o پi06@sRdZddlmZddlmZddlmZmZee Z dZ dZ GdddeZ d S) z$GraniteMoeHybrid model configuration)PretrainedConfig)logging)Mamba2CacheParamsMamba2StateShapemamba attentioncseZdZdZdZdgZ                             ! !   "d-fd#d$ Zed%d&Zed'd(Z ed)d*Z ed+d,Z Z S).GraniteMoeHybridConfiga/ This is the configuration class to store the configuration of a [`GraniteMoeHybridModel`]. It is used to instantiate a GraniteMoeHybrid model according to the specified arguments, defining the model architecture. The GraniteMoeHybrid is a hybrid architecture combining Mamba2 layers with attention layers, developed by IBM. 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 100352): Vocabulary size of the GraniteMoeHybrid model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`GraniteMoeHybridModel`] tie_word_embeddings (`bool`, *optional*, defaults to `True`): Whether the model's input and output word embeddings should be tied. Note that this is only relevant if the model has a output word embedding layer. hidden_size (`int`, *optional*, defaults to 2048): Dimension of the hidden representations. intermediate_size (`int`, *optional*, defaults to 8192): Dimension of the MLP representations. num_hidden_layers (`int`, *optional*, defaults to 40): Number of hidden layers in the model. layer_types (`list[str]`, *optional*): List of layer types for each layer. Each element should be either "mamba" or "attention". If not provided, defaults to alternating pattern based on num_hidden_layers. num_attention_heads (`int`, *optional*, defaults to 32): Number of attention heads for each attention layer. num_key_value_heads (`int`, *optional*, defaults to 8): 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. hidden_act (`str` or `function`, *optional*, defaults to `"silu"`): The non-linear activation function (function or string) in the decoder. initializer_range (`float`, *optional*, defaults to 0.1): 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. normalization_function (`str`, *optional*, defaults to `"rmsnorm"`): The normalization function to use. Currently only "rmsnorm" is supported. 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 100256): The id of the padding token. bos_token_id (`int`, *optional*, defaults to 100257): The id of the "beginning-of-sequence" token. eos_token_id (`int`, *optional*, defaults to 100257): The id of the "end-of-sequence" token. max_position_embeddings (`int`, *optional*, defaults to 131072): Max cached sequence length for the model attention_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. attention_bias (`bool`, *optional*, defaults to `False`): Whether to use bias in attention layers. position_embedding_type (`str`, *optional*, defaults to `"nope"`): Type of position embedding. Can be "nope" (no position embedding) or "rope". rope_theta (`float`, *optional*, defaults to 10000.0): The theta value used for the RoPE embeddings. rope_scaling (`dict`, *optional*): The scaling configuration for the RoPE embeddings. If `None`, no scaling is applied. mamba_d_state (`int`, *optional*, defaults to 128): The dimension of the mamba state space latents mamba_d_conv (`int`, *optional*, defaults to 4): The size of the mamba convolution kernel mamba_expand (`int`, *optional*, defaults to 2): Expanding factor (relative to hidden_size) used to determine the mamba intermediate size mamba_d_head (`int`, *optional*, defaults to 64): Head embedding dimension size for Mamba mamba_n_heads (`int`, *optional*, defaults to 64): The number of mamba heads mamba_n_groups (`int`, *optional*, defaults to 1): The number of the mamba groups mamba_chunk_size (`int`, *optional*, defaults to 256): The chunks in which to break the sequence when doing prefill/training mamba_conv_bias (`bool`, *optional*, defaults to `True`): Flag indicating whether or not to use bias in the convolution layer of the mamba mixer block. mamba_proj_bias (`bool`, *optional*, defaults to `False`): Flag indicating whether or not to use bias in the input and output projections of the mamba mixer block embedding_multiplier (`float`, *optional*, defaults to 12.0): The multiplier for the embedding layer. This is used to scale the output of the embedding layer. logits_scaling (`float`, *optional*, defaults to 8.0): The scaling factor for the logits. attention_multiplier (`float`, *optional*, defaults to 0.015625): The multiplier for the attention layers. residual_multiplier (`float`, *optional*, defaults to 0.22): The multiplier for residual connections. num_local_experts (`int`, *optional*, defaults to 0): Number of local experts in MoE layers. num_experts_per_tok (`int`, *optional*, defaults to 0): Number of experts to use per token in MoE layers. shared_intermediate_size (`int`, *optional*, defaults to 8192): Intermediate size for shared experts. output_router_logits (`bool`, *optional*, defaults to `False`): Whether to output router logits. router_aux_loss_coef (`float`, *optional*, defaults to 0.01): Auxiliary loss coefficient for the router. granitemoehybridpast_key_valuesT (N silu皙?h㈵>rmsnorm頇顇Fnope@@(@ @?)\(?r{Gz?c), s||_||_||_||_|dur0g|_t|D]}*|*dddkr(|jtq|jtqn||_t |j|jkrHt d|dt |j|jD]}+|+ttfvrat dtdtd|+d qK||_ ||_ | |_ | |_| |_| |_| |_||_||_||_||_||_||_||_||_||_||_||_||_||_||_||_ |||_!|j!|dkrt d |j!d |d |||j!krt d |d|d|j!d | |_"|!|_#|"|_$|#|_%|$|_&|%|_'|&|_(|'|_)|(|_*t+j,d||||d|)dS)Nrrz9layer_types must have length equal to num_hidden_layers (z ), but got z,Each element in layer_types must be either 'z' or 'z ', but got ''zmamba_intermediate_size (z&) must be divisible by mamba_n_heads ()zmamba_d_head (z) * mamba_n_heads (z&) must equal mamba_intermediate_size () pad_token_id bos_token_id eos_token_idtie_word_embeddings)- vocab_size hidden_sizeintermediate_sizenum_hidden_layers layer_typesrangeappend ATTENTIONMAMBAlen ValueErrornum_attention_headsnum_key_value_heads hidden_actinitializer_range rms_norm_epsnormalization_function use_cachemax_position_embeddingsattention_dropoutattention_biasposition_embedding_type rope_theta rope_scaling mamba_d_state mamba_d_conv mamba_expand mamba_d_head mamba_n_headsmamba_n_groupsmamba_chunk_sizemamba_conv_biasmamba_proj_biasmamba_intermediate_sizeembedding_multiplierlogits_scalingattention_multiplierresidual_multipliernum_local_expertsnum_experts_per_tokshared_intermediate_sizeoutput_router_logitsrouter_aux_loss_coefsuper__init__),selfr.r,r/r0r1r2r9r:r;r<r=r>r?r)r*r+r@rArBrCrDrErFrGrHrIrJrKrLrMrNrPrQrRrSrTrUrVrWrXkwargsi layer_type __class__r-W/home/ubuntu/.local/lib/python3.10/site-packages/sglang/srt/configs/granitemoehybrid.pyrZs,      zGraniteMoeHybridConfig.__init__cfddtjDS)z4Returns the indices of layers that are Mamba layers.cg|] }j|tkr|qSr-)r2r6.0r]r[r-ra z:GraniteMoeHybridConfig.mamba_layer_ids..r3r1rfr-rframamba_layer_ids  z&GraniteMoeHybridConfig.mamba_layer_idscrb)z8Returns the indices of layers that are attention layers.crcr-)r2r5rdrfr-rargrhz>GraniteMoeHybridConfig.attention_layer_ids..rirfr-rfraattention_layer_idsrkz*GraniteMoeHybridConfig.attention_layer_idscCs|jS)z0Alias for attention_layer_ids for compatibility.)rlrfr-r-rafull_attention_layer_idssz/GraniteMoeHybridConfig.full_attention_layer_idsc Cs@ddlm}tj||j|j|j|j|j|j d}t ||j dS)z;Returns the Mamba2 cache parameters for this configuration.r)get_attention_tp_size) tp_world_sizer0n_groups num_headshead_dim state_size conv_kernel)shapelayers) sglang.srt.layers.dp_attentionrnrcreaterOrKrJrIrFrGrrj)r[rnrur-r-ramamba2_cache_paramss  z*GraniteMoeHybridConfig.mamba2_cache_params)(r Tr r rNrrrrrrTrrrrrFrrNrrrrrrr TFr!r"r#r$rrr Fr%) __name__ __module__ __qualname____doc__ model_typekeys_to_ignore_at_inferencerZpropertyrjrlrmry __classcell__r-r-r_rarsla   rN)r} transformers.configuration_utilsrtransformers.utilsrsglang.srt.configs.mamba_utilsrr get_loggerrzloggerr6r5rr-r-r-ras