o ۾i8@s@ddlmZGdddeZGdddeZGdddeZdS) )PretrainedConfigcsVeZdZdZdZ                 dfdd ZZS)HunYuanVLVisionConfig hunyuan_vl vision_configgelubilinearh㈵>rNT@ c stjdi|||_||_||_||_||_||_|s!||_n||_| |_ | |_ | |_ | |_ | |_ ||_||_||_||_||_||_||_||_||_||_||_||_dS)N)super__init__ hidden_act hidden_sizeintermediate_sizeinterpolate_modelearnable_mlp_pooling_sizenum_attention_headsnum_key_value_heads num_channelsnum_hidden_layersout_hidden_size patch_sizeremove_prenormspatial_merge_sizetemporal_patch_size rms_norm_epsresize_resolutionimg_max_token_nummax_image_sizemin_image_sizevideo_max_image_sizevideo_min_image_sizeanyres_vit_max_image_sizemax_vit_seq_lentext_hidden_size)selfrrrrr(rrr r!r"r#r$r%r&r'r)r*r+r-r.r,r/r0r1kwargs __class__r^/home/ubuntu/.local/lib/python3.10/site-packages/vllm/transformers_utils/configs/hunyuan_vl.pyr s6 zHunYuanVLVisionConfig.__init__)rrrr r rr Nr r rr Trrrrrrrrrrr)__name__ __module__ __qualname__ model_typebase_config_keyr __classcell__rrr4r6r s8rcsfeZdZdZdZdgZ                 ddeffdd ZddZZ S)HunYuanVLTextConfiga* This is the configuration class to store the configuration of a [`HunYuanVLTextConfig`]. It is used to instantiate an HunYuan 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 HunYuan-7B. Hunyuan-7B-Instruct [tencent/Hunyuan-7B-Instruct](https://huggingface.co/tencent/Hunyuan-7B-Instruct). 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 290943): Vocabulary size of the HunYuan model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`HunYuanVLTextConfig`] hidden_size (`int`, *optional*, defaults to 4096): Dimension of the hidden representations. intermediate_size (`int`, *optional*, defaults to 11008): Dimension of the MLP representations or shared MLP representations. num_hidden_layers (`int`, *optional*, defaults to 32): Number of hidden layers in the Transformer decoder. num_attention_heads (`int`, *optional*, defaults to 32): Number of attention heads for each attention layer in the Transformer decoder. num_key_value_heads (`int`, *optional*): This is the number of key_value heads that should be used to implement Grouped Query Attention. If `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if `num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed by meanpooling all the original heads within that group. For more details checkout [this paper](https://huggingface.co/papers/2305.13245). If it is not specified, will default to `num_attention_heads`. hidden_act (`str` or `function`, *optional*, defaults to `"silu"`): The non-linear activation function (function or string) in the decoder. max_position_embeddings (`int`, *optional*, defaults to 2048): The maximum sequence length that this model might ever be used with. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. rms_norm_eps (`float`, *optional*, defaults to 1e-05): The epsilon used by the rms normalization layers. use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). Only relevant if `config.is_decoder=True`. pad_token_id (`int`, *optional*, defaults to 0): Padding token id. bos_token_id (`int`, *optional*, defaults to 1): Beginning of stream token id. eos_token_id (`int`, *optional*, defaults to 2): End of stream token id. eod_token_id (int, *optional*, defaults to 3): Token ID representing the end-of-document marker. Used to indicate the termination of a text sequence. Example: In multi-document processing, this token helps the model distinguish between separate documents. pretraining_tp (`int`, *optional*, defaults to 1): Experimental feature. Tensor parallelism rank used during pretraining. Please refer to [this document](https://huggingface.co/docs/transformers/parallelism) to understand more about it. This value is necessary to ensure exact reproducibility of the pretraining results. Please refer to [this issue](https://github.com/pytorch/pytorch/issues/76232). tie_word_embeddings (`bool`, *optional*, defaults to `False`): Whether to tie weight embeddings rope_theta (`float`, *optional*, defaults to 10000.0): The base period of the RoPE embeddings. rope_scaling (`Dict`, *optional*): Dictionary containing the scaling configuration for the RoPE embeddings. Currently supports two scaling strategies: linear and dynamic. Their scaling factor must be a float greater than 1. The expected format is `{"type": strategy name, "factor": scaling factor}`. When using this flag, don't update `max_position_embeddings` to the expected new maximum. See the following thread for more information on how these scaling strategies behave: https://www.reddit.com/r/LocalLLaMA/comments/14mrgpr/dynamically_scaled_rope_further_increases/. This is an experimental feature, subject to breaking API changes in future versions. attention_bias (`bool`, defaults to `False`, *optional*, defaults to `False`): Whether to use a bias in the query, key, value and output projection layers during self-attention. attention_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. head_dim (`int`, *optional*, defaults to 128): The attention head dimension. hunyuan_vl_textpast_key_valuespr+ Nsilur{Gz?r Trrrr F@rc s||_||_||_||_||_||_||_|dur|}||_||_| |_ | |_ ||_ | |_ ||_ ||_||_||_tjd| | ||d|dS)N) pad_token_id bos_token_id eos_token_idtie_word_embeddingsr) vocab_sizemax_position_embeddingsrrr"rhead_dimr rinitializer_ranger(pretraining_tp use_cache rope_theta rope_scalingattention_biasattention_dropoutrr)r2rKrrr"rr rrLrNr(rPrGrHrI eod_token_idrOrJrQrRrSrTrMr3r4rr6rs6 zHunYuanVLTextConfig.__init__cCs|jdurdSt|jtrt|jdkrtd|j|jdd}|jdd}|jdd}|dus9|dvr@td||durL|durLtd |dur`t|trY|d kr`td ||durtt|trm|d krvtd |dSdS) z< Validate the `rope_scaling` configuration. 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