diff --git a/test/entrypoints/test_generation.py b/test/entrypoints/test_generation.py new file mode 100644 index 0000000000..214f1017cd --- /dev/null +++ b/test/entrypoints/test_generation.py @@ -0,0 +1,124 @@ +""" +# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. +# +# 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 os +import unittest +import weakref + +from fastdeploy.engine.request import RequestOutput +from fastdeploy.engine.sampling_params import SamplingParams +from fastdeploy.entrypoints.llm import LLM + +MODEL_NAME = os.getenv("MODEL_PATH") + "/ERNIE-4.5-0.3B-Paddle" + + +class TestGeneration(unittest.TestCase): + """Test case for generation functionality""" + + TOKEN_IDS = [ + [0], + [0, 1], + [0, 1, 3], + [0, 2, 4, 6], + ] + + PROMPTS = [ + "Hello, my name is", + "The capital of China is", + "The future of AI is", + "人工智能是", + ] + + @classmethod + def setUpClass(cls): + try: + llm = LLM( + model=MODEL_NAME, + max_num_batched_tokens=4096, + tensor_parallel_size=1, + engine_worker_queue_port=int(os.getenv("FD_ENGINE_QUEUE_PORT")), + ) + cls.llm = weakref.proxy(llm) + except Exception as e: + print(f"Setting up LLM failed: {e}") + raise unittest.SkipTest(f"LLM initialization failed: {e}") + + @classmethod + def tearDownClass(cls): + """Clean up after all tests have run""" + if hasattr(cls, "llm"): + del cls.llm + + def assert_outputs_equal(self, o1: list[RequestOutput], o2: list[RequestOutput]): + self.assertEqual([o.outputs for o in o1], [o.outputs for o in o2]) + + def test_consistency_single_prompt_tokens(self): + """Test consistency between different prompt input formats""" + sampling_params = SamplingParams(temperature=1.0, top_p=0.0) + + for prompt_token_ids in self.TOKEN_IDS: + with self.subTest(prompt_token_ids=prompt_token_ids): + output1 = self.llm.generate(prompts=prompt_token_ids, sampling_params=sampling_params) + output2 = self.llm.generate( + {"prompt": "", "prompt_token_ids": prompt_token_ids}, sampling_params=sampling_params + ) + self.assert_outputs_equal(output1, output2) + + def test_api_consistency_multi_prompt_tokens(self): + """Test consistency with multiple prompt tokens""" + sampling_params = SamplingParams( + temperature=1.0, + top_p=0.0, + ) + + output1 = self.llm.generate(prompts=self.TOKEN_IDS, sampling_params=sampling_params) + + output2 = self.llm.generate( + [{"prompt": "", "prompt_token_ids": p} for p in self.TOKEN_IDS], + sampling_params=sampling_params, + ) + + self.assert_outputs_equal(output1, output2) + + def test_multiple_sampling_params(self): + """Test multiple sampling parameters combinations""" + sampling_params = [ + SamplingParams(temperature=0.01, top_p=0.95), + SamplingParams(temperature=0.3, top_p=0.95), + SamplingParams(temperature=0.7, top_p=0.95), + SamplingParams(temperature=0.99, top_p=0.95), + ] + + # Multiple SamplingParams should be matched with each prompt + outputs = self.llm.generate(prompts=self.PROMPTS, sampling_params=sampling_params) + self.assertEqual(len(self.PROMPTS), len(outputs)) + + # Exception raised if size mismatch + with self.assertRaises(ValueError): + self.llm.generate(prompts=self.PROMPTS, sampling_params=sampling_params[:3]) + + # Single SamplingParams should be applied to every prompt + single_sampling_params = SamplingParams(temperature=0.3, top_p=0.95) + outputs = self.llm.generate(prompts=self.PROMPTS, sampling_params=single_sampling_params) + self.assertEqual(len(self.PROMPTS), len(outputs)) + + # sampling_params is None, default params should be applied + outputs = self.llm.generate(prompts=self.PROMPTS, sampling_params=None) + self.assertEqual(len(self.PROMPTS), len(outputs)) + + +if __name__ == "__main__": + unittest.main() diff --git a/test/plugins/setup.py b/test/plugins/setup.py index 92c953d61b..06038c15ea 100644 --- a/test/plugins/setup.py +++ b/test/plugins/setup.py @@ -22,6 +22,5 @@ "fastdeploy.model_register_plugins": [ "fd_add_dummy_model = fd_add_dummy_model:register", ], - "fastdeploy.model_runner_plugins": ["fd_add_dummy_model_runner = fd_add_dummy_model_runner:get_runner"], }, ) diff --git a/test/plugins/test_model_runner_register.py b/test/plugins/test_model_runner_register.py deleted file mode 100644 index 85110ba626..0000000000 --- a/test/plugins/test_model_runner_register.py +++ /dev/null @@ -1,35 +0,0 @@ -# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. -# -# 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 unittest - -from fastdeploy.plugins import load_model_runner_plugins - - -class TestModelRunnerRegistryPlugins(unittest.TestCase): - def test_model_runner_callable(self): - runner_class = load_model_runner_plugins() - device_id = 1 - - # create runner - runner = runner_class(device_id) - - # test func - res = runner.get_rank() - - self.assertEqual(res, device_id) - - -if __name__ == "__main__": - unittest.main()