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| | | # Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved. |
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| | | # MIT License (https://opensource.org/licenses/MIT) |
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| | | import json |
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| | | import os |
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| | | import sys |
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| | | |
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| | | from funasr import AutoModel |
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| | | if len(sys.argv) > 1: |
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| | | ckpt_dir = sys.argv[1] |
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| | | ckpt_id = sys.argv[2] |
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| | | jsonl = sys.argv[3] |
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| | | output_dir = sys.argv[4] |
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| | | device = sys.argv[5] |
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| | | else: |
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| | | ckpt_dir = "/nfs/beinian.lzr/workspace/GPT-4o/Exp/exp6/5m-8gpu/exp6_speech2text_linear_ddp_0609" |
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| | | ckpt_id = "model.pt.ep0.90000" |
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| | | jsonl = "/nfs/beinian.lzr/workspace/GPT-4o/Data/Speech2Text/TestData/aishell1_test_speech2text.jsonl" |
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| | | dataset = jsonl.split("/")[-1] |
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| | | output_dir = os.path.join(ckpt_dir, f"inference-{ckpt_id}", dataset) |
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| | | device = "cuda:0" |
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| | | |
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| | | model = AutoModel( |
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| | | model="iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch", |
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| | | vad_model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch", |
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| | | vad_kwargs={"max_single_segment_time": 60000}, |
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| | | punc_model="iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch", |
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| | | # spk_model="iic/speech_campplus_sv_zh-cn_16k-common", |
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| | | model=ckpt_dir, |
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| | | init_param=f"{os.path.join(ckpt_dir, ckpt_id)}", |
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| | | output_dir=output_dir, |
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| | | device=device, |
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| | | fp16=False, |
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| | | bf16=False, |
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| | | llm_dtype="bf16", |
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| | | ) |
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| | | |
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| | | res = model.generate( |
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| | | input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav", |
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| | | cache={}, |
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| | | ) |
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| | | |
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| | | print(res) |
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| | | with open(jsonl, "r") as f: |
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| | | lines = f.readlines() |
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| | | |
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| | | tearchforing = False |
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| | | for i, line in enumerate(lines): |
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| | | data_dict = json.loads(line.strip()) |
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| | | data = data_dict["messages"] |
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| | | |
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| | | """ can not use currently |
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| | | from funasr import AutoFrontend |
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| | | res = model.generate( |
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| | | input=[data], |
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| | | tearchforing=tearchforing, |
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| | | cache={}, |
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| | | ) |
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| | | |
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| | | frontend = AutoFrontend(model="iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch") |
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| | | |
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| | | fbanks = frontend(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav", batch_size=2) |
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| | | |
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| | | for batch_idx, fbank_dict in enumerate(fbanks): |
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| | | res = model.generate(**fbank_dict) |
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| | | print(res) |
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| | | """ |
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