o
    Ti                     @   s   d dl mZmZmZ d dlZd dlmZ ddlm	Z	 ddl
mZmZ ddlT ddlT ddlT ddlmZ d	d
lmZmZ G dd deZdS )    )IterableOptionalTupleN   )
empty_from)ActivationType	DtypeEnum   )*)RaggedBatchWrapper   )Phi3NonTransformerContainerPhi3TransformerContainerc                   @   s  e Zd ZU dZee ed< 	 eee  ed< 	 	 e	de
fddZ	 e	de
fddZe	de
fd	d
Ze	de
fddZe	de
fddZe	de
fddZe	de
fddZe	de
fddZe	defddZe	defddZe	defddZe	defddZe	dee fddZ	 dedejfd d!Z d"e
d#ejd$ejd%ede!ejejf f
d&d'Z"d$ejd%edejfd(d)Z#d*edejfd+d,Z$d-S ).Phi3InferenceModelzP
    Inference model implementation for ragged batching for Llama-2 models.
    _non_transformer_transformerreturnc                 C      | j jS N)_configmax_seq_lengthself r   k/home/ubuntu/.local/lib/python3.10/site-packages/deepspeed/inference/v2/model_implementations/phi3/model.pymax_sequence_length(      z&Phi3InferenceModel.max_sequence_lengthc                 C   r   r   )r   num_hidden_layersr   r   r   r   
num_layers0   r   zPhi3InferenceModel.num_layersc                 C   r   r   )r   hidden_sizer   r   r   r   	model_dim4   r   zPhi3InferenceModel.model_dimc                 C   r   r   )r   
vocab_sizer   r   r   r   r!   8   r   zPhi3InferenceModel.vocab_sizec                 C   s   | j | j S r   )r    n_headsr   r   r   r   	head_size<   s   zPhi3InferenceModel.head_sizec                 C   r   r   )r   num_attention_headsr   r   r   r   r"   @   r   zPhi3InferenceModel.n_headsc                 C   r   r   )r   intermediate_sizer   r   r   r   intermediate_dimD   r   z#Phi3InferenceModel.intermediate_dimc                 C   r   r   )r   num_key_value_headsr   r   r   r   
n_heads_kvH   r   zPhi3InferenceModel.n_heads_kvc                 C   s0   | j jtjkr
tjS | j jtjkrtjS td)Nz Only fp16 and bf16 are supported)	r   torch_dtypetorchfloat16r   fp16bfloat16bf16NotImplementedErrorr   r   r   r   activation_dtypeL   s
   z#Phi3InferenceModel.activation_dtypec                 C   sT   | j j }|dkrtjS |dkrtjS |dkrtjS |dkr"tjS td| d)NgelurelugegelusiluzActivation z not supported)r   
hidden_actlowerr   GEGLUReGLUSiGLUr/   )r   
activationr   r   r   mlp_activation_fnU   s   z$Phi3InferenceModel.mlp_activation_fnc                 C      t jS r   )NormTypeEnumRMSNormr   r   r   r   	norm_typec      zPhi3InferenceModel.norm_typec                 C   r<   r   )PositionalEmbeddingTyperotate_halfr   r   r   r   positional_embedding_typeg   r@   z,Phi3InferenceModel.positional_embedding_typec                 C   s   t | jjdS )N)
theta_base)RotateHalfConfigr   
rope_thetar   r   r   r   positional_embedding_configk   s   z.Phi3InferenceModel.positional_embedding_configragged_batchc                 C   s<   |  || jj}|jd | jkrtd|j d| j |S )z
        Performs the embedding lookup prior to running the transformer of the model.

        Arguments:
            ragged_batch (RaggedBatchWrapper): The batch to embed.

        Returns:
            torch.Tensor: The embedded batch.
        zEmbedding output shape z does not match model_dim )embedr   word_embshaper    
ValueError)r   rH   rJ   r   r   r   _forward_embeds   s   
z!Phi3InferenceModel._forward_embed	layer_idxresidualhidden_statesragged_batch_infoc                 C   s  | j | }| j|}| j||jdd}| |||}| j||jdd}| jdkr1t	j
|| jd | j|||jdd\}}| j||jdd}| j||jdd}| jdkr\t	j
|| jd || jd krz| j |d  }| j|||jdd\}}||fS || ||fS )aL  
        Executes one (slightly offset) layer of the transformer. This implementation does a peak-ahead
        optimization to fuse the layer norm of the next layer into the current layer.

        Arguments:
            layer_idx (int): The index of the layer to execute.
            residual (torch.Tensor): The residual tensor from the previous layer.
            hidden_states (torch.Tensor): The hidden states from the previous layer. This is the
                hidden states after pre normalization.
            ragged_batch_info (RaggedBatchWrapper): The batch metadata.
        N)br   group)beta)r   state_manager	get_cacheqkvqkv_wattnattn_out
attn_out_wtp_sizedist
all_reduce_base_mp_groupnormmlp_norm_gammamlp_1mlp_1_wmlp_2mlp_2_wr   attn_norm_gammaadd_)r   rO   rP   rQ   rR   
cur_paramskv_cachenext_paramsr   r   r   _forward_transformer_layer   s$   



z-Phi3InferenceModel._forward_transformer_layerc                 C   s   | j || jj|| jjd}| jdkrKt| j| j|jd |jd f}t| j|jd | j	f}t
j||| jd ||ddd|jd | j	 |S |S )z
        Performs unembedding of the hidden states to logits. This will only sample the final
        token of each sequence.
        )gammar   r   rT   r	   )unembedr   word_unembed_wfinal_norm_gammar^   r   _comm_logitsrL   _return_logitsr!   r_   all_gather_into_tensorra   copy_permutereshape)r   rQ   rR   logitscomm_bufferfull_logitsr   r   r   _forward_unembed   s   
 $z#Phi3InferenceModel._forward_unembedwrapped_batchc                 C   sX   |  |}| j|d | jd jd d\}}t| jD ]}| ||||\}}q| ||S )Nr   )rn   rV   )rN   rb   r   rh   ranger   rm   r{   )r   r|   rP   rQ   rO   r   r   r   forward   s   


zPhi3InferenceModel.forwardN)%__name__
__module____qualname____doc__r   r   __annotations__r   r   propertyintr   r   r    r!   r#   r"   r&   r(   r   r0   r   r;   r=   r?   rA   rC   rE   rG   r   r*   TensorrN   r   rm   r{   r~   r   r   r   r   r      sV   
 
)r   )typingr   r   r   r*   deepspeed.commcommr_   	allocatorr   inference_utilsr   r    modules.configsmodules.interfacesraggedr   
containersr   r   DSTransformerModelBaser   r   r   r   r   <module>   s   