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| | | from typeguard import check_argument_types |
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| | | |
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| | | from funasr.models.ctc import CTC |
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| | | from funasr.models.encoder.abs_encoder import AbsEncoder |
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| | | from funasr.modules.attention import ( |
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| | | MultiHeadedAttention, # noqa: H301 |
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| | | RelPositionMultiHeadedAttention, # noqa: H301 |
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| | | RelPositionMultiHeadedAttentionChunk, |
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| | | LegacyRelPositionMultiHeadedAttention, # noqa: H301 |
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| | | ) |
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| | | from funasr.models.encoder.abs_encoder import AbsEncoder |
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| | | from funasr.modules.embedding import ( |
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| | | PositionalEncoding, # noqa: H301 |
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| | | ScaledPositionalEncoding, # noqa: H301 |
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| | |
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| | | limit_size, |
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| | | ) |
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| | | |
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| | | mask = make_source_mask(x_len) |
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| | | mask = make_source_mask(x_len).to(x.device) |
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| | | |
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| | | if self.unified_model_training: |
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| | | chunk_size = self.default_chunk_size + torch.randint(-self.jitter_range, self.jitter_range+1, (1,)).item() |
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