o eiE@sbdZddlmZddlmZeeZGdddeZGdddeZ Gdd d eZ gd Z d S) zAltCLIP model configuration)PreTrainedConfig)loggingcsHeZdZdZdZ         dfdd ZZS)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. 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_modelgelu皙?{Gz?h㈵>c s|tjdi|||_||_||_||_||_||_||_||_ ||_ ||_ ||_ | |_ | |_| |_| |_| |_||_dSN)super__init__ pad_token_id bos_token_id eos_token_id vocab_size hidden_sizenum_hidden_layersnum_attention_heads hidden_actintermediate_sizehidden_dropout_probattention_probs_dropout_probmax_position_embeddingstype_vocab_sizeinitializer_rangeinitializer_factorlayer_norm_eps project_dim)selfrrrrr rr!r"r#r$r%r&r'rrrr(kwargs __class__ro/home/ubuntu/transcripts/venv/lib/python3.10/site-packages/transformers/models/altclip/configuration_altclip.pyrYs$ zAltCLIPTextConfig.__init__)rrrr r r r r r rrrrrrrr)__name__ __module__ __qualname____doc__ model_typer __classcell__rrr+r-rs*?rcsDeZdZdZdZdZ        dfdd ZZS)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_configr  r quick_gelurr?c sdtjdi|||_||_||_||_||_||_||_||_ | |_ | |_ | |_ | |_ | |_dSr)rrrr projection_dimrr num_channels patch_size image_sizer%r&attention_dropoutr'r)r)rr r?rrr@rBrArr'rCr%r&r*r+rr-rs zAltCLIPVisionConfig.__init__) rr7r8r9r9rr:r;r<rr=rr>)r.r/r0r1r2base_config_keyrr3rrr+r-r4s$7r4cs2eZdZdZdZeedZ d fdd ZZ 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(text_config=config_text, vision_config=config_vision) ```altclip) text_configr6Nr/L F@c  s|dd}|dd}|durT|duri}tdi|}|D]+\} } | |vrN| || krN| dkrN| |vrCd| d| d} nd| d} t| q#|||dur|dur^i}tdi|} d | vrxd d | d D| d <| D]+\} } | |vr| || kr| dkr| |vrd| d | d} nd | d} t| q||| |durt}tdn t|t rtdi|}|durt}tdn t|t rtdi|}||_ ||_ ||_ ||_ d|_tjdi|dS)Ntext_config_dictvision_config_dicttransformers_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.id2labelcSsi|] \}}t||qSr)str).0keyvaluerrr- ?sz*AltCLIPConfig.__init__..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.r>r)poprto_dictitemsloggerinfoupdater4 isinstancedictrGr6r?logit_scale_init_valuer&rr) r)rGr6r?r[r*rIrJ_text_config_dictrPrQmessage_vision_config_dictr+rr-rst            zAltCLIPConfig.__init__)NNrrH) r.r/r0r1r2rr4 sub_configsrr3rrr+r-rEs , rE)rr4rEN) r1configuration_utilsrutilsr get_loggerr.rVrr4rE__all__rrrr-s   l]