i7dZddlmZddlmZddlmZejeZ GddeZ GddeZ Gd d eZ gd Z y ) zDia model configuration)PreTrainedConfig)RopeParameters)loggingcxeZdZdZdZ ddededededed ed ed ed ed ededzdeffd Z xZ S)DiaEncoderConfiga This is the configuration class to store the configuration of a [`DiaEncoder`]. It is used to instantiate a Dia encoder according to the specified arguments, defining the encoder architecture. Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PreTrainedConfig`] for more information. Args: max_position_embeddings (`int`, *optional*, defaults to 1024): The maximum sequence length that this model might ever be used with. num_hidden_layers (`int`, *optional*, defaults to 12): Number of hidden layers in the Transformer encoder. hidden_size (`int`, *optional*, defaults to 1024): Dimensionality of the encoder layers and the pooler layer. num_attention_heads (`int`, *optional*, defaults to 16): Number of attention heads for each attention layer in the Transformer encoder. num_key_value_heads (`int`, *optional*, defaults to 16): Number of key and value heads for each attention layer in the Transformer encoder. head_dim (`int`, *optional*, defaults to 128): Dimensionality of the attention head. intermediate_size (`int`, *optional*, defaults to 4096): Dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer encoder. norm_eps (`float`, *optional*, defaults to 1e-05): The epsilon used by the normalization layers. vocab_size (`int`, *optional*, defaults to 256): Vocabulary size of the Dia model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`DiaModel`]. hidden_act (`str` or `function`, *optional*, defaults to `"silu"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, `"relu"`, `"swish"` and `"gelu_new"` are supported. rope_parameters (`RopeParameters`, *optional*): Dictionary containing the configuration parameters for the RoPE embeddings. The dictionary should contain a value for `rope_theta` and optionally parameters used for scaling in case you want to use RoPE with longer `max_position_embeddings`. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. dia_encoderNmax_position_embeddingsnum_hidden_layers hidden_sizenum_attention_headsnum_key_value_headshead_dimintermediate_sizenorm_eps vocab_size hidden_actrope_parametersinitializer_rangec  ||_||_||_||_||_||_||_| |_||_| |_ | |_ | |_ t|4di| y)N)r r r rr rrrr rrrsuper__init__)selfr r r r r rrrrrrrkwargs __class__s s/home/obispo/Crisostomo_bridge/mision_env/lib/python3.12/site-packages/transformers/models/dia/configuration_dia.pyrzDiaEncoderConfig.__init__Asq (?$!2&!2#6     $#6 $!2. "6")  rr ih㈵>siluN{Gz?) __name__ __module__ __qualname____doc__ model_typeintfloatstrrr __classcell__rs@rrrs$LJ(,!##%#%!% 15#'#!$## # ! # ! ######($.#!##rrc'eZdZdZdZ ddededededed ed ed ed ed edededededededzdede de f&fd Z xZ S)DiaDecoderConfiga This is the configuration class to store the configuration of a [`DiaDecoder`]. It is used to instantiate a Dia decoder according to the specified arguments, defining the decoder architecture. Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PreTrainedConfig`] for more information. Args: max_position_embeddings (`int`, *optional*, defaults to 3072): The maximum sequence length that this model might ever be used with. num_hidden_layers (`int`, *optional*, defaults to 18): Number of hidden layers in the Transformer decoder. hidden_size (`int`, *optional*, defaults to 2048): Dimensionality of the decoder layers and the pooler layer. intermediate_size (`int`, *optional*, defaults to 8192): Dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer decoder. num_attention_heads (`int`, *optional*, defaults to 16): Number of attention heads for each attention layer in the Transformer decoder. num_key_value_heads (`int`, *optional*, defaults to 4): Number of key and value heads for each attention layer in the Transformer decoder. head_dim (`int`, *optional*, defaults to 128): Dimensionality of the attention head. cross_num_attention_heads (`int`, *optional*, defaults to 16): Number of attention heads for each cross-attention layer in the Transformer decoder. cross_head_dim (`int`, *optional*, defaults to 128): Dimensionality of the cross-attention head. cross_num_key_value_heads (`int`, *optional*, defaults to 16): Number of key and value heads for each cross-attention layer in the