| from transformers.models.voxtral.configuration_voxtral import VoxtralConfig, VoxtralEncoderConfig |
|
|
|
|
| class DixtralEncoderConfig(VoxtralEncoderConfig): |
| def __init__( |
| self, |
| |
| use_dicow_encoder: bool = False, |
| ctc_weight: float = 0.0, |
| additional_layer: bool = False, |
| additional_self_attention_layer: bool = False, |
| pre_ctc_sub_sample: bool = False, |
| final_dropout: float = 0.0, |
| use_fddt: bool = False, |
| apply_fddt_to_n_layers: int = -1, |
| use_pre_pos_fddt: bool = False, |
| fddt_init: str = "zeros", |
| fddt_is_diagonal: bool = False, |
| fddt_bias_only: bool = False, |
| fddt_use_silence: bool = True, |
| fddt_use_target: bool = True, |
| fddt_use_overlap: bool = True, |
| fddt_use_non_target: bool = True, |
| non_target_fddt_value: float = 1.0, |
| use_enrollments: bool = False, |
| scb_layers: int = None, |
| remove_timestamps_from_ctc: bool = False, |
| ctc_loss_reduction: str = "mean", |
| **kwargs |
| ): |
| super().__init__(**kwargs) |
| self.use_dicow_encoder = use_dicow_encoder |
| self.ctc_weight = ctc_weight |
| self.additional_layer = additional_layer |
| self.additional_self_attention_layer = additional_self_attention_layer |
| self.pre_ctc_sub_sample = pre_ctc_sub_sample |
| self.final_dropout = final_dropout |
| self.use_fddt = use_fddt |
| self.apply_fddt_to_n_layers = apply_fddt_to_n_layers |
| self.use_pre_pos_fddt = use_pre_pos_fddt |
| self.fddt_init = fddt_init |
| self.fddt_is_diagonal = fddt_is_diagonal |
| self.fddt_bias_only = fddt_bias_only |
| self.fddt_use_silence = fddt_use_silence |
| self.fddt_use_target = fddt_use_target |
| self.fddt_use_overlap = fddt_use_overlap |
| self.fddt_use_non_target = fddt_use_non_target |
| self.non_target_fddt_value = non_target_fddt_value |
| self.use_enrollments = use_enrollments |
| self.scb_layers = scb_layers |
| self.remove_timestamps_from_ctc = remove_timestamps_from_ctc |
| self.ctc_loss_reduction = ctc_loss_reduction |
|
|
|
|
| class DixtralConfig(VoxtralConfig): |
| def __init__( |
| self, |
| audio_config: dict = None, |
| num_soft_prompts: int = 0, |
| **kwargs |
| ): |
| |
| if audio_config is not None and not isinstance(audio_config, DixtralEncoderConfig): |
| audio_config = DixtralEncoderConfig(**audio_config) |
|
|
| super().__init__(audio_config=audio_config, **kwargs) |
| self.num_soft_prompts = num_soft_prompts |
|
|
