fTh`SrSSKJr SSKJr \R "\5r"SS\5rS/r g)zCANINE model configuration)PretrainedConfig)loggingcZ^\rSrSrSrSrSU4SjjrSrU=r$) CanineConfiga This is the configuration class to store the configuration of a [`CanineModel`]. It is used to instantiate an CANINE 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 CANINE [google/canine-s](https://huggingface.co/google/canine-s) 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): Dimension of the encoder layers and the pooler layer. num_hidden_layers (`int`, *optional*, defaults to 12): Number of hidden layers in the deep Transformer encoder. num_attention_heads (`int`, *optional*, defaults to 12): Number of attention heads for each attention layer in the Transformer encoders. intermediate_size (`int`, *optional*, defaults to 3072): Dimension of the "intermediate" (i.e., feed-forward) layer in the Transformer encoders. 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. hidden_dropout_prob (`float`, *optional*, defaults to 0.1): The dropout probability for all fully connected layers in the embeddings, encoders, 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 16384): The maximum sequence length that this model might ever be used with. type_vocab_size (`int`, *optional*, defaults to 16): The vocabulary size of the `token_type_ids` passed when calling [`CanineModel`]. 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): Padding token id. bos_token_id (`int`, *optional*, defaults to 57344): Beginning of stream token id. eos_token_id (`int`, *optional*, defaults to 57345): End of stream token id. downsampling_rate (`int`, *optional*, defaults to 4): The rate at which to downsample the original character sequence length before applying the deep Transformer encoder. upsampling_kernel_size (`int`, *optional*, defaults to 4): The kernel size (i.e. the number of characters in each window) of the convolutional projection layer when projecting back from `hidden_size`*2 to `hidden_size`. num_hash_functions (`int`, *optional*, defaults to 8): The number of hash functions to use. Each hash function has its own embedding matrix. num_hash_buckets (`int`, *optional*, defaults to 16384): The number of hash buckets to use. local_transformer_stride (`int`, *optional*, defaults to 128): The stride of the local attention of the first shallow Transformer encoder. Defaults to 128 for good TPU/XLA memory alignment. Example: ```python >>> from transformers import CanineConfig, CanineModel >>> # Initializing a CANINE google/canine-s style configuration >>> configuration = CanineConfig() >>> # Initializing a model (with random weights) from the google/canine-s style configuration >>> model = CanineModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```caninec >[TU]"SXUS.UD6 XlXlX lX0lX@lXPlX`lXpl Xl Xl Xl Xl UUlUUlUUlUUlg)N) pad_token_id bos_token_id eos_token_id)super__init__max_position_embeddings hidden_sizenum_hidden_layersnum_attention_headsintermediate_size hidden_acthidden_dropout_probattention_probs_dropout_probinitializer_rangetype_vocab_sizelayer_norm_epsdownsampling_rateupsampling_kernel_sizenum_hash_functionsnum_hash_bucketslocal_transformer_stride)selfrrrrrrrrrrrr r r rrrrrkwargs __class__s g/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/canine/configuration_canine.pyrCanineConfig.__init__`s. sl\hslrs'>$&!2#6 !2$#6 ,H)!2.,"3&<#"4 0(@%)rrrrrrrrrrrrrrrr)i r&i gelu皙?r(@g{Gz?g-q=iir,r)) __name__ __module__ __qualname____firstlineno____doc__ model_typer__static_attributes__ __classcell__)r"s@r#rrsXC JJ%( % !$)*A*Ar%rN) r3configuration_utilsrutilsr get_loggerr/loggerr__all__r r%r#r<s>!3   H %rA#rAj  r%