o Zh&@spdZddlmZmZddlmZddlmZee Z GdddeZ Gdd d eZ Gd d d eZ d gZd S) zDBRX model configuration)AnyOptional)PretrainedConfig)loggingc sHeZdZdZdZ    ddedeed ed ed ef fd d Z Z S)DbrxAttentionConfiga_Configuration class for Dbrx Attention. [`DbrxAttention`] class. It is used to instantiate attention layers according to the specified arguments, defining the layers architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: attn_pdrop (`float`, *optional*, defaults to 0.0): The dropout probability for the attention layers. clip_qkv (`float`, *optional*): If set, clip the queries, keys, and values in the attention layer to this value. kv_n_heads (`int`, *optional*, defaults to 1): For grouped_query_attention only, allow user to specify number of kv heads. rope_theta (`float`, *optional*, defaults to 10000.0): The base frequency for rope. attn_configN@ attn_pdropclip_qkv kv_n_heads rope_thetakwargsc sdtjdi|||_||_||_||_dD] }||vr"||qt|dkr0td|dS)N model_typeZattn_implementationZtransformers_versionZ _commit_hashZ torch_dtyperFound unknown kwargs=) super__init__r r rrpoplen ValueError)selfr r rrrk __class__rZ/var/www/auris/lib/python3.10/site-packages/transformers/models/dbrx/configuration_dbrx.pyr.s  zDbrxAttentionConfig.__init__)r Nr r ) __name__ __module__ __qualname____doc__base_config_keyfloatrintrr __classcell__rrrrrs$rcsbeZdZdZdZ       dd eed ed ed ed eededeede ffdd Z Z S) DbrxFFNConfiga|Configuration class for Dbrx FFN. [`DbrxFFN`] class. It is used to instantiate feedforward layers according to the specified arguments, defining the layers architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: ffn_act_fn (`dict`, *optional*, defaults to `None`): A dict specifying activation function for the FFN. The dict should have a key 'name' with the value being the name of the activation function along with any additional keyword arguments. If `None`, then set to `{"name": "silu"}`. ffn_hidden_size (`int`, *optional*, defaults to 3584): The hidden size of the feedforward network. moe_num_experts (`int`, *optional*, defaults to 4): The number of experts in the mixture of experts layer. moe_top_k (`int`, *optional*, defaults to 1): The number of experts to use in the mixture of experts layer. moe_jitter_eps (`float`, *optional*, defaults to `None`): If not `None`, the jitter epsilon for the mixture of experts layer. moe_loss_weight (`float`, *optional*, defaults to 0.01): The loss weight for the mixture of experts layer. moe_normalize_expert_weights (`float`, *optional*, defaults to 1.0): The normalization factor for the expert weights. ffn_configNr {Gz?? ffn_act_fnffn_hidden_sizemoe_num_experts moe_top_kmoe_jitter_epsmoe_loss_weightmoe_normalize_expert_weightsrc  s~t|dur ddi}||_||_||_||_||_||_||_dD] } | |vr/| | q$t |dkr=t d|dS)NnameZsilurrr) rrr-r.r/r0r1r2r3rrr) rr-r.r/r0r1r2r3rrrrrrZs"   zDbrxFFNConfig.__init__)Nr)r*r Nr+r,) rr r!r"r#rdictr%r$rrr&rrrrr'Cs6 r'cseZdZdZdZeedZdddddZ     dde de de de de de de de ede ede de de de ffdd ZZS) DbrxConfiga. This is the configuration class to store the configuration of a [`DbrxModel`]. It is used to instantiate a Dbrx model according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a different configuration to that of the [databricks/dbrx-instruct](https://huggingface.co/databricks/dbrx-instruct) architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: d_model (`int`, *optional*, defaults to 2048): Dimensionality of the embeddings and hidden states. n_heads (`int`, *optional*, defaults to 16): Number of attention heads for each attention layer in the Transformer encoder. n_layers (`int`, *optional*, defaults to 24): Number of hidden layers in the Transformer encoder. max_seq_len (`int`, *optional*, defaults to 2048): The maximum sequence length of the model. vocab_size (`int`, *optional*, defaults to 32000): Vocabulary size of the Dbrx model. Defines the maximum number of different tokens that can be represented by the `inputs_ids` passed when calling [`DbrxModel`]. resid_pdrop (`float`, *optional*, defaults to 0.0): The dropout probability applied to the attention output before combining with residual. emb_pdrop (`float`, *optional*, defaults to 0.0): The dropout probability for the embedding layer. attn_config (`dict`, *optional*): A dictionary used to configure the model's attention module. ffn_config (`dict`, *optional*): A dictionary used to configure the model's FFN module. use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. output_router_logits (`bool`, *optional*, defaults to `False`): Whether or not the router logits should be returned by the model. Enabling this will also allow the model to output the auxiliary loss. See [here]() for more details. Example: ```python >>> from transformers import DbrxConfig, DbrxModel >>> # Initializing a Dbrx configuration >>> configuration = DbrxConfig(n_layers=2, d_model=256, n_heads=8, vocab_size=128) >>> # Initializing a model (with random weights) from the configuration >>> model = DbrxModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` Zdbrx)rr(n_headsd_modeln_layers max_seq_len)Znum_attention_headsZ hidden_sizeZnum_hidden_layersZmax_position_embeddings}r NT{Gz?F vocab_size resid_pdrop emb_pdroprr( use_cacheinitializer_rangeoutput_router_logitsrc  s|dur t|_nt|trtdi||_n||_| dur#t|_nt| tr1tdi| |_n| |_||_||_||_||_ ||_ ||_ ||_ | |_ | |_| |_|jj|_| dd}|rctdtjdd|i| dS)Ntie_word_embeddingsFz5tie_word_embeddings is not supported for DBRX models.r)rr isinstancer5r'r(r8r7r9r:r@rArBrCrDrErZnum_key_value_headsrrrr)rr8r7r9r:r@rArBrr(rCrDrErrFrrrrs2      zDbrxConfig.__init__) r;r<r=r;r>r r NNTr?F)rr r!r"rrr'Z sub_configsZ attribute_mapr%r$rboolrrr&rrrrr6ws`6       r6N)r"typingrrZconfiguration_utilsrutilsrZ get_loggerrloggerrr'r6__all__rrrrs   )4 q