eTh$JSrSSKJr SSKJr \R "\5r"SS\5r"SS\5r "SS \5r /S Qr g ) zAltCLIP model configuration)PretrainedConfig)loggingcZ^\rSrSrSrSrSU4SjjrSrU=r$)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_modelc >[TU]"SXUS.UD6 XlX lX0lX@lX`lXPlXplXl Xl Xl Xl Xl XlUUlUUlUUlg)N) pad_token_id bos_token_id eos_token_id)super__init__ vocab_size hidden_sizenum_hidden_layersnum_attention_heads hidden_actintermediate_sizehidden_dropout_probattention_probs_dropout_probmax_position_embeddingstype_vocab_sizeinitializer_rangeinitializer_factorlayer_norm_epsposition_embedding_type use_cache project_dim)selfrrrrrrrrrrrrrr r r rrrkwargs __class__s i/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/altclip/configuration_altclip.pyrAltCLIPTextConfig.__init__cs. sl\hslrs$&!2#6 $!2#6 ,H)'>$.!2"4,'>$"&)rrrrrrrrrrrrrrrr)iirigelu皙?r(i{Gz?r*h㈵>r)absoluteT) __name__ __module__ __qualname____firstlineno____doc__ model_typer__static_attributes__ __classcell__r"s@r#rrsVF P&J%( # *)('('r%rcR^\rSrSrSrSrSrSU4SjjrSrU=r $)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_model vision_configc >[TU]"S0UD6 XlX lX0lX@lXPlX`lXlXpl Xl Xl Xl Xl Xlg)Nr )rrrrprojection_dimrr num_channels patch_size image_sizerrattention_dropoutrr)r rrr?rrr@rBrArrrCrrr!r"s r#rAltCLIPVisionConfig.__init__s`" "6"&!2,!2#6 ($$!2"4!2,$r%) rCrrrBrrrrrr@rrAr?) r/i i rEr quick_gelur+gr*?) r0r1r2r3r4r5base_config_keyrr6r7r8s@r#r:r:sH5 n(J%O%%r%r:c\^\rSrSrSrSr\\S.rS U4Sjjr \ S\S\4Sj5r S r U=r $) AltCLIPConfigak 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) ```altclip text_configr=c >URSS5nURSS5n[T U]"S0UD6 UbUc0n[S0UD6R 5nUR 5HHupX;dM XU :wdMU S;dMX;a SU SU S3n OSU S3n [ RU 5 MJ URU5 UbUc0n[S0UD6R 5n S U ;a5U S R 5V V s0sHup[U 5U _M sn n U S 'U R 5HHupX;dM XU :wdMU S;dMX;a SU S U S3n OS U S3n [ RU 5 MJ URU 5 Uc0n[ RS 5 Uc0n[ RS 5 [S0UD6Ul [S0UD6Ul X0l X@lSUlgs sn n f)Ntext_config_dictvision_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.id2labelzv` 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.rIr )poprrrto_dictitemsloggerinfoupdater:strrPr=r?logit_scale_init_valuer)r rPr=r?r^r!rRrS_text_config_dictkeyvaluemessage_vision_config_dictr"s r#rAltCLIPConfig.__init__sS "::&8$?#ZZ(ros\"3   H %s'(s'lZ%*Z%zRg$Rgj Hr%