
    gCM                         d Z ddlZddlmZ ddlmZ ddlmZ  ej        e	          Z
 G d de          Z G d	 d
e          Z G d de          Zg dZdS )zAltCLIP model configuration    N)Union   )PretrainedConfig)loggingc                   N     e Zd ZdZdZ	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 d fd	Z xZS )AltCLIPTextConfiga  
    This is the configuration class to store the configuration of a [`AltCLIPTextModel`]. It is used to instantiate a
    AltCLIP text 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 AltCLIP
    [BAAI/AltCLIP](https://huggingface.co/BAAI/AltCLIP) architecture.

    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 250002):
            Vocabulary size of the AltCLIP model. Defines the number of different tokens that can be represented by the
            `inputs_ids` passed when calling [`AltCLIPTextModel`].
        hidden_size (`int`, *optional*, defaults to 1024):
            Dimensionality of the encoder layers and the pooler layer.
        num_hidden_layers (`int`, *optional*, defaults to 24):
            Number of hidden layers in the Transformer encoder.
        num_attention_heads (`int`, *optional*, defaults to 16):
            Number of attention heads for each attention layer in the Transformer encoder.
        intermediate_size (`int`, *optional*, defaults to 4096):
            Dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer encoder.
        hidden_act (`str` or `Callable`, *optional*, defaults to `"gelu"`):
            The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
            `"relu"`, `"silu"` and `"gelu_new"` are supported.
        hidden_dropout_prob (`float`, *optional*, defaults to 0.1):
            The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
        attention_probs_dropout_prob (`float`, *optional*, defaults to 0.1):
            The dropout ratio for the attention probabilities.
        max_position_embeddings (`int`, *optional*, defaults to 514):
            The maximum sequence length that this model might ever be used with. Typically set this to something large
            just in case (e.g., 512 or 1024 or 2048).
        type_vocab_size (`int`, *optional*, defaults to 1):
            The vocabulary size of the `token_type_ids` passed when calling [`AltCLIPTextModel`]
        initializer_range (`float`, *optional*, defaults to 0.02):
            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
        initializer_factor (`float`, *optional*, defaults to 0.02):
            A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
            testing).
        layer_norm_eps (`float`, *optional*, defaults to 1e-05):
            The epsilon used by the layer normalization layers.
        pad_token_id (`int`, *optional*, defaults to 1): The id of the *padding* token.
        bos_token_id (`int`, *optional*, defaults to 0): 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.
        position_embedding_type (`str`, *optional*, defaults to `"absolute"`):
            Type of position embedding. Choose one of `"absolute"`, `"relative_key"`, `"relative_key_query"`. For
            positional embeddings use `"absolute"`. For more information on `"relative_key"`, please refer to
            [Self-Attention with Relative Position Representations (Shaw et al.)](https://arxiv.org/abs/1803.02155).
            For more information on `"relative_key_query"`, please refer to *Method 4* in [Improve Transformer Models
            with Better Relative Position Embeddings (Huang et al.)](https://arxiv.org/abs/2009.13658).
        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`.
        project_dim (`int`, *optional*, defaults to 768):
            The dimensions of the teacher model before the mapping layer.

    Examples:

    ```python
    >>> from transformers import AltCLIPTextModel, AltCLIPTextConfig

    >>> # Initializing a AltCLIPTextConfig with BAAI/AltCLIP style configuration
    >>> configuration = AltCLIPTextConfig()

    >>> # Initializing a AltCLIPTextModel (with random weights) from the BAAI/AltCLIP style configuration
    >>> model = AltCLIPTextModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```altclip_text_model             gelu皙?     {Gz?h㈵>r      absoluteT   c                 "    t                      j        d|||d| || _        || _        || _        || _        || _        || _        || _        || _	        |	| _
        |
| _        || _        || _        || _        || _        || _        || _        d S )N)pad_token_idbos_token_ideos_token_id )super__init__
vocab_sizehidden_sizenum_hidden_layersnum_attention_heads
hidden_actintermediate_sizehidden_dropout_probattention_probs_dropout_probmax_position_embeddingstype_vocab_sizeinitializer_rangeinitializer_factorlayer_norm_epsposition_embedding_type	use_cacheproject_dim)selfr   r    r!   r"   r$   r#   r%   r&   r'   r(   r)   r*   r+   r   r   r   r,   r-   r.   kwargs	__class__s                        m/var/www/html/ai-engine/env/lib/python3.11/site-packages/transformers/models/altclip/configuration_altclip.pyr   zAltCLIPTextConfig.__init__f   s    . 	sl\hsslrsss$&!2#6 $!2#6 ,H)'>$.!2"4,'>$"&    )r
   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   Tr   )__name__
__module____qualname____doc__
model_typer   __classcell__r1   s   @r2   r   r      s        F FP &J %( # *)(' (' (' (' (' (' (' (' (' ('r3   r   c                   |     e Zd ZdZdZ	 	 	 	 	 	 	 	 	 	 	 	 	 d fd	Zedeee	j
        f         ddfd            Z xZS )AltCLIPVisionConfiga  
    This is the configuration class to store the configuration of a [`AltCLIPModel`]. It is used to instantiate an
    AltCLIP 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 AltCLIP
    [BAAI/AltCLIP](https://huggingface.co/BAAI/AltCLIP) architecture.

