77 lines
3.1 KiB
Python
77 lines
3.1 KiB
Python
#
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# Copyright 2016 The BigDL Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import pytest
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import os
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import tempfile
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from unittest import TestCase
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from bigdl.llm import llm_convert
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from bigdl.llm.transformers import AutoModelForCausalLM
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llama_model_path = os.environ.get('LLAMA_ORIGIN_PATH')
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gptneox_model_path = os.environ.get('GPTNEOX_ORIGIN_PATH')
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bloom_model_path = os.environ.get('BLOOM_ORIGIN_PATH')
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starcoder_model_path = os.environ.get('STARCODER_ORIGIN_PATH')
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output_dir = os.environ.get('INT4_CKPT_DIR')
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class TestConvertModel(TestCase):
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def test_convert_llama(self):
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converted_model_path = llm_convert(model=llama_model_path,
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outfile=output_dir,
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model_family='llama',
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model_format="pth",
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outtype='int4')
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assert os.path.isfile(converted_model_path)
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def test_convert_gptneox(self):
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converted_model_path = llm_convert(model=gptneox_model_path,
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outfile=output_dir,
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model_family='gptneox',
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model_format="pth",
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outtype='int4')
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assert os.path.isfile(converted_model_path)
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def test_convert_bloom(self):
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converted_model_path = llm_convert(model=bloom_model_path,
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outfile=output_dir,
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model_family='bloom',
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model_format="pth",
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outtype='int4')
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assert os.path.isfile(converted_model_path)
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def test_convert_starcoder(self):
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converted_model_path = llm_convert(model=starcoder_model_path,
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outfile=output_dir,
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model_family='starcoder',
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model_format="pth",
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outtype='int4')
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assert os.path.isfile(converted_model_path)
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def test_transformer_convert_llama(self):
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model = AutoModelForCausalLM.from_pretrained(llama_model_path,
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load_in_4bit=True)
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tempdir = tempfile.mkdtemp(dir=output_dir)
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model.save_pretrained(tempdir)
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model = AutoModelForCausalLM.from_pretrained(tempdir)
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assert model is not None
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if __name__ == '__main__':
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pytest.main([__file__])
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