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https://github.com/NVIDIA/TensorRT-LLM.git
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0ec7b5701f
* Handle qwen2audio inputs ids expansion during processing Signed-off-by: Aurelien Chartier <achartier@nvidia.com> * remove more dead code Signed-off-by: Aurelien Chartier <achartier@nvidia.com> * fix yapf Signed-off-by: Aurelien Chartier <achartier@nvidia.com> --------- Signed-off-by: Aurelien Chartier <achartier@nvidia.com> Co-authored-by: QI JUN <22017000+QiJune@users.noreply.github.com>
108 lines
3.5 KiB
Python
108 lines
3.5 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2024 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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"""Module test_qwen test qwen2audio examples."""
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import os
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import re
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import pytest
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from defs.common import venv_check_call, venv_check_output
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from defs.trt_test_alternative import check_call
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@pytest.fixture(scope="module")
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def qwen2audio_example_root(llm_root, llm_venv):
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"Get qwen2audio example root"
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example_root = os.path.join(llm_root, "examples", "qwen2audio")
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llm_venv.run_cmd([
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"-m", "pip", "install", "-r",
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os.path.join(example_root, "requirements.txt")
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])
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return example_root
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@pytest.mark.parametrize("llm_qwen_model_root", ["qwen2_audio_7b_instruct"],
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indirect=True)
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def test_llm_qwen2audio_single_gpu(qwen2audio_example_root, llm_qwen_model_root,
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llm_venv, engine_dir):
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"Build & run qwen2audio on 1 gpu."
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workspace = llm_venv.get_working_directory()
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print("Generate audio engine...")
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audio_engine_dir = f"{engine_dir}/audio"
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audio_cmd = [
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f"{qwen2audio_example_root}/../multimodal/build_multimodal_engine.py",
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f"--model_type=qwen2_audio",
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f"--model_path={llm_qwen_model_root}",
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f"--max_batch_size=32",
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f"--output_dir={audio_engine_dir}",
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]
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venv_check_call(llm_venv, audio_cmd)
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print("Convert checkpoint...")
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convert_cmd = [
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f"{qwen2audio_example_root}/../qwen/convert_checkpoint.py",
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f"--model_dir={llm_qwen_model_root}",
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f"--output_dir={workspace}/Qwen2-Audio",
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f"--dtype=float16",
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]
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venv_check_call(llm_venv, convert_cmd)
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print("Build TRT-LLM engine...")
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build_cmd = [
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"trtllm-build",
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f"--checkpoint_dir={workspace}/Qwen2-Audio",
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f"--gemm_plugin=float16",
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f"--gpt_attention_plugin=float16",
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f"--max_prompt_embedding_table_size=4096",
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f"--output_dir={engine_dir}",
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f"--max_batch_size={1}",
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]
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check_call(" ".join(build_cmd), shell=True, env=llm_venv._new_env)
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print("Run engine...")
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audio_url = f"{qwen2audio_example_root}/audio/glass-breaking-151256.mp3"
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run_cmd = [
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f"{qwen2audio_example_root}/run.py",
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f"--tokenizer_dir={llm_qwen_model_root}",
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f"--engine_dir={engine_dir}",
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f"--audio_engine_path={audio_engine_dir}/model.engine",
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f"--audio_url={audio_url}",
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]
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output = venv_check_output(llm_venv, run_cmd)
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output = [line for line in output.split("\n") if "Output:" in line]
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print(output)
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print("Verify the output...")
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results = []
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for item in output:
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match = re.search(r"Output: \"(.*)", item)
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if match:
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results.append(match.group(1))
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for item in results:
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# check the output if it contains key words
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item = item.lower()
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if ("glass" in item) and ("shatter" in item or "break" in item):
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pass
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else:
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assert False, f"output is: {item}"
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