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


    Args:
        hidden_size (`int`, *optional*, defaults to 768):
            Dimensionality of the encoder layers and the pooler layer.
        intermediate_size (`int`, *optional*, defaults to 3072):
            Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
        projection_dim (`int`, *optional*, defaults to 512):
            Dimensionality of text and vision projection layers.
        num_hidden_layers (`int`, *optional*, defaults to 12):
            Number of hidden layers in the Transformer encoder.
        num_attention_heads (`int`, *optional*, defaults to 12):
            Number of attention heads for each attention layer in the Transformer encoder.
        num_channels (`int`, *optional*, defaults to 3):
            The number of input channels.
        image_size (`int`, *optional*, defaults to 224):
            The size (resolution) of each image.
        patch_size (`int`, *optional*, defaults to 32):
            The size (resolution) of each patch.
        hidden_act (`str` or `function`, *optional*, defaults to `"quick_gelu"`):
            The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
            `"relu"`, `"selu"` and `"gelu_new"` `"quick_gelu"` are supported.
        layer_norm_eps (`float`, *optional*, defaults to 1e-05):
            The epsilon used by the layer normalization layers.
        attention_dropout (`float`, *optional*, defaults to 0.0):
            The dropout ratio for the attention probabilities.
        initializer_range (`float`, *optional*, defaults to 0.02):
            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
        initializer_factor (`float`, *optional*, defaults to 1.0):
            A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
            testing).

    Example:

    ```python
    >>> from transformers import AltCLIPVisionConfig, AltCLIPVisionModel

    >>> # Initializing a AltCLIPVisionConfig with BAAI/AltCLIP style configuration
    >>> configuration = AltCLIPVisionConfig()

    >>> # Initializing a AltCLIPVisionModel (with random weights) from the BAAI/AltCLIP style configuration
    >>> model = AltCLIPVisionModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```altclip_vision_modelr            r          
quick_gelur           r         ?c                      t                      j        di | || _        || _        || _        || _        || _        || _        || _        || _	        || _
        || _        || _        |
| _        |	| _        d S )Nr   )r   r   r    r$   projection_dimr!   r"   num_channels
patch_size
image_sizer)   r*   attention_dropoutr+   r#   )r/   r    r$   rG   r!   r"   rH   rJ   rI   r#   r+   rK   r)   r*   r0   r1   s                  r2   r   zAltCLIPVisionConfig.__init__   s    " 	""6"""&!2,!2#6 ($$!2"4!2,$r3   pretrained_model_name_or_pathreturnr   c                 N   |                      |            | j        |fi |\  }}|                    d          dk    r|d         }d|v rMt          | d          r=|d         | j        k    r,t
                              d|d          d| j         d            | j        |fi |S )Nr8   altclipvision_configzYou are using a model of type z  to instantiate a model of type zN. This is not supported for all configurations of models and can yield errors.)_set_token_in_kwargsget_config_dictgethasattrr8   loggerwarning	from_dict)clsrL   r0   config_dicts       r2   from_pretrainedz#AltCLIPVisionConfig.from_pretrained   s      (((1c12OZZSYZZV ??<((I55%o6K;&&73+E+E&+VbJcgjguJuJuNNr\1J r r>r r r  
 s}[33F333r3   )r   r>   r?   r@   r@   r   rA   rB   rC   r   rD   r   rE   )r4   r5   r6   r7   r8   r   classmethodr   strosPathLikerZ   r9   r:   s   @r2   r<   r<      s        5 5n (J % % % % % %B 4E#r{BR<S 4bt 4 4 4 [4 4 4 4 4r3   r<   c                   J     e Zd ZdZdZ	 d
 fd	Zededefd	            Z	 xZ
S )AltCLIPConfiga  
    This is the configuration class to store the configuration of a [`AltCLIPModel`]. It is used to instantiate an
    AltCLIP 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 AltCLIP
    [BAAI/AltCLIP](https://huggingface.co/BAAI/AltCLIP) architecture.

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

    Args:
        text_config (`dict`, *optional*):
            Dictionary of configuration options used to initialize [`AltCLIPTextConfig`].
        vision_config (`dict`, *optional*):
            Dictionary of configuration options used to initialize [`AltCLIPVisionConfig`].
        projection_dim (`int`, *optional*, defaults to 768):
            Dimensionality of text and vision projection layers.
        logit_scale_init_value (`float`, *optional*, defaults to 2.6592):
            The initial value of the *logit_scale* parameter. Default is used as per the original CLIP implementation.
        kwargs (*optional*):
            Dictionary of keyword arguments.