Transformer decoder. cross_hidden_size (`int`, *optional*, defaults to 1024): Dimensionality of the cross-attention layers. norm_eps (`float`, *optional*, defaults to 1e-05): The epsilon used by the normalization layers. vocab_size (`int`, *optional*, defaults to 1028): Vocabulary size of the Dia model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`DiaModel`]. hidden_act (`str` or `function`, *optional*, defaults to `"silu"`): The non-linear activation function (function or string) in the decoder. If string, `"gelu"`, `"relu"`, `"swish"` and `"gelu_new"` are supported. num_channels (`int`, *optional*, defaults to 9): Number of channels for the Dia decoder. rope_parameters (`RopeParameters`, *optional*): Dictionary containing the configuration parameters for the RoPE embeddings. The dictionary should contain a value for `rope_theta` and optionally parameters used for scaling in case you want to use RoPE with longer `max_position_embeddings`. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). is_encoder_decoder (`bool`, *optional*, defaults to `True`): Indicating that this model is part of an encoder-decoder architecture. dia_decoderNr r r rr r rcross_num_attention_headscross_head_dimcross_num_key_value_headscross_hidden_sizerrr num_channelsrr use_cacheis_encoder_decoderc $||_||_||_||_||_||_||_| |_||_| |_ | |_ | |_ | |_ ||_ ||_||_||_||_t%|Ldd|i|y)Nr9r)r r r rr r rr5r3r4r6rrrr7rr8rrr)rr r r rr r rr3r4r5r6rrrr7rrr8r9rrs rrzDiaDecoderConfig.__init__s.(?$!2&!2#6 #6   )B&)B&,!2  $$(!2". I,>I&Ir)i ii r r!r r!r rr"ir$ Nr%TT) r&r'r(r)r*r+r,r-rboolrr.r/s@rr1r1as+2hJ(,!#!%#%#$)+!)+!% 15#'#')*J!$*J*J *J  *J ! *J!*J*J$'*J*J$'*J*J*J*J*J !*J"($.#*J$!%*J&'*J(!)*J*Jrr1ceZdZdZdZdgZeedZ ddedzdedzde d e d e d e d e d e e dzde de ffd Z dZxZS) DiaConfigaw This is the configuration class to store the configuration of a [`DiaModel`]. It is used to instantiate a Dia 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 [nari-labs/Dia-1.6B](https://huggingface.co/nari-labs/Dia-1.6B) architecture. Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PreTrainedConfig`] for more information. Args: encoder_config (`DiaEncoderConfig`, *optional*): Configuration for the encoder part of the model. If not provided, a default `DiaEncoderConfig` will be used. decoder_config (`DiaDecoderConfig`, *optional*): Configuration for the decoder part of the model. If not provided, a default `DiaDecoderConfig` will be used. norm_eps (`float`, *optional*, defaults to 1e-05): The epsilon used by the normalization layers. is_encoder_decoder (`bool`, *optional*, defaults to `True`): Indicating that this model uses an encoder-decoder architecture. pad_token_id (`int`, *optional*, defaults to 1025): Padding token id. eos_token_id (`int`, *optional*, defaults to 1024): End of stream token id. bos_token_id (`int`, *optional*, defaults to 1026): Beginning of stream token id. delay_pattern (`list[int]`, *optional*, defaults to `[0, 8, 9, 10, 11, 12, 13, 14, 15]`): The delay pattern for the decoder. The length of this list must match `decoder_config.num_channels`. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). Example: ```python >>> from transformers import DiaConfig, DiaModel >>> # Initializing a DiaConfig with default values >>> configuration = DiaConfig() >>> # Initializing a DiaModel (with random weights) from the configuration >>> model = DiaModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` diapast_key_values)encoder_configdecoder_configNrCrDrr9 pad_token_id eos_token_id bos_token_id delay_patternrr8c  t|tr tdi|}t|tr tdi|}||n t|_||n t|_||_||ngd|_| |_| |_ ||j _ ||j _ ||j _ |j jt|jk(sJdt |@dd|i| y)N) r= r z3Number of channels must match delay pattern length.r9r) isinstancedictrr1rCrDrrHrr8rErFrGr7lenrr) rrCrDrr9rErFrGrHrr8rrs rrzDiaConfig.__init__s nd +-??N nd +-??N0>0JnP`Pb0>0JnP`Pb  .;.G]Mn!2"+7(+7(+7(""//3t7I7I3JJ A J I,>I&Irc|jS)z^Defaulting to audio config as it's the decoder in this case which is usually the text backbone)rD)rargsrs rget_text_configzDiaConfig.get_text_configs"""r) NNr"TiriNr%T)r&r'r(r)r*keys_to_ignore_at_inferencerr1 sub_configsr,r>r+listrrVr.r/s@rr@r@s-^J#4"5%5IYZK3726#'   *.#' J(4/ J)4/ J J ! J  J J JCy4' J! J JD#rr@)r@rr1N)r)configuration_utilsrmodeling_rope_utilsrutilsr get_loggerr&loggerrr1r@__all__rrrr`sa31   H %F#'F#RaJ'aJHX# X#v @r