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from typing import Optional |
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from transformers import WhisperConfig |
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class DiCoWConfig(WhisperConfig): |
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"""This is a modified version of the `WhisperEncoder` model from the `transformers` library. |
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The model has been modified to support CTC loss computation in the forward pass.""" |
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model_type = "DiCoW" |
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def __init__( |
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self, |
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ctc_loss_reduction: str = "mean", |
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final_dropout: float = 0.0, |
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ctc_zero_infinity: bool = False, |
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ctc_weight: float = 0.0, |
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blank_token_id: Optional[int] = None, |
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additional_layer: bool = False, |
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additional_self_attention_layer: bool = False, |
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pre_ctc_sub_sample: bool = False, |
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use_fddt: bool = True, |
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fddt_is_diagonal: bool = True, |
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fddt_bias_only: bool = False, |
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fddt_use_silence: bool = True, |
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fddt_use_target: bool = True, |
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fddt_use_overlap: bool = True, |
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fddt_use_non_target: bool = True, |
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remove_timestamps_from_ctc: bool = False, |
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apply_fddt_to_n_layers: int = -1, |
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fddt_init: str = 'suppressive', |
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non_target_fddt_value: float = 0.0, |
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use_enrollments: bool = False, |
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scb_layers: Optional[int] = None, |
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use_pre_pos_fddt: bool = False, |
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**kwargs, |
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): |
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super().__init__(**kwargs) |
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self.ctc_loss_reduction = ctc_loss_reduction |
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self.final_dropout = final_dropout |
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self.ctc_zero_infinity = ctc_zero_infinity |
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self.ctc_weight = ctc_weight |
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self.blank_token_id = blank_token_id |
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self.additional_layer = additional_layer |
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self.additional_self_attention_layer = additional_self_attention_layer |
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self.pre_ctc_sub_sample = pre_ctc_sub_sample |
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self.use_fddt = use_fddt |
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self.fddt_is_diagonal = fddt_is_diagonal |
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self.fddt_bias_only = fddt_bias_only |
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self.fddt_use_silence = fddt_use_silence |
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self.fddt_use_target = fddt_use_target |
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self.fddt_use_overlap = fddt_use_overlap |
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self.fddt_use_non_target = fddt_use_non_target |
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self.remove_timestamps_from_ctc = remove_timestamps_from_ctc |
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self.apply_fddt_to_n_layers = apply_fddt_to_n_layers |
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self.fddt_init = fddt_init |
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self.non_target_fddt_value = non_target_fddt_value |
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self.use_enrollments = use_enrollments |
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self.scb_layers = scb_layers |
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self.use_pre_pos_fddt = use_pre_pos_fddt |
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_HIDDEN_STATES_START_POSITION = 2 |
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