shfit to shift (#2266)

Rin Arakaki

2024-12-24 1367973f9818d8e15c7bf52ad6ffba4ddb6ac2b2

 funasr/models/ct_transformer_streaming/encoder.py

@@ -56,7 +56,7 @@
        self.stochastic_depth_rate = stochastic_depth_rate
        self.dropout_rate = dropout_rate

    def forward(self, x, mask, cache=None, mask_shfit_chunk=None, mask_att_chunk_encoder=None):
    def forward(self, x, mask, cache=None, mask_shift_chunk=None, mask_att_chunk_encoder=None):
        """Compute encoded features.

        Args:
@@ -93,7 +93,7 @@
                    self.self_attn(
                        x,
                        mask,
                        mask_shfit_chunk=mask_shfit_chunk,
                        mask_shift_chunk=mask_shift_chunk,
                        mask_att_chunk_encoder=mask_att_chunk_encoder,
                    ),
                ),
@@ -109,7 +109,7 @@
                    self.self_attn(
                        x,
                        mask,
                        mask_shfit_chunk=mask_shfit_chunk,
                        mask_shift_chunk=mask_shift_chunk,
                        mask_att_chunk_encoder=mask_att_chunk_encoder,
                    )
                )
@@ -118,7 +118,7 @@
                    self.self_attn(
                        x,
                        mask,
                        mask_shfit_chunk=mask_shfit_chunk,
                        mask_shift_chunk=mask_shift_chunk,
                        mask_att_chunk_encoder=mask_att_chunk_encoder,
                    )
                )
@@ -132,7 +132,7 @@
        if not self.normalize_before:
            x = self.norm2(x)

        return x, mask, cache, mask_shfit_chunk, mask_att_chunk_encoder
        return x, mask, cache, mask_shift_chunk, mask_att_chunk_encoder

    def forward_chunk(self, x, cache=None, chunk_size=None, look_back=0):
        """Compute encoded features.
@@ -198,7 +198,7 @@
        interctc_layer_idx: List[int] = [],
        interctc_use_conditioning: bool = False,
        kernel_size: int = 11,
        sanm_shfit: int = 0,
        sanm_shift: int = 0,
        selfattention_layer_type: str = "sanm",
    ):
        super().__init__()
@@ -277,7 +277,7 @@
                output_size,
                attention_dropout_rate,
                kernel_size,
                sanm_shfit,
                sanm_shift,
            )

            encoder_selfattn_layer_args = (
@@ -286,7 +286,7 @@
                output_size,
                attention_dropout_rate,
                kernel_size,
                sanm_shfit,
                sanm_shift,
            )

        self.encoders0 = repeat(