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| | | #!/usr/bin/env python3 |
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| | | # -*- encoding: utf-8 -*- |
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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 logging |
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| | | import torch |
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| | | from funasr.models.transformer.model import Transformer |
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| | | from funasr.register import tables |
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| | | @tables.register("model_classes", "SANM") |
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| | | class SANM(Transformer): |
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| | | """CTC-attention hybrid Encoder-Decoder model""" |
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| | | """ |
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| | | Author: Zhifu Gao, Shiliang Zhang, Ming Lei, Ian McLoughlin |
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| | | San-m: Memory equipped self-attention for end-to-end speech recognition |
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| | | https://arxiv.org/abs/2006.01713 |
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| | | """ |
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| | | |
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| | | def __init__( |
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| | | self, |
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