fTh:SSKJr SSKJr SSKJr SSKJrJr \R"\ 5r "SS\5r "S S \5r "S S \5r/S Qrg))List)PretrainedConfig)logging)CONFIG_MAPPING AutoConfigc\^\rSrSrSrSrSrSU4SjjrSrU=r $)JanusVisionConfig a^ This is the configuration class to store the configuration of a [`JanusVisionModel`]. It is used to instantiate a `JanusVisionModel` according to the specified arguments, defining the model 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 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. num_channels (`int`, *optional*, defaults to 3): The number of input channels. patch_size (`int`, *optional*, defaults to 16): The size (resolution) of each patch. image_size (`int`, *optional*, defaults to 384): The size (resolution) of each image. attention_dropout (`float`, *optional*, defaults to 0.0): Dropout probability for attention weights. layer_norm_eps (`float`, *optional*, defaults to 1e-06): The epsilon used by the layer normalization layers. hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, `"relu"`, `"selu"`, and `"gelu_new"` are supported. mlp_ratio (`float`, *optional*, defaults to 4.0): Ratio of MLP hidden dimensionality to embedding dimensionality. attention_bias (`bool`, *optional*, defaults to `True`): Whether to add a bias to the queries, keys, and values in the attention layers. hidden_dropout_rate (`float`, *optional*, defaults to 0.0): The dropout probability for fully connected layers in the encoder. projection_dim (`int`, *optional*, defaults to 2048): Dimensionality of the MLP projection head. projection_dropout (`float`, *optional*, defaults to 0.0): Dropout probability for the projection layer. use_qk_norm (`bool`, *optional*, defaults to `False`): Whether to normalize the query and key matrices. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated normal initializer for initializing all weight matrices. depth (`int`, *optional*, defaults to 2): Number of hidden layers in the aligner module. num_image_tokens (`int`, *optional*, defaults to 576): Number of image tokens. janus_vision_model vision_configc >[TU]"S0UD6 XlX lX0lX@lXPlX`lXplXl Xl Xl Xl Xl XlXlXlUUlUUlUUlgN)super__init__ hidden_sizenum_hidden_layersnum_attention_heads num_channels patch_size image_sizeattention_dropoutlayer_norm_eps hidden_act mlp_ratioattention_biashidden_dropout_rateprojection_dimprojection_dropout use_qk_norminitializer_rangedepthnum_image_tokens)selfrrrrrrrrrrrrr r!r"r#r$r%kwargs __class__s e/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/janus/configuration_janus.pyrJanusVisionConfig.__init__Rs, "6"&!2#6 ($$!2,$",#6 ,"4&!2 0)rrr$rrrrr#rrrrrr%rr r!r")irr-igư>gelug@Tr.r.F{Gz?ri@) __name__ __module__ __qualname____firstlineno____doc__ model_typebase_config_keyr__static_attributes__ __classcell__r(s@r)r r sW,\&J%O'*1*1r+r c^\rSrSrSrSrSrSSSSS S S S /S QS SSSS SS4S\S\S\S\S\S\S\S\S\ \S\S\ 4U4Sjjjr Sr U=r $)JanusVQVAEConfiga This is the configuration class to store the configuration of a [`JanusVQVAEModel`]. It is used to instantiate a `JanusVQVAEModel` according to the specified arguments, defining the model architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Instantiating a configuration with the defaults will yield a similar configuration to the VQModel of the [deepseek-community/Janus-Pro-1B](https://huggingface.co/deepseek-community/Janus-Pro-1B). Args: embed_dim (`int`, *optional*, defaults to 8): Dimensionality of each embedding vector. num_embeddings (`int`, *optional*, defaults to 16384): Number of codebook embeddings. double_latent (`bool`, *optional*, defaults to `False`): Whether to use double z channels. latent_channels (`int`, *optional*, defaults to 256): Number of channels for the latent space. num_patches (`int`, *optional*, defaults to 32): Num of patches the input images can be divided into. in_channels (`int`, *optional*, defaults to 3): Number of input channels. out_channels (`int`, *optional*, defaults to 3): Number of out channels. base_channels (`int`, *optional*, defaults to 128): Base channel count. channel_multiplier (`List[int]`, *optional*, defaults to `[1, 1, 2, 2, 4]`): Channel multipliers for each resolution. num_res_blocks (`int`, *optional*, defaults to 2): Number of residual blocks. dropout (`float`, *optional*, defaults to 0.0): Dropout rate. