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    ÜÓ^j¯  ã                   ój   — d Z ddlmZ ddlmZ ddlmZ  ed¬«      e G d„ d	e«      «       «       Zd	gZy
)zLongT5 model configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringzgoogle/long-t5-local-base)Ú
checkpointc                   ó®  ‡ — e Zd ZU dZdZdgZdddddœZd	Zee	d
<   dZ
ee	d<   dZee	d<   dZee	d<   dZee	d<   dZedz  e	d<   dZee	d<   dZee	d<   dZee	d<   dZee	d<   dZee	d<   dZeez  e	d<   dZee	d<   dZee	d <   d!Zee	d"<   d#Zee	d$<   d%Zee	d&<   d#Zee	d'<   d(Zedz  e	d)<   d*Zee e   z  dz  e	d+<   dZ!edz  e	d,<   d-Z"ee	d.<   d#Z#ee	d/<   ˆ fd0„Z$d1„ Z%ˆ xZ&S )2ÚLongT5Configa!  
    d_ff (`int`, *optional*, defaults to 2048):
        Size of the intermediate feed forward layer in each `LongT5Block`.
    local_radius (`int`, *optional*, defaults to 127):
        Number of tokens to the left/right for each token to locally self-attend in a local attention mechanism.
    global_block_size (`int`, *optional*, defaults to 16):
        Length of blocks an input sequence is divided into for a global token representation. Used only for
        `encoder_attention_type = "transient-global"`.
    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.
    feed_forward_proj (`string`, *optional*, defaults to `"relu"`):
        Type of feed forward layer to be used. Should be one of `"relu"` or `"gated-gelu"`. LongT5v1.1 uses the
        `"gated-gelu"` feed forward projection. Original LongT5 implementation uses `"gated-gelu"`.
    encoder_attention_type (`string`, *optional*, defaults to `"local"`):
        Type of encoder attention to be used. Should be one of `"local"` or `"transient-global"`, which are
        supported by LongT5 implementation.
    Úlongt5Úpast_key_valuesÚd_modelÚ	num_headsÚ
num_layersÚd_kv)Úhidden_sizeÚnum_attention_headsÚnum_hidden_layersÚhead_dimi€}  Ú
vocab_sizei   é@   i   Úd_ffé   NÚnum_decoder_layersé   é   Úlocal_radiusé   Úglobal_block_sizeé    Úrelative_attention_num_bucketsé€   Úrelative_attention_max_distancegš™™™™™¹?Údropout_rateg�íµ ÷Æ°>Úlayer_norm_epsilong      ð?Úinitializer_factorÚreluÚfeed_forward_projTÚis_encoder_decoderÚlocalÚencoder_attention_typeÚ	use_cacher   Úpad_token_idé   Úeos_token_idÚbos_token_idFÚ
is_decoderÚtie_word_embeddingsc                 ó  •— | j                   �| j                   n| j                  | _         | j                  j                  d«      }|d   | _        |d   dk(  | _        | j                  dk(  rd| _        t        ‰| �  di |¤Ž y )Nú-éÿÿÿÿr   Úgatedz
gated-geluÚgelu_new© )r   r   r&   ÚsplitÚdense_act_fnÚis_gated_actÚsuperÚ__post_init__)ÚselfÚkwargsÚact_infoÚ	__class__s      €úz/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/longt5/configuration_longt5.pyr;   zLongT5Config.__post_init__N   s~   ø€ Ø=A×=TÑ=TÐ=` $×"9Ò"9Ðfj×fuÑfuˆÔØ×)Ñ)×/Ñ/°Ó4ˆØ$ R™LˆÔØ$ Q™K¨7Ñ2ˆÔà×!Ñ! \Ò1Ø *ˆDÔä‰ÑÑ' Ó'ó    c                 ó´   — | j                   j                  d«      }t        |«      dkD  r|d   dk7  st        |«      dkD  rt        d| j                   › d�«      ‚y)	zOPart of `@strict`-powered validation. Validates the architecture of the config.r2   r,   r   r4   é   z`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'N)r&   r7   ÚlenÚ
ValueError)r<   r>   s     r@   Úvalidate_architecturez"LongT5Config.validate_architectureY   sf   € à×)Ñ)×/Ñ/°Ó4ˆÜˆx‹=˜1Ò ¨!¡°Ò!7¼3¸x»=È1Ò;LÜØ'¨×(>Ñ(>Ð'?ð @)ð )óð ð <MrA   )'Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typeÚkeys_to_ignore_at_inferenceÚattribute_mapr   ÚintÚ__annotations__r   r   r   r   r   r   r   r   r   r!   r"   Úfloatr#   r$   r&   Ústrr'   Úboolr)   r*   r+   r-   Úlistr.   r/   r0   r;   rF   Ú__classcell__)r?   s   @r@   r	   r	      sC  ø… ñð( €JØ#4Ð"5Ðà Ø*Ø)Øñ	€Mð €J�ÓØ€GˆSÓØ€Dˆ#ƒNØ€Dˆ#ÓØ€J�ÓØ%)Ð˜˜d™
Ó)Ø€IˆsÓØ€L�#ÓØÐ�sÓØ*,Ð" CÓ,Ø+.Ð# SÓ.Ø #€L�%˜#‘+Ó#Ø $Ð˜Ó$Ø #Ð˜Ó#Ø#Ð�sÓ#Ø#Ð˜Ó#Ø")Ð˜CÓ)Ø€IˆtÓØ €L�#˜‘*Ó Ø+,€L�#˜˜S™	‘/ DÑ(Ó,Ø#€L�#˜‘*Ó#Ø€J�ÓØ $Ð˜Ó$ô	(örA   r	   N)	rJ   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r6   rA   r@   ú<module>rY      sK   ðñ !å .å 3Ý #ñ Ð6Ô7ØôIÐ#ó Ió ó 8ðIðX Ð
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