§
    ‚Štjî  ã                   óŒ   — d dl m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	d
S )é    )Ústricté   )ÚPreTrainedConfig)ÚRopeParameters)Úauto_docstringzTHUDM/glm-4-9b-chat)Ú
checkpointc                   ó¸  ‡ — e Zd ZU dZdZdgZdddddddœZd	gd
gfddgdgfdgdgf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	dz  e
d<   dZee
d<   dZee	z  dz  e
d <   d!Ze	e
d"<   d#Zee
d$<   d%Zee
d&<   d'Zee
d(<   d)Zee
d*<   dZeez  dz  e
d+<   d,Ze	dz  e
d-<   dZe	e e	         z  dz  e
d.<   dZ!e	dz  e
d/<   d'Z"ee
d0<   ˆ fd1„Z#ˆ xZ$S )2Ú	GlmConfiga  
    Example:

    ```python
    >>> from transformers import GlmModel, GlmConfig
    >>> # Initializing a Glm glm-4-9b-chat style configuration
    >>> configuration = GlmConfig()
    >>> # Initializing a model from the glm-4-9b-chat style configuration
    >>> model = GlmModel(configuration)
    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```ÚglmÚpast_key_valuesÚcolwiseÚrowwiseÚcolwise_gather_outputÚrowwise_split_input)zlayers.*.self_attn.q_projzlayers.*.self_attn.k_projzlayers.*.self_attn.v_projzlayers.*.self_attn.o_projzlayers.*.mlp.gate_up_projzlayers.*.mlp.down_projÚ	input_idsÚinputs_embedsÚhidden_statesÚattention_mask)Úembed_tokensÚlayersÚnormi P Ú
vocab_sizei   Úhidden_sizei€5  Úintermediate_sizeé(   Únum_hidden_layersé    Únum_attention_headsé   NÚnum_key_value_headsé€   Úhead_dimÚsiluÚ
hidden_actg        Úattention_dropouti   Úmax_position_embeddingsg{®Gáz”?Úinitializer_rangegñhãˆµø„>Úrms_norm_epsTÚ	use_cacheFÚtie_word_embeddingsÚrope_parametersé!O Úpad_token_idÚeos_token_idÚbos_token_idÚattention_biasc                 ó†   •— |                      dd¦  «         | j        €	g d¢| _         t          ¦   «         j        di |¤Ž d S )NÚpartial_rotary_factorg      à?)r,   i(O i*O © )Ú
setdefaultr.   ÚsuperÚ__post_init__)ÚselfÚkwargsÚ	__class__s     €úg/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/glm/configuration_glm.pyr6   zGlmConfig.__post_init__L   sT   ø€ Ø×ÒÐ1°3Ñ7Ô7Ð7ØÔÐ$Ø 8Ð 8Ð 8ˆDÔØ�‰ŒÔÐ'Ð' Ð'Ð'Ð'Ð'Ð'ó    )%Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typeÚkeys_to_ignore_at_inferenceÚbase_model_tp_planÚbase_model_pp_planr   ÚintÚ__annotations__r   r   r   r   r    r"   r$   Ústrr%   Úfloatr&   r'   r(   r)   Úboolr*   r+   r   Údictr-   r.   Úlistr/   r0   r6   Ú__classcell__)r9   s   @r:   r
   r
      s  ø€ € € € € € ðð ð €JØ#4Ð"5Ðà%.Ø%.Ø%.Ø%.Ø%<Ø"7ðð Ðð &˜¨Ð(9Ð:Ø#Ð%5Ð6¸Ð8IÐJØ!Ð" _Ð$5Ð6ðð Ðð €J�ÐÐÑØ€K�ÐÐÑØ"Ð�sÐ"Ð"Ñ"ØÐ�sÐÐÑØ!Ð˜Ð!Ð!Ñ!Ø&'Ð˜˜t™Ð'Ð'Ñ'Ø€Hˆc�D‰jÐÐÑØ€J�ÐÐÑØ,/Ð�u˜s‘{ TÑ)Ð/Ð/Ñ/Ø#)Ð˜SÐ)Ð)Ñ)Ø#Ð�uÐ#Ð#Ñ#Ø'€L�%Ð'Ð'Ñ'Ø€IˆtÐÐÑØ %Ð˜Ð%Ð%Ñ%Ø48€O�^ dÑ*¨TÑ1Ð8Ð8Ñ8Ø%€L�#˜‘*Ð%Ð%Ñ%Ø+/€L�#˜˜Sœ	‘/ DÑ(Ð/Ð/Ñ/Ø#€L�#˜‘*Ð#Ð#Ñ#Ø€N�DÐÐÑð(ð (ð (ð (ð (ð (ð (ð (ð (r;   r
   N)
Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úmodeling_rope_utilsr   Úutilsr   r
   Ú__all__r3   r;   r:   ú<module>rQ      s­   ðð" /Ð .Ð .Ð .Ð .Ð .à 3Ð 3Ð 3Ð 3Ð 3Ð 3Ø 1Ð 1Ð 1Ð 1Ð 1Ð 1Ø #Ð #Ð #Ð #Ð #Ð #ð €Ð0Ð1Ñ1Ô1Øð6(ð 6(ð 6(ð 6(ð 6(Ð ñ 6(ô 6(ñ „ñ 2Ô1ð6(ðr ˆ-€€€r;   