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. projection_dim (`int`, *optional*, defaults to 2048): Dimensionality of the MLP projection head. num_hidden_layers (`int`, *optional*, defaults to 2): Number of hidden layers in VAVAE MLP Connecter module. 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. image_token_embed_dim (`int`, *optional*, defaults to 2048): Dimension of image embeddings. It should be same as the dimensionality of text embeddings. janus_vqgan vq_configi@Fr r)rDrrrr.r1r0r/ embed_dimnum_embeddings double_latentlatent_channels num_patches in_channels out_channels base_channelschannel_multipliernum_res_blocksdropoutc >[TU]"S0UD6 XlX lX0lX@lX`lXlXlXl Xl Xl XPl Xpl XlXlXlUUlgr)rrrFrGrHrIrKrMrNrOrPr#rJrLr rrimage_token_embed_dim)r&rFrGrHrIrJrKrLrMrNrOrPr#r rrrRr'r(s r)rJanusVQVAEConfig.__init__st( "6"",*.&*"4, !2&(,!2$%:"r+)rMrNrHrPrFrrRrKr#rIrGrrJrOrLr )r2r3r4r5r6r7r8intboolrfloatrr9r:r;s@r)r=r=s*XJ!O##" (7"#$;$;$; $;  $;  $;$;$;$;!I$;$;$;$;r+r=cH^\rSrSrSrSr\\\S.r SU4Sjjr Sr U=r $) JanusConfiga This is the configuration class to store the configuration of a [`JanusModel`]. It is used to instantiate an Janus 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 Janus-1B or Janus-7B models. e.g. [deepseek-community/Janus-Pro-1B](https://huggingface.co/deepseek-community/Janus-Pro-1B) or [deepseek-community/Janus-Pro-7B](https://huggingface.co/deepseek-community/Janus-Pro-7B) 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 (`Union[AutoConfig, dict]`, *optional*, defaults to `LlamaConfig`): The config object or dictionary of the text backbone. vision_config (`Union[AutoConfig, dict]`, *optional*, defaults to `JanusVisionConfig`): The config object or dictionary of the vision backbone. vq_config (`Union[AutoConfig, dict]`, *optional*, defaults to `JanusVQVAEConfig`): The config object or dictionary of the VQVAE backbone. image_token_id (`int`, *optional*, defaults to 100581): Token index of a placeholder image token. Example: ```python >>> from transformers import JanusForConditionalGeneration, JanusConfig, JanusVisionConfig, JanusVQVAEConfig, LlamaConfig >>> # Initializing a Janus vision config >>> vision_config = JanusVisionConfig() >>> # Initializing a Llama config >>> text_config = LlamaConfig() >>> # Initializing a VQ config >>> vq_config = JanusVQVAEConfig() >>> # Initializing a Janus Pro 1B style configuration >>> configuration = JanusConfig(vision_config=vision_config, text_config=text_config, vq_config=vq_config) >>> # Initializing a model from the Janus Pro 1B style configuration >>> model = JanusForConditionalGeneration(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```janus) text_configrr@c >[U[5(a-URSS5US'[US"S 0UD6UlO_Uc)[ R S5 [S"5UlO3[U[5(aXlO[S[U535eUc%[ R S5 [5Ul OY[U[5(a[S 0UD6Ul O3[U[5(aX l O[S[U535eUc%[ R S5 [5Ul OY[U[5(a[S 0UD6Ul O3[U[5(aX0l O[S[U535eURRURR-URlX@l[$TU]L"S 0UD6 g) Nr7llamaz7`text_config` is None. Initializing with default valueszTInvalid type for `text_config`. Must be either `dict` or `LlamaConfig`. Type found: zK`vision_config` is None. Initializing with default JanusVisionConfig valuesz\Invalid type for `vision_config`. Must be either `dict` or `JanusVisionConfig`. Type found: zF`vq_config` is None. Initializing with default JanusVQVAEConfig valueszWInvalid type for `vq_config`. Must be either `dict` or `JanusVQVAEConfig`. Type found: r) isinstancedictgetrr[loggerinfor ValueErrortyper rr=r@rrrJimage_token_idrr)r&r[rr@rer'r(s r)rJanusConfig.__init__ s k4 ( ((3 g(NK %-k,.GHW;WD   KKQ R-g68D   %5 6 6*  $[ 124   KKe f!2!4D   t , ,!2!C]!CD   '8 9 9!.  $] 346    KK` a-/DN  4 ( (-: :DN  #3 4 4&N $Y02  &*%7%7%B%BdFXFXFcFc%c", "6"r+)rer[rr@)NNNi) r2r3r4r5r6r7r r r= sub_configsrr9r:r;s@r)rXrXs8+ ZJ!*%K 5#5#r+rX)r=r rXN)typingrconfiguration_utilsrutilsrautorr get_loggerr2rar r=rX__all__rr+r)rns],3-   H %\1(\1~T;'T;nj#"j#Z Cr+