
    <h'                     p    S r SSKJr  SSKJr  SSKJrJr  \R                  " \	5      r
 " S S\5      rS/rg)	zFuyu model configuration   )PretrainedConfig)logging   )CONFIG_MAPPING
AutoConfigc                   z   ^  \ rS rSrSrSrS\0rS/r                         S	U 4S jjr	S r
SrU =r$ )

FuyuConfig   a  
This is the configuration class to store the configuration of a [`FuyuForCausalLM`]. It is used to instantiate an
Fuyu 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
[adept/fuyu-8b](https://huggingface.co/adept/fuyu-8b).

Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information.


Args:
    vocab_size (`int`, *optional*, defaults to 262144):
        Vocabulary size of the Fuyu model. Defines the number of different tokens that can be represented by the
        `inputs_ids` passed when calling [`FuyuForCausalLM`]
    hidden_size (`int`, *optional*, defaults to 4096):
        Dimension of the hidden representations.
    intermediate_size (`int`, *optional*, defaults to 16384):
        Dimension of the MLP representations.
    num_hidden_layers (`int`, *optional*, defaults to 36):
        Number of hidden layers in the Transformer encoder.
    num_attention_heads (`int`, *optional*, defaults to 64):
        Number of attention heads for each attention layer in the Transformer encoder.
    hidden_act (`str` or `function`, *optional*, defaults to `"relu2"`):
        The non-linear activation function (function or string) in the decoder.
    max_position_embeddings (`int`, *optional*, defaults to 16384):
        The maximum sequence length that this model might ever be used with.
    image_size (`int`, *optional*, defaults to 300):
        The input image size.
    patch_size (`int`, *optional*, defaults to 30):
        The input vision transformer encoding patch size.
    num_channels (`int`, *optional*, defaults to 3):
        The input image number of channels.
    initializer_range (`float`, *optional*, defaults to 0.02):
        The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
    layer_norm_eps (`float`, *optional*, defaults to 1e-05):
        The epsilon used by the rms normalization layers.
    use_cache (`bool`, *optional*, defaults to `True`):
        Whether or not the model should return the last key/values attentions (not used by all models). Only
        relevant if `config.is_decoder=True`. Whether to tie weight embeddings
    tie_word_embeddings (`bool`, *optional*, defaults to `False`):
        Whether to tie input and output embeddings.
    rope_theta (`float`, *optional*, defaults to 25000.0):
        The base period of the RoPE embeddings.
    rope_scaling (`Dict`, *optional*):
        Dictionary containing the scaling configuration for the RoPE embeddings. Currently supports two scaling
        strategies: linear and dynamic. Their scaling factor must be a float greater than 1. The expected format is
        `{"type": strategy name, "factor": scaling factor}`. When using this flag, don't update
        `max_position_embeddings` to the expected new maximum. See the following thread for more information on how
        these scaling strategies behave:
        https://www.reddit.com/r/LocalFuyu/comments/14mrgpr/dynamically_scaled_rope_further_increases/. This is an
        experimental feature, subject to breaking API changes in future versions.
    qk_layernorm (`bool`, *optional*, defaults to `True`):
        Whether or not to normalize the Queries and Keys after projecting the hidden states
    hidden_dropout (`float`, *optional*, defaults to 0.0):
        The dropout ratio after applying the MLP to the hidden states.
    attention_dropout (`float`, *optional*, defaults to 0.0):
        The dropout ratio after computing the attention scores.
    partial_rotary_factor (`float`, *optional*, defaults to 0.5):
        Percentage of the query and keys which will have rotary embedding.

