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游雁

2023-05-25 b18f7d121f2f17df8bf2d0c2bbb223bc5ddbcc0f

 funasr/models/encoder/conformer_encoder.py

@@ -15,13 +15,13 @@
from typeguard import check_argument_types

from funasr.models.ctc import CTC
from funasr.models.encoder.abs_encoder import AbsEncoder
from funasr.modules.attention import (
    MultiHeadedAttention,  # noqa: H301
    RelPositionMultiHeadedAttention,  # noqa: H301
    RelPositionMultiHeadedAttentionChunk,
    LegacyRelPositionMultiHeadedAttention,  # noqa: H301
)
from funasr.models.encoder.abs_encoder import AbsEncoder
from funasr.modules.embedding import (
    PositionalEncoding,  # noqa: H301
    ScaledPositionalEncoding,  # noqa: H301
@@ -307,7 +307,7 @@
        feed_forward: torch.nn.Module,
        feed_forward_macaron: torch.nn.Module,
        conv_mod: torch.nn.Module,
        norm_class: torch.nn.Module = torch.nn.LayerNorm,
        norm_class: torch.nn.Module = LayerNorm,
        norm_args: Dict = {},
        dropout_rate: float = 0.0,
    ) -> None:
@@ -1078,7 +1078,7 @@
                limit_size,
            )

        mask = make_source_mask(x_len)
        mask = make_source_mask(x_len).to(x.device)

        if self.unified_model_training:
            chunk_size = self.default_chunk_size + torch.randint(-self.jitter_range, self.jitter_range+1, (1,)).item()
@@ -1145,7 +1145,7 @@
            x = x[:,::self.time_reduction_factor,:]
            olens = torch.floor_divide(olens-1, self.time_reduction_factor) + 1

        return x, olens
        return x, olens, None

    def simu_chunk_forward(
        self,