mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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80 lines
2.3 KiB
Python
80 lines
2.3 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2025 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 torch
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from run import QWenInfer, parse_arguments
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import tensorrt_llm
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if __name__ == '__main__':
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args = parse_arguments()
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stream = torch.cuda.current_stream()
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tensorrt_llm.logger.set_level(args.log_level)
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qinfer = QWenInfer(
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args.audio_engine_path,
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args.tokenizer_dir,
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args.engine_dir,
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args.log_level,
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args.output_csv,
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args.output_npy,
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args.num_beams,
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)
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qinfer.qwen_model_init(args)
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run_i = 0
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history = []
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audios = None
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global_audio_id = 1
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audio_ids = []
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while True:
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input_text = None
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try:
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input_text = input(
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"Text (type 'q' to quit, or 'audio_url:[url]' to input audio): "
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)
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except:
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continue
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if input_text == "clear history":
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history = []
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audios = None
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continue
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if input_text.lower() == 'q':
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break
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print('\n')
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if input_text.startswith('audio_url:'):
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audio_url = input_text[len('audio_url:'):].strip()
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if isinstance(audios, list):
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audios.extend(qinfer.get_raw_audios([audio_url]))
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else:
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audios = qinfer.get_raw_audios([audio_url])
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user_input = qinfer.build_user_input(audio=audio_url)
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audio_ids.append(global_audio_id)
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global_audio_id += 1
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else:
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user_input = qinfer.build_user_input(text=input_text)
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qinfer.qwen_infer(
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user_input,
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audios,
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audio_ids,
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args,
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stream,
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history,
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)
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