-
Notifications
You must be signed in to change notification settings - Fork 1.5k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge remote-tracking branch 'upstream/main' into add_xlora
- Loading branch information
Showing
15 changed files
with
330 additions
and
10 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,103 @@ | ||
# Copyright 2024-present 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. | ||
|
||
""" | ||
Example script demonstrating the time difference loading a model with a DoRA using ephemeral GPU offloading vs doing it purely on the CPU. | ||
Example outputs: | ||
$ python load_with_dora.py | ||
--- Loading model --- | ||
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:04<00:00, 1.03s/it] | ||
--- Loading PeftModel --- | ||
--- Done --- | ||
Model loading time: 4.83s | ||
PeftModel loading time: 28.14s | ||
Use ephemeral GPU offloading: False | ||
(Note: if this was the first time you ran the script, or if your cache was cleared, the times shown above are invalid, due to the time taken to download the model and DoRA files. Just re-run the script in this case.) | ||
$ python load_with_dora.py --ephemeral_gpu_offload | ||
--- Loading model --- | ||
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:03<00:00, 1.11it/s] | ||
--- Loading PeftModel --- | ||
--- Done --- | ||
Model loading time: 4.28s | ||
PeftModel loading time: 16.59s | ||
Use ephemeral GPU offloading: True | ||
(Note: if this was the first time you ran the script, or if your cache was cleared, the times shown above are invalid, due to the time taken to download the model and DoRA files. Just re-run the script in this case.) | ||
""" | ||
|
||
import argparse | ||
import time | ||
|
||
from huggingface_hub import snapshot_download | ||
from transformers import AutoModelForCausalLM | ||
|
||
from peft import PeftModel | ||
|
||
|
||
def main(): | ||
parser = argparse.ArgumentParser(description="Load a model with DoRA using ephemeral GPU offloading") | ||
parser.add_argument("--model", type=str, default="NousResearch/Hermes-2-Pro-Mistral-7B", help="Model to load") | ||
parser.add_argument( | ||
"--dora", | ||
type=str, | ||
default="peft-internal-testing/DoRA-Hermes-2-Pro-Mistral-7B", | ||
help="DoRA to use", | ||
) | ||
parser.add_argument("--ephemeral_gpu_offload", action="store_true", help="Use ephemeral GPU offloading") | ||
parser.add_argument( | ||
"--merge_model_path", type="str", help="Merge the model with the DoRA model and save to the given path" | ||
) | ||
args = parser.parse_args() | ||
|
||
peft_model_kwargs = { | ||
"ephemeral_gpu_offload": args.ephemeral_gpu_offload, | ||
"max_memory": {"cpu": "256GiB"}, | ||
"device_map": {"": "cpu"}, | ||
} | ||
|
||
# Predownload | ||
try: | ||
snapshot_download(repo_id=args.model) | ||
except Exception as e: | ||
print(f"Failed to download model: {e}") | ||
# We continue anyway as this might be e.g. a local directory or something | ||
try: | ||
snapshot_download(repo_id=args.dora) | ||
except Exception as e: | ||
print(f"Failed to download DoRA: {e}") | ||
# We continue anyway as this might be e.g. a local directory or something | ||
|
||
start = time.perf_counter() | ||
print("--- Loading model ---") | ||
model = AutoModelForCausalLM.from_pretrained(args.model) | ||
model_time = time.perf_counter() - start | ||
print("--- Loading PeftModel ---") | ||
peft_model = PeftModel.from_pretrained(model, args.dora, **peft_model_kwargs) | ||
print("--- Done ---") | ||
peft_model_time = time.perf_counter() - start | ||
|
||
print(f"Model loading time: {model_time:.2f}s") | ||
print(f"PeftModel loading time: {peft_model_time:.2f}s") | ||
print(f"Use ephemeral GPU offloading: {args.ephemeral_gpu_offload}") | ||
|
||
if args.merge_model_path is not None: | ||
merged_model = peft_model.merge_and_unload(progressbar=True) | ||
merged_model.save_pretrained(args.merge_model_path) | ||
|
||
|
||
if __name__ == "__main__": | ||
main() |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Oops, something went wrong.