    Example:

    ```python
    >>> from transformers import AltCLIPConfig, AltCLIPModel

    >>> # Initializing a AltCLIPConfig with BAAI/AltCLIP style configuration
    >>> configuration = AltCLIPConfig()

    >>> # Initializing a AltCLIPModel (with random weights) from the BAAI/AltCLIP style configuration
    >>> model = AltCLIPModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config

    >>> # We can also initialize a AltCLIPConfig from a AltCLIPTextConfig and a AltCLIPVisionConfig

    >>> # Initializing a AltCLIPText and AltCLIPVision configuration
    >>> config_text = AltCLIPTextConfig()
    >>> config_vision = AltCLIPVisionConfig()

    >>> config = AltCLIPConfig.from_text_vision_configs(config_text, config_vision)
    ```rO   Nr   /L
F@c                 "   |                     dd           }|                     dd           } t                      j        di | ||i }t          di |                                }|                                D ]G\  }	}
|	|v r>|
||	         k    r2|	dvr.|	|v r
d|	 d|	 d}nd|	 d}t                              |           H|                    |           ||i }t          di |                                }d	|v r'd
 |d	                                         D             |d	<   |                                D ]G\  }	}
|	|v r>|
||	         k    r2|	dvr.|	|v r
d|	 d|	 d}nd|	 d}t                              |           H|                    |           |i }t                              d           |i }t                              d           t          di || _
        t          di || _        || _        || _        d| _        d S )Ntext_config_dictvision_config_dict)transformers_version`zp` is found in both `text_config_dict` and `text_config` but with different values. The value `text_config_dict["z"]` will be used instead.zm`text_config_dict` is provided which will be used to initialize `AltCLIPTextConfig`. The value `text_config["z"]` will be overridden.id2labelc                 4    i | ]\  }}t          |          |S r   )r\   ).0keyvalues      r2   
<dictcomp>z*AltCLIPConfig.__init__.<locals>.<dictcomp>_  s1     3 3 3(2UCHHe3 3 3r3   zv` is found in both `vision_config_dict` and `vision_config` but with different values. The value `vision_config_dict["zs`vision_config_dict` is provided which will be used to initialize `AltCLIPVisionConfig`. The value `vision_config["zR`text_config` is `None`. Initializing the `AltCLIPTextConfig` with default values.zV`vision_config` is `None`. initializing the `AltCLIPVisionConfig` with default values.rE   r   )popr   r   r   to_dictitemsrU   infoupdater<   text_configrP   rG   logit_scale_init_valuer*   )r/   rr   rP   rG   rs   r0   rc   rd   _text_config_dictrj   rk   message_vision_config_dictr1   s                r2   r   zAltCLIPConfig.__init__.  s    "::&8$??#ZZ(<dCC""6"""
 '"  !2 E E4D E E M M O O 05577 ) )
U+%%%;s3C*C*CSkHkHk...[ [ [<?[ [ [  P36P P P   KK((( 0111)$ " #6"K"K8J"K"K"S"S"U"U0003 36I*6U6[6[6]6]3 3 3#J/
 27799 ) )
U-''E]35G,G,GCWoLoLo000e e eFIe e e  V9<V V V   KK(((   !4555KKKlmmm MKKpqqq,;;{;;0AA=AA,&<#"%r3   rr   rP   c                 `     | d|                                 |                                 d|S )z
        Instantiate a [`AltCLIPConfig`] (or a derived class) from altclip text model configuration and altclip vision
        model configuration.

        Returns:
            [`AltCLIPConfig`]: An instance of a configuration object
        )rr   rP   r   )rn   )rX   rr   rP   r0   s       r2   from_text_vision_configsz&AltCLIPConfig.from_text_vision_configs  s:     sf{2244MDYDYD[D[ff_efffr3   )NNr   ra   )r4   r5   r6   r7   r8   r   r[   r   r<   rx   r9   r:   s   @r2   r`   r`      s        * *X J `fV& V& V& V& V& V&p 	g3D 	gUh 	g 	g 	g [	g 	g 	g 	g 	gr3   r`   )r   r<   r`   )r7   r]   typingr   configuration_utilsr   utilsr   
get_loggerr4   rU   r   r<   r`   __all__r   r3   r2   <module>r~      s   " ! 				       3 3 3 3 3 3       
	H	%	%s' s' s' s' s'( s' s' s'lk4 k4 k4 k4 k4* k4 k4 k4\Qg Qg Qg Qg Qg$ Qg Qg Qgh H
G
Gr3   