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hub / github.com/FunAudioLLM/SenseVoice / __init__

Method __init__

model.py:445–541  ·  view source on GitHub ↗
(
        self,
        input_size: int,
        output_size: int = 256,
        attention_heads: int = 4,
        linear_units: int = 2048,
        num_blocks: int = 6,
        tp_blocks: int = 0,
        dropout_rate: float = 0.1,
        positional_dropout_rate: float = 0.1,
        attention_dropout_rate: float = 0.0,
        stochastic_depth_rate: float = 0.0,
        input_layer: Optional[str] = "conv2d",
        pos_enc_class=SinusoidalPositionEncoder,
        normalize_before: bool = True,
        concat_after: bool = False,
        positionwise_layer_type: str = "linear",
        positionwise_conv_kernel_size: int = 1,
        padding_idx: int = -1,
        kernel_size: int = 11,
        sanm_shfit: int = 0,
        selfattention_layer_type: str = "sanm",
        **kwargs,
    )

Source from the content-addressed store, hash-verified

443 """
444
445 def __init__(
446 self,
447 input_size: int,
448 output_size: int = 256,
449 attention_heads: int = 4,
450 linear_units: int = 2048,
451 num_blocks: int = 6,
452 tp_blocks: int = 0,
453 dropout_rate: float = 0.1,
454 positional_dropout_rate: float = 0.1,
455 attention_dropout_rate: float = 0.0,
456 stochastic_depth_rate: float = 0.0,
457 input_layer: Optional[str] = "conv2d",
458 pos_enc_class=SinusoidalPositionEncoder,
459 normalize_before: bool = True,
460 concat_after: bool = False,
461 positionwise_layer_type: str = "linear",
462 positionwise_conv_kernel_size: int = 1,
463 padding_idx: int = -1,
464 kernel_size: int = 11,
465 sanm_shfit: int = 0,
466 selfattention_layer_type: str = "sanm",
467 **kwargs,
468 ):
469 super().__init__()
470 self._output_size = output_size
471
472 self.embed = SinusoidalPositionEncoder()
473
474 self.normalize_before = normalize_before
475
476 positionwise_layer = PositionwiseFeedForward
477 positionwise_layer_args = (
478 output_size,
479 linear_units,
480 dropout_rate,
481 )
482
483 encoder_selfattn_layer = MultiHeadedAttentionSANM
484 encoder_selfattn_layer_args0 = (
485 attention_heads,
486 input_size,
487 output_size,
488 attention_dropout_rate,
489 kernel_size,
490 sanm_shfit,
491 )
492 encoder_selfattn_layer_args = (
493 attention_heads,
494 output_size,
495 output_size,
496 attention_dropout_rate,
497 kernel_size,
498 sanm_shfit,
499 )
500
501 self.encoders0 = nn.ModuleList(
502 [

Callers

nothing calls this directly

Calls 4

EncoderLayerSANMClass · 0.85
LayerNormClass · 0.85
__init__Method · 0.45

Tested by

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