoundError", diff --git a/server/text_generation_server/utils/peft.py b/server/text_generation_server/utils/peft.py new file mode 100644 index 00000000..68744e38 --- /dev/null +++ b/server/text_generation_server/utils/peft.py @@ -0,0 +1,66 @@ +import os +import sys +import json +from loguru import logger + +from transformers.models.auto import modeling_auto +from transformers import AutoModelForCausalLM, AutoModelForSeq2SeqLM, AutoConfig, AutoModel, AutoTokenizer +from peft import PeftModel + +def download_and_unload_peft(model_id, revision, adapter_config_filename, trust_remote_code): + + logger.info("Peft model detected.") + peft_model_id = model_id + with open(adapter_config_filename, "r") as f: + adapter_config = json.load(f) + model_id = adapter_config["base_model_name_or_path"] + logger.info(f"Merging the lora weights {repr(peft_model_id)} into the base model {repr(model_id)}") + config = AutoConfig.from_pretrained(model_id, revision=revision, trust_remote_code=trust_remote_code) + model_type = config.model_type + logger.info(f"Starting to load the base model {repr(model_id)}, this may take a while with no feedback.") + if model_type in modeling_auto.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES: + base_model = AutoModelForCausalLM.from_pretrained( + model_id, + revision=revision, + trust_remote_code=trust_remote_code + ) + elif model_type in modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES: + base_model = AutoModelForSeq2SeqLM( + model_id, + revision=revision, + ) + else: + # We have no idea just try either + try: + base_model = AutoModelForCausalLM.from_pretrained( + model_id, + revision=revision, + trust_remote_code=trust_remote_code + ) + except Exception: + base_model = AutoModelForSeq2SeqLM.from_pretrained( + model_id, + revision=revision, + trust_remote_code=trust_remote_code + ) + logger.info(f"Loaded.") + + logger.info(f"Merging the lora weights {repr(peft_model_id)} into the base model {repr(model_id)}") + + model = PeftModel.from_pretrained( + base_model, + peft_model_id, + trust_remote_code=trust_remote_code, + ) + model = model.merge_and_unload() + + os.makedirs(peft_model_id, exist_ok=True) + cache_dir = peft_model_id + logger.info(f"Saving the newly created merged model to {cache_dir}") + tokenizer = AutoTokenizer.from_pretrained(model_id) + model.save_pretrained(cache_dir, safe_serialization=True) + config.save_pretrained(cache_dir) + tokenizer.save_pretrained(cache_dir) + + +