    pad_token_id (`int`, *optional*):
        The id of the *padding* token.
    bos_token_id (`int`, *optional*, defaults to 1):
        The id of the *beginning-of-sequence* token.
    eos_token_id (`Union[int, list[int]]`, *optional*, defaults to 2):
        The id of the *end-of-sequence* token. Optionally, use a list to set multiple *end-of-sequence* tokens.
    image_token_id (`int`, *optional*, defaults to 71011):
        The id of the image placeholder token.
    text_config (`dict`, *optional*):
        Dictionary of configuration options used to initialize the `language``[`Aut`].

```python
>>> from transformers import FuyuConfig

>>> # Initializing a Fuyu fuyu-7b style configuration
>>> configuration = FuyuConfig()
```fuyutext_configpast_key_valuesc                 >  > UcP  0 SU_SU_SU_SU_SU_SU_SU_SU_S	U_S
U_SU_SU_SU_SU_SU_SU_SU_UUUS.En[         R                  S5        UR                  SS5      n[        U   " S0 UD6U l        Xl        Xpl        Xl        Xl        Xl	        X l
        X0l        X@l        XPl        X`l        Xl        Xl        Xl        Xl        UU l        UU l        UU l        UU l        UU l        UU l        U R3                  5         [4        TU ]l  " SUUUUS.UD6  g )N
vocab_sizemax_position_embeddingshidden_sizeintermediate_sizenum_hidden_layersnum_attention_heads
hidden_actinitializer_rangelayer_norm_eps	use_cache
rope_thetarope_scalingqk_layernormhidden_dropoutattention_dropoutpartial_rotary_factorpad_token_id)bos_token_ideos_token_idtie_word_embeddingszEtext_config is None. initializing the text model with default values.
model_type	persimmon)r   r    r!   r"    )loggerinfogetr   r   _vocab_sizer   
image_size
patch_sizenum_channelsr   r   r   r   r   r   r   r   r   r   r   r   r   r   image_token_id_rope_scaling_validationsuper__init__)selfr   r   r   r   r   r   r   r*   r+   r,   r   r   r   r"   r   r   r   r   r   r   r   r    r!   r-   r   kwargstext_model_type	__class__s                               c/var/www/html/shao/venv/lib/python3.13/site-packages/transformers/models/fuyu/configuration_fuyu.pyr0   FuyuConfig.__init__l   s   : j)+B { $%6	
 $%6 &': j $%6 !. Y j   !. $%6  ()>!" #$ !- ,':)K, KK_`%//,D)/:I[I%'>$$$(&!2!2#6 $!2,"$((,!2%:",%%' 	
%%% 3		

 	
    c                    U R                   c  g[        U R                   [        5      (       a  [        U R                   5      S:w  a  [	        SU R                    35      eU R                   R                  SS5      nU R                   R                  SS5      nUb  US;  a  [	        SU 35      eUb  [        U[        5      (       a  US::  a  [	        S	U 35      eg)
z,
Validate the `rope_scaling` configuration.
Nr   zN`rope_scaling` must be a dictionary with two fields, `type` and `factor`, got typefactor)lineardynamiczF`rope_scaling`'s type field must be one of ['linear', 'dynamic'], got g      ?z7`rope_scaling`'s factor field must be a float > 1, got )r   
isinstancedictlen
ValueErrorr(   float)r1   rope_scaling_typerope_scaling_factors      r5   r.   #FuyuConfig._rope_scaling_validation   s     $$++T22c$:K:K6LPQ6Q`aearar`st  !--11&$?"//33HdC$(9AV(VXYjXkl  &j9Le.T.TXkorXrVWjVklmm Ysr7   )r)   r   r   r   r   r*   r-   r   r   r   r   r   r,   r   r   r+   r   r   r   r   r   )i   i    @  $   @   relu2rE   i,     r   g{Gz?gh㈵>TFg     j@NT        rJ   g      ?N   r   ic N)__name__
__module____qualname____firstlineno____doc__r#   r   sub_configskeys_to_ignore_at_inferencer0   r.   __static_attributes____classcell__)r4   s   @r5   r	   r	      s    L\ J *-K#4"5  %!!5T
ln nr7   r	   N)rP   configuration_utilsr   utilsr   autor   r   
get_loggerrL   r&   r	   __all__r%   r7   r5   <module>rZ      s@     3  - 
		H	%{n! {n| .r7   