fThSrSSKJr SSKJr SSKJr SSKJr \R"\ 5r "SS\5r "S S \5r SS /rg ) zT5 model configuration)Mapping)PretrainedConfig)OnnxSeq2SeqConfigWithPast)loggingcl^\rSrSrSrSrS/rSSSSS .rS U4S jjrS r U=r $) T5Configa& This is the configuration class to store the configuration of a [`T5Model`] or a [`TFT5Model`]. It is used to instantiate a T5 model according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the T5 [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Arguments: vocab_size (`int`, *optional*, defaults to 32128): Vocabulary size of the T5 model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`T5Model`] or [`TFT5Model`]. d_model (`int`, *optional*, defaults to 512): Size of the encoder layers and the pooler layer. d_kv (`int`, *optional*, defaults to 64): Size of the key, query, value projections per attention head. The `inner_dim` of the projection layer will be defined as `num_heads * d_kv`. d_ff (`int`, *optional*, defaults to 2048): Size of the intermediate feed forward layer in each `T5Block`. num_layers (`int`, *optional*, defaults to 6): Number of hidden layers in the Transformer encoder. num_decoder_layers (`int`, *optional*): Number of hidden layers in the Transformer decoder. Will use the same value as `num_layers` if not set. num_heads (`int`, *optional*, defaults to 8): Number of attention heads for each attention layer in the Transformer encoder. relative_attention_num_buckets (`int`, *optional*, defaults to 32): The number of buckets to use for each attention layer. relative_attention_max_distance (`int`, *optional*, defaults to 128): The maximum distance of the longer sequences for the bucket separation. dropout_rate (`float`, *optional*, defaults to 0.1): The ratio for all dropout layers. classifier_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for classifier. layer_norm_eps (`float`, *optional*, defaults to 1e-6): The epsilon used by the layer normalization layers. initializer_factor (`float`, *optional*, defaults to 1): A factor for initializing all weight matrices (should be kept to 1, used internally for initialization testing). feed_forward_proj (`string`, *optional*, defaults to `"relu"`): Type of feed forward layer to be used. Should be one of `"relu"` or `"gated-gelu"`. T5v1.1 uses the `"gated-gelu"` feed forward projection. Original T5 uses `"relu"`. use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). t5past_key_valuesd_model num_heads num_layersd_kv) hidden_sizenum_attention_headsnum_hidden_layershead_dimc >XlX lX0lX@lXPlUbUO URUlXplXlXlXl UUl Xl Xl Xl XlURRS5nUSUlUSS:HUl[%U5S:a USS:wd[%U5S:a['SU S35eU S :XaS Ul[(TU]T"S UUUS .UD6 g) N-rgatedz`feed_forward_proj`: z is not a valid activation function of the dense layer. Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. 'gated-gelu' or 'relu'z gated-gelugelu_new) pad_token_id eos_token_idis_encoder_decoder) vocab_sizer rd_ffrnum_decoder_layersrrelative_attention_num_bucketsrelative_attention_max_distance dropout_rateclassifier_dropoutlayer_norm_epsiloninitializer_factorfeed_forward_proj use_cachesplit dense_act_fn is_gated_actlen ValueErrorsuper__init__)selfr r rr!rr"rr#r$r%r'r(r)rr*rrr&kwargsact_info __class__s _/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/t5/configuration_t5.pyr1T5Config.__init__Ss,%   $"4"@ doo #.L+/N,("4"4"4!2"))//4$RL$QK72 x=1 !!73x=1;L'(9':;))   , *D   %%1   )r&r!rr r,r%r)r(r-r'r"rrr$r#r*r )i}i@iN g?gư>g?reluTTrrg) __name__ __module__ __qualname____firstlineno____doc__ model_typekeys_to_ignore_at_inference attribute_mapr1__static_attributes__ __classcell__)r5s@r6r r sn,\J#4"5 *) M  ')(+ '< < r8r cX\rSrSr\S\\\\\444Sj5r\S\4Sj5r Sr g) T5OnnxConfigreturncSSS.SSS.S.nUR(aSUSS'SS0US 'SS S.US 'OSS S.US 'SS S.US 'UR(aURUS S9 U$)Nbatchencoder_sequence)rr) input_idsattention_maskz past_encoder_sequence + sequencerQrrdecoder_input_idsz past_decoder_sequence + sequencedecoder_attention_maskdecoder_sequenceinputs) direction)use_pastfill_with_past_key_values_)r2 common_inputss r6rUT5OnnxConfig.inputss%);<").@A  ==1SM* +A .23WM- .:AFh6iM2 35risQ3-   H %t t n,2 ~ &r8