wehub-resource-sync
86 lines
2.5 KiB
Python
86 lines
2.5 KiB
Python
# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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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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from __future__ import annotations
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import unittest
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import paddle
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from .testing_utils import LLMTest, argv_context_guard
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class SpeculatePredictorTest(LLMTest, unittest.TestCase):
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model_name_or_path: str = "__internal_testing__/tiny-random-llama-hd128"
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def setUp(self) -> None:
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super().setUp()
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paddle.set_default_dtype("bfloat16")
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self.config_params = {
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"model_name_or_path": self.model_name_or_path,
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"mode": "dynamic",
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"dtype": "bfloat16",
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"max_length": 48,
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"inference_model": 1,
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"speculate_method": None,
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}
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def run_speculate_predictor(self, speculate_params):
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"""
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base speculative decoding forward test.
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"""
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predict_config = self.config_params
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predict_config.update(speculate_params)
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# dynamic forward
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self.disable_static()
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with argv_context_guard(predict_config):
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from predict.predictor import predict
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predict()
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# to static
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self.disable_static()
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predict_config["output_path"] = self.output_dir
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with argv_context_guard(predict_config):
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from predict.export_model import main
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main()
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# static forward
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self.disable_static()
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predict_config["mode"] = "static"
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predict_config["model_name_or_path"] = self.output_dir
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predict_config.pop("output_path")
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with argv_context_guard(predict_config):
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from predict.predictor import predict
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predict()
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def test_inference_with_reference(self):
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"""
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test inference with reference method.
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"""
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speculate_params = {
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"speculate_method": "inference_with_reference",
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"speculate_max_draft_token_num": 5,
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"speculate_max_ngram_size": 2,
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}
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self.run_speculate_predictor(speculate_params)
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if __name__ == "__main__":
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unittest.main()
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