U Ö9%eã@sDdZddlmZddlmZe e¡ZdddœZGdd„deƒZ d S) z Bros model configurationé)ÚPretrainedConfig)ÚloggingzHhttps://huggingface.co/jinho8345/bros-base-uncased/blob/main/config.jsonzIhttps://huggingface.co/jinho8345/bros-large-uncased/blob/main/config.json)zjinho8345/bros-base-uncasedzjinho8345/bros-large-uncasedcs&eZdZdZdZd‡fdd„ Z‡ZS)Ú BrosConfiga This is the configuration class to store the configuration of a [`BrosModel`] or a [`TFBrosModel`]. It is used to instantiate a Bros 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 Bros [jinho8345/bros-base-uncased](https://huggingface.co/jinho8345/bros-base-uncased) 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 30522): Vocabulary size of the Bros model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`BrosModel`] or [`TFBrosModel`]. hidden_size (`int`, *optional*, defaults to 768): Dimensionality of the encoder layers and the pooler layer. 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. intermediate_size (`int`, *optional*, defaults to 3072): 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 512): 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 2): The vocabulary size of the `token_type_ids` passed when calling [`BrosModel`] or [`TFBrosModel`]. 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-12): The epsilon used by the layer normalization layers. pad_token_id (`int`, *optional*, defaults to 0): The index of the padding token in the token vocabulary. dim_bbox (`int`, *optional*, defaults to 8): The dimension of the bounding box coordinates. (x0, y1, x1, y0, x1, y1, x0, y1) bbox_scale (`float`, *optional*, defaults to 100.0): The scale factor of the bounding box coordinates. n_relations (`int`, *optional*, defaults to 1): The number of relations for SpadeEE(entity extraction), SpadeEL(entity linking) head. classifier_dropout_prob (`float`, *optional*, defaults to 0.1): The dropout ratio for the classifier head. Examples: ```python >>> from transformers import BrosConfig, BrosModel >>> # Initializing a BROS jinho8345/bros-base-uncased style configuration >>> configuration = BrosConfig() >>> # Initializing a model from the jinho8345/bros-base-uncased style configuration >>> model = BrosModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```Zbrosé:wéé é Úgeluçš™™™™™¹?ééç{®Gáz”?çê-™—q=ééçY@éc srtƒjf||||||||| | | | | dœ |—Ž||_||_||_|jd|_|j|j|_|j|j|_ ||_ dS)N) Ú vocab_sizeÚ hidden_sizeÚnum_hidden_layersÚnum_attention_headsÚintermediate_sizeÚ hidden_actÚhidden_dropout_probÚattention_probs_dropout_probÚmax_position_embeddingsÚtype_vocab_sizeÚinitializer_rangeÚlayer_norm_epsÚ pad_token_idé) ÚsuperÚ__init__Údim_bboxÚ bbox_scaleÚ n_relationsrZdim_bbox_sinusoid_emb_2dZdim_bbox_sinusoid_emb_1drZdim_bbox_projectionÚclassifier_dropout_prob)Úselfrrrrrrrrrrrrrr#r$r%r&Úkwargs©Ú __class__©új/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/transformers/models/bros/configuration_bros.pyr"_s0óò zBrosConfig.__init__)rrrrrr r r r r r rrrrrr )Ú__name__Ú __module__Ú __qualname__Ú__doc__Z model_typer"Ú __classcell__r+r+r)r,rs(?îrN) r0Zconfiguration_utilsrÚutilsrZ get_loggerr-ÚloggerZ"BROS_PRETRAINED_CONFIG_ARCHIVE_MAPrr+r+r+r,Ús   þ