mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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69 lines
2.7 KiB
Python
69 lines
2.7 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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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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import pytest
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from tensorrt_llm._torch.auto_deploy import LLM as AutoDeployLLM
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from tensorrt_llm.sampling_params import SamplingParams
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from ..conftest import llm_models_root
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from .accuracy_core import MMLU, CnnDailymail, LlmapiAccuracyTestHarness
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class TestLlama3_1_8B(LlmapiAccuracyTestHarness):
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MODEL_NAME = "meta-llama/Llama-3.1-8B"
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MODEL_PATH = f"{llm_models_root()}/llama-3.1-model/Meta-Llama-3.1-8B"
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def get_default_kwargs(self):
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return {
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'skip_tokenizer_init': False,
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'trust_remote_code': True,
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# TODO(https://github.com/NVIDIA/TensorRT-LLM/issues/7142):
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# AutoDeploy does not support cache reuse yet.
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'kv_cache_config': {
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'enable_block_reuse': False,
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},
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'max_batch_size': 512,
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# 131072 is the max seq len for the model
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'max_seq_len': 8192,
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# max num tokens is derived in the build_config, which is not used by AutoDeploy llmargs.
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# Set it explicitly here to 8192 which is the default in build_config.
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'max_num_tokens': 8192,
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'skip_loading_weights': False,
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'compile_backend': 'torch-opt',
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'free_mem_ratio': 0.7,
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'cuda_graph_batch_sizes': [1, 2, 4, 8, 16, 32, 64, 128, 256, 512]
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}
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def get_default_sampling_params(self):
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eos_id = -1
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beam_width = 1
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return SamplingParams(end_id=eos_id,
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pad_id=eos_id,
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n=beam_width,
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use_beam_search=beam_width > 1)
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@pytest.mark.skip_less_device_memory(32000)
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def test_auto_dtype(self):
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kwargs = self.get_default_kwargs()
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sampling_params = self.get_default_sampling_params()
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with AutoDeployLLM(model=self.MODEL_PATH,
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tokenizer=self.MODEL_PATH,
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**kwargs) as llm:
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task = CnnDailymail(self.MODEL_NAME)
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task.evaluate(llm)
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task = MMLU(self.MODEL_NAME)
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task.evaluate(llm, sampling_params=sampling_params)
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