o óÜÓhã@sBdZddlmZddlmZe e¡ZddiZGdd„deƒZ dS) z PEGASUS model configurationé)ÚPretrainedConfig)Úloggingzgoogle/pegasus-largezDhttps://huggingface.co/google/pegasus-large/resolve/main/config.jsoncsˆeZdZdZdZdgZdddœZ           d‡fdd„ Zede fdd„ƒZ ede fdd„ƒZ ‡Z S)Ú PegasusConfiga This is the configuration class to store the configuration of a [`PegasusModel`]. It is used to instantiate an PEGASUS 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 PEGASUS [google/pegasus-large](https://huggingface.co/google/pegasus-large) 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 50265): Vocabulary size of the PEGASUS model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`PegasusModel`] or [`TFPegasusModel`]. d_model (`int`, *optional*, defaults to 1024): Dimensionality of the layers and the pooler layer. encoder_layers (`int`, *optional*, defaults to 12): Number of encoder layers. decoder_layers (`int`, *optional*, defaults to 12): Number of decoder layers. encoder_attention_heads (`int`, *optional*, defaults to 16): Number of attention heads for each attention layer in the Transformer encoder. decoder_attention_heads (`int`, *optional*, defaults to 16): Number of attention heads for each attention layer in the Transformer decoder. decoder_ffn_dim (`int`, *optional*, defaults to 4096): Dimensionality of the "intermediate" (often named feed-forward) layer in decoder. encoder_ffn_dim (`int`, *optional*, defaults to 4096): Dimensionality of the "intermediate" (often named feed-forward) layer in decoder. activation_function (`str` or `function`, *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. dropout (`float`, *optional*, defaults to 0.1): The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. attention_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. activation_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for activations inside the fully connected layer. max_position_embeddings (`int`, *optional*, defaults to 1024): 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). init_std (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. encoder_layerdrop (`float`, *optional*, defaults to 0.0): The LayerDrop probability for the encoder. See the [LayerDrop paper](see https://arxiv.org/abs/1909.11556) for more details. decoder_layerdrop (`float`, *optional*, defaults to 0.0): The LayerDrop probability for the decoder. See the [LayerDrop paper](see https://arxiv.org/abs/1909.11556) for more details. scale_embedding (`bool`, *optional*, defaults to `False`): Scale embeddings by diving by sqrt(d_model). use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models) forced_eos_token_id (`int`, *optional*, defaults to 1): The id of the token to force as the last generated token when `max_length` is reached. Usually set to `eos_token_id`. Example: ```python >>> from transformers import PegasusConfig, PegasusModel >>> # Initializing a PEGASUS google/pegasus-large style configuration >>> configuration = PegasusConfig() >>> # Initializing a model (with random weights) from the google/pegasus-large style configuration >>> model = PegasusModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```ÚpegasusÚpast_key_valuesÚencoder_attention_headsÚd_model)Únum_attention_headsÚ hidden_sizeéYÄéé ééçTÚgeluçš™™™™™¹?ç{®Gáz”?éFéc s”||_||_||_||_||_||_||_||_||_||_ ||_ ||_ | |_ ||_ | |_| |_| |_||_||_tƒjd||| ||dœ|¤ŽdS)N)Ú pad_token_idÚ eos_token_idÚis_encoder_decoderÚdecoder_start_token_idÚforced_eos_token_id©)Ú vocab_sizeÚmax_position_embeddingsrÚencoder_ffn_dimÚencoder_layersrÚdecoder_ffn_dimÚdecoder_layersÚdecoder_attention_headsÚdropoutÚattention_dropoutÚactivation_dropoutÚactivation_functionÚinit_stdÚencoder_layerdropÚdecoder_layerdropÚ use_cacheÚnum_hidden_layersÚscale_embeddingÚsuperÚ__init__)Úselfrrrrrr!r r"r(r)r*rr&rr#r$r%r'rr,rrrÚkwargs©Ú __class__rúg/var/www/html/ai/venv/lib/python3.10/site-packages/transformers/models/pegasus/configuration_pegasus.pyr.is8û úzPegasusConfig.__init__ÚreturncCó|jS©N)r©r/rrr3r  óz!PegasusConfig.num_attention_headscCr5r6)rr7rrr3r ¤r8zPegasusConfig.hidden_size)r r r rrr rrrrTTrr rrrrrFrrr) Ú__name__Ú __module__Ú __qualname__Ú__doc__Ú model_typeÚkeys_to_ignore_at_inferenceÚ attribute_mapr.ÚpropertyÚintr r Ú __classcell__rrr1r3rsBG è7rN) r<Úconfiguration_utilsrÚutilsrÚ get_loggerr9ÚloggerÚ%PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAPrrrrr3Ús   ÿ