tj ddlmZddlmZddlmZedeGddeZedeGd d eZdd gZd S) )strict)PreTrainedConfig)auto_docstringz google/medasr) checkpointceZdZUdZdZdgZdZeed<dZ eed<dZ eed <d Z eed <d Z e ed <dZeed<dZeed<dZeed<dZeed<dZeed<dZeed<dZeed<dZeezed<dZeezed<dZeezed<dZeezed <dZeezed!<d"Zeed#<d$Zeed%<d&Zeed'<d(Ze ee!ed)fzed*<d+Z"e ee!ed)fzed,<d-Z#eed.<d/Z$e%d/zed0<fd1Z&xZ'S)2LasrEncoderConfiga convolution_bias (`bool`, *optional*, defaults to `False`): Whether to use bias in convolutions of the conformer's convolution module. conv_kernel_size (`int`, *optional*, defaults to 32): The kernel size of the convolution layers in the Conformer block. subsampling_conv_channels (`int`, *optional*, defaults to 256): The number of channels in the subsampling convolution layers. subsampling_conv_kernel_size (`int`, *optional*, defaults to 5): The kernel size of the subsampling convolution layers. subsampling_conv_stride (`int`, *optional*, defaults to 2): The stride of the subsampling convolution layers. dropout_positions (`float`, *optional*, defaults to 0.0): The dropout ratio for the positions in the input sequence. feed_forward_residual_weights (`tuple[float, float]`, *optional*, defaults to `[1.5, 0.5]`): The residual weights for the feed forward layers. conv_residual_weights (`tuple[float, float]`, *optional*, defaults to `[2.0, 1.0]`): The residual weights for the convolution layers. batch_norm_momentum (`float`, *optional*, defaults to 0.01): The momentum for the batch normalization layers Example: ```python >>> from transformers import LasrEncoderModel, LasrEncoderConfig >>> # Initializing a `LasrEncoder` configuration >>> configuration = LasrEncoderConfig() >>> # Initializing a model from the configuration >>> model = LasrEncoderModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` This configuration class is based on the LasrEncoder architecture from Google Health AI. You can find more details and pre-trained models at [google/medasr](https://huggingface.co/google/medasr). lasr_encoderpast_key_values hidden_sizenum_hidden_layersnum_attention_headsiintermediate_sizesilu hidden_actFattention_biasconvolution_bias conv_kernel_sizesubsampling_conv_channels num_mel_binssubsampling_conv_kernel_sizesubsampling_conv_strideg?dropoutgdropout_positions layerdropactivation_dropoutattention_dropouti'max_position_embeddingsg{Gz?initializer_rangegư>layer_norm_eps)g?g?.feed_forward_residual_weights)g@g?conv_residual_weightsg{Gz?batch_norm_momentumNrope_parametersc R|j|_tjdi|dSN)rnum_key_value_headssuper __post_init__selfkwargs __class__s i/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/lasr/configuration_lasr.pyr2zLasrEncoderConfig.__post_init__`s1#'#; ''''''')(__name__ __module__ __qualname____doc__ model_typekeys_to_ignore_at_inferencer int__annotations__rrrrstrrboolrrrrrr r!floatr"r#r$r%r&r'r(r)listtupler*r+r,dictr2 __classcell__r6s@r7r r s!$$L J#4"5Ks    !s!!!J ND   "d"""c%(s(((L#() #)))#$S$$$GUS[%(us{((( Ius{   &) )))%(us{(((#(S(((#u### NE   EO!4;ucz1B#BOOO=G4;ucz)::GGG!%%%%#'OTD['''(((((((((r8r ceZdZUdZdZdeiZdZee d<dZ e e d<dZ e e d <d Zeezd ze d<d Zee d <fd ZedZxZS) LasrCTCConfigaE ctc_loss_reduction (`str`, *optional*, defaults to `"mean"`): Specifies the reduction to apply to the output of `torch.nn.CTCLoss`. Only relevant when training an instance of [`LasrForCTC`]. ctc_zero_infinity (`bool`, *optional*, defaults to `True`): Whether to zero infinite losses and the associated gradients of `torch.nn.CTCLoss`. Infinite losses mainly occur when the inputs are too short to be aligned to the targets. Only relevant when training an instance of [`LasrForCTC`]. Example: ```python >>> from transformers import LasrForCTC, LasrCTCConfig >>> # Initializing a Lasr configuration >>> configuration = LasrCTCConfig() >>> # Initializing a model from the configuration >>> model = LasrForCTC(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` This configuration class is based on the Lasr CTC architecture from Google Health AI. You can find more details and pre-trained models at [google/medasr](https://huggingface.co/google/medasr). lasr_ctcencoder_configr vocab_sizemeanctc_loss_reductionTctc_zero_infinityNr pad_token_idc t|jtrtdi|j|_n|jt|_|jj|_t jdi|dSr.) isinstancerLrFr r'r1r2r3s r7r2zLasrCTCConfig.__post_init__s| d)4 0 0 6"3"J"Jd6I"J"JD    ("3"5"5D !%!4!F'''''''r8c |jjdzS)Nr)rLr )r4s r7inputs_to_logits_ratioz$LasrCTCConfig.inputs_to_logits_ratios":A==r8)r9r:r;r<r=r sub_configsrMr?r@rOrArPrBrLrFrrQr2propertyrUrGrHs@r7rJrJes.J#%67KJ$$$$"t"""59ND++d2999L#(((((>>X>>>>>r8rJN) huggingface_hub.dataclassesrconfiguration_utilsrutilsrr rJ__all__r/r8r7r\s*/.....333333######?+++E(E(E(E(E((E(E(,+E(P?++++>+>+>+>+>$+>+>,++>\  0r8