
    qi                     `    d Z ddlmZ ddlmZ  ej
                  e      Z G d de      ZdgZ	y)zLongT5 model configuration   )PreTrainedConfig)loggingc                   j     e Zd ZdZdZdgZdddddZ	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 d
 fd		Z xZS )LongT5Configa  
    This is the configuration class to store the configuration of a [`LongT5Model`]. It is
    used to instantiate a LongT5 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 LongT5
    [google/long-t5-local-base](https://huggingface.co/google/long-t5-local-base) architecture.

    Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the
    documentation from [`PreTrainedConfig`] for more information.

    Arguments:
        vocab_size (`int`, *optional*, defaults to 32128):
            Vocabulary size of the LongT5 model. Defines the number of different tokens that can be represented by the
            `inputs_ids` passed when calling [`LongT5Model`].
        d_model (`int`, *optional*, defaults to 512):
            Size of the encoder layers and the pooler layer.
        d_kv (`int`, *optional*, defaults to 64):
            Size of the key, query, value projections per attention head. `d_kv` has to be equal to `d_model //
            num_heads`.
        d_ff (`int`, *optional*, defaults to 2048):
            Size of the intermediate feed forward layer in each `LongT5Block`.
        num_layers (`int`, *optional*, defaults to 6):
            Number of hidden layers in the Transformer encoder.
        num_decoder_layers (`int`, *optional*):
            Number of hidden layers in the Transformer decoder. Will use the same value as `num_layers` if not set.
        num_heads (`int`, *optional*, defaults to 8):
            Number of attention heads for each attention layer in the Transformer encoder.
        local_radius (`int`, *optional*, defaults to 127)
            Number of tokens to the left/right for each token to locally self-attend in a local attention mechanism.
        global_block_size (`int`, *optional*, defaults to 16)
            Length of blocks an input sequence is divided into for a global token representation. Used only for
            `encoder_attention_type = "transient-global"`.
        relative_attention_num_buckets (`int`, *optional*, defaults to 32):
            The number of buckets to use for each attention layer.
        relative_attention_max_distance (`int`, *optional*, defaults to 128):
            The maximum distance of the longer sequences for the bucket separation.
        dropout_rate (`float`, *optional*, defaults to 0.1):
            The ratio for all dropout layers.
        layer_norm_eps (`float`, *optional*, defaults to 1e-6):
            The epsilon used by the layer normalization layers.
        initializer_factor (`float`, *optional*, defaults to 1):
            A factor for initializing all weight matrices (should be kept to 1, used internally for initialization
            testing).
        feed_forward_proj (`string`, *optional*, defaults to `"relu"`):
            Type of feed forward layer to be used. Should be one of `"relu"` or `"gated-gelu"`. LongT5v1.1 uses the
            `"gated-gelu"` feed forward projection. Original LongT5 implementation uses `"gated-gelu"`.
        encoder_attention_type (`string`, *optional*, defaults to `"local"`):
            Type of encoder attention to be used. Should be one of `"local"` or `"transient-global"`, which are
            supported by LongT5 implementation.
        use_cache (`bool`, *optional*, defaults to `True`):
            Whether or not the model should return the last key/values attentions (not used by all models).
    longt5past_key_valuesd_model	num_heads
num_layersd_kv)hidden_sizenum_attention_headsnum_hidden_layershead_dimc                 Z   || _         || _        || _        || _        || _        || _        ||n| j
                  | _        || _        || _        |	| _	        |
| _
        || _        || _        || _        || _        || _        || _        || _        || _        || _        || _        || _        | j                  j-                  d      }|d   | _        |d   dk(  | _        t3        |      dkD  r|d   dk7  st3        |      dkD  rt5        d| d      |d	k(  rd
| _        t7        | p  dd|i| y )N-    gated      z`feed_forward_proj`: z is not a valid activation function of the dense layer. Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. 'gated-gelu' or 'relu'z
gated-gelugelu_newis_encoder_decoder )
is_decoder
vocab_sizer	   r   d_ffr   num_decoder_layersr
   local_radiusglobal_block_sizerelative_attention_num_bucketsrelative_attention_max_distancedropout_ratelayer_norm_epsiloninitializer_factorfeed_forward_projencoder_attention_type	use_cachepad_token_idbos_token_ideos_token_idtie_word_embeddingssplitdense_act_fnis_gated_actlen
ValueErrorsuper__init__)selfr   r	   r   r   r   r   r
   r   r    r!   r"   r#   r$   r%   r&   r   r'   r(   r)   r+   r   r*   r,   kwargsact_info	__class__s                             a/opt/pipecat/venv/lib/python3.12/site-packages/transformers/models/longt5/configuration_longt5.pyr3   zLongT5Config.__init__U   sY   6 %$		$8J8V"4\`\k\k"(!2.L+/N,("4"4!2&<#"(((#6 ))//4$RL$QK72x=1!!73x=1;L'(9': ;) )  , *DI,>I&I    )i}  i   @   i      N                g?gư>g      ?reluTlocalTr   r   FNT)	__name__
__module____qualname____doc__
model_typekeys_to_ignore_at_inferenceattribute_mapr3   __classcell__)r7   s   @r8   r   r      s    2h J#4"5 *)	M ')(+ & 1BJ BJr9   r   N)
rF   configuration_utilsr   utilsr   
get_loggerrC   loggerr   __all__r   r9   r8   <module>rP      s@    ! 3  
		H	%@J# @JF 
r9   