ipex-llm/python/llm/test/inference_gpu/test_optimize_model.py
Cheen Hau, 俊豪 cee9eaf542 [LLM] Fix llm arc ut oom (#9300)
* Move model to cpu after testing so that gpu memory is deallocated

* Add code comment

---------

Co-authored-by: sgwhat <ge.song@intel.com>
2023-10-30 14:38:34 +08:00

60 lines
2.2 KiB
Python

#
# Copyright 2016 The BigDL Authors.
#
# 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.
#
import pytest
import os
from bigdl.llm.transformers import AutoModelForCausalLM, AutoModel
from transformers import LlamaTokenizer, AutoTokenizer
device = os.environ['DEVICE']
print(f'Running on {device}')
if device == 'xpu':
import intel_extension_for_pytorch as ipex
prompt = "Once upon a time, there existed a little girl who liked to have adventures. She wanted to go to places and meet new people, and have fun"
@pytest.mark.parametrize('Model, Tokenizer, model_path',[
(AutoModelForCausalLM, AutoTokenizer, os.environ.get('MPT_7B_ORIGIN_PATH')),
(AutoModelForCausalLM, AutoTokenizer, os.environ.get('FALCON_7B_ORIGIN_PATH')),
])
def test_optimize_model(Model, Tokenizer, model_path):
tokenizer = Tokenizer.from_pretrained(model_path, trust_remote_code=True)
input_ids = tokenizer.encode(prompt, return_tensors="pt").to(device)
model = Model.from_pretrained(model_path,
load_in_4bit=True,
optimize_model=False,
trust_remote_code=True)
model = model.to(device)
logits_base_model = (model(input_ids)).logits
model.to('cpu') # deallocate gpu memory
model = Model.from_pretrained(model_path,
load_in_4bit=True,
optimize_model=True,
trust_remote_code=True)
model = model.to(device)
logits_optimized_model = (model(input_ids)).logits
model.to('cpu')
diff = abs(logits_base_model - logits_optimized_model).flatten()
assert any(diff) is False
if __name__ == '__main__':
pytest.main([__file__])