
    g&                       d dl mZ d dlZd dlZd dlZd dlZd dlZd dlZd dl	m
Z
 d dlmZmZ d dlmZmZmZmZmZmZ d dlmZ d dlmZ d dlZ ej6                  d      Zdd	Zdd
Z	 	 d	 	 	 	 	 	 	 	 	 	 	 ddZddZ g fddZ!e"dk(  r7dZ#ejH                  jG                  e#        ejJ                  e#        e!        yy)    )annotationsN)setup_logger)get_rankget_size)add_io_bindings_as_ortvaluesconvert_inputs_for_ort%get_merged_sample_with_past_kv_inputsget_sample_inputsget_sample_with_past_kv_inputsverify_ort_inputs)setup_torch_model)
AutoConfig c                J    | j                   rdnd\  }}|j                  }|||fS )N)      )r   r   )use_past_kvmax_position_embeddings)argsconfigpast_sequence_lengthcurr_sequence_lengthmax_sequence_lengths        g/var/www/openai/venv/lib/python3.12/site-packages/onnxruntime/transformers/models/llama/llama_parity.pyget_sequence_lengthsr   !   s4    ;?;K;KQW.. 88!57JJJ    c                \   t               }d}t        | |      \  }}}| j                  r5t        || j                  ||||| j
                  | j                  d|
      }|S | j                  r(t        || j                  ||| j
                  d|      }|S t        || j                  ||d      }|S )N   T)seq_lenpast_seq_lenmax_seq_lenuse_fp16use_buffer_sharereturn_dict
world_size)r"   r$   r%   )r$   )
r   r   mergedr	   devicer"   r#   r   r   r
   )r   r   r%   
batch_sizer   sequence_lengthr   inputss           r   
get_inputsr+   '   s    JJAUVZ\bAc>/+>{{6KK#-+]]!22!
2 M 
		/KK]]!
 M #64;;
OaefMr   c                "   |}|Gt        | ||| j                  rt        j                  nt        j                  | j
                        \  }}t        | |      }| j                  dk7  rt        j                  j                          t        j                         } |di |j                  j                         j                         j                         }	| j                  dk7  rt        j                  j                          t        j                         }
t        j!                  d|
|z
   d       | j"                  r!|~t        j                  j%                          t'        | |      \  }}}t)        || j*                  ||      }| j                  j-                          d}|dk(  r|d| j.                  if}t1        j2                  | j4                  t1        j6                         |g	      }t9        ||      }| j                  dk7  rt;        ||| j                  t=        | j.                        | j*                  |
      \  }}|j?                          t        j                         }|jA                  |       |jC                          t        j                         }
|jE                         d   }~n?t        j                         }|jG                  d |      }t        j                         }
|d   }t        j!                  d|
|z
   d       d| j4                  v sd| j4                  v rdnd}tI        jJ                  |	|||      }t        jM                  d|        |s.t        jM                  dtI        jN                  |	|z
                |S )Ntorch_dtyper'   cpuzPyTorch took z s)r#   r    r!   ExecutionProviderCUDAExecutionProvider	device_id)sess_options	providers)
ort_inputsr'   r2   r#   kv_cache_ortvaluesr   zONNX Runtime took int4int8g      4@g      ?)rtolatolz,Are PyTorch and ONNX Runtime results close? z
Max diff:  )(r   r"   torchfloat16float32r'   r+   execution_providercudasynchronizetimelogitsdetachr/   numpyloggerinfo	small_gpuempty_cacher   r   r#   upperrankortInferenceSessiononnx_model_pathSessionOptionsr   r   intsynchronize_inputsrun_with_iobindingsynchronize_outputscopy_outputs_to_cpurunnpallclosewarningmax)r   locationuse_auth_tokenr6   pytorch_modelr   py_modelr*   
start_time
pt_outputsend_timer   _r   ep	ort_model
io_bindingort_outputstolparitys                       r   verify_parityrh   J   s    H,*.--U]];;
 f%F %'

 J#F#**113779??AJ%'

 yy{H
KK-: 56b9:~~(.

  4Hf3U0!0#..)'	F ##))+,,=	>B	$$;		*+$$'')$I
 y&1F %')E**$))n!221*
&
& 	%%'YY[
$$Z0&&(99; 446q9 YY[
mmD&199;!!n
KK$X
%:$;2>? 4///6T=Q=Q3Q#W[C[[[sEF
NNA&JKBFF:+C$D#EFGr   c                   t        j                         }|j                  dddd       |j                  dddt        j                  j                  d      d	
       |j                  dddt        j                  j                  d      d
       |j                  ddddg dd       |j                  dddd       |j                  d       |j                  dddd       |j                  d       |j                  dd dd!       |j                  d"       |j                  d#dd$       |j                  d%       |j                  d&d'dg d(d)*       |j                  d+dt        d,d-.       |j                  d/dd0       | g k(  r|j                         n|j                  |       }|j                  d1v s|j                  d2k(  r|j                  dk(  r	d3|_	        |S d4|_	        |S )5Nz-mz--model_nameFzModel name in Hugging Face)requiredhelpz-tz--torch_model_directory.zMPath to folder containing PyTorch model and associated files if saved on disk)rj   defaultrk   z-oz--onnx_model_pathTzSPath to ONNX model (with external data files saved in the same folder as the model)z-epz--execution_providerr/   )r/   r@   rocmz(Execution provider to verify parity with)rj   rm   choicesrk   z-vz	--verbose
store_truezPrint verbose logs)actionrk   )verbosez-pz--use_past_kvzfUse past key and past value as inputs to the model. Necessary for decoder_with_past_model.onnx models.)r   z-gz--use_buffer_sharezWUse if model has GroupQueryAttention and you want to enable past-present buffer sharing)r#   z--mergedz2Use merged model (i.e. decoder_merged_model.onnx).)r&   z-fpz--precision)r7   r8   fp16fp32zPrecision of model)rj   ro   rk   z--cache_dirz./model_cachezQmodel cache dir to override default HF cache dir to avoid overflood the /home dir)rj   typerm   rk   z--small_gpuzhLoad the llama in GPU every time for parity_check if it's running in a machine which GPU memory < 36GB. >   rt   r8   r7   rt   rs   )argparseArgumentParseradd_argumentospathjoinset_defaultsstr
parse_args	precisionr?   )argvparserr   s      r   get_argsr      sT   $$&F
)	   !S!\   S!b   '7   !	   &
u	   E*
f	   /
A  
 u%
0!   `   w   #'"*6&2C2CD2ID
 >>--$..F2JtOfOfjoOo 	 	N
 K  	N
 Kr   c                4   t        |       }t        |j                         t        j	                  d|        t               }t        |d|j                  dk(         ||_        t        |d|j                  dk(  rdnd|        t        |dt        j                  |j                               |j                  t        j                  j!                  d      k(  }|r|j"                  n|j                  }i }|j$                  st'        ||||       y d x}}|j(                  sGt+        ||||j,                  rt        j.                  nt        j0                  |j                  	      \  }}d
|_        t'        ||||||      }d|_        t'        ||||||       y )NzArguments: r"   rs   device_namer/   zcuda:r'   rl   r-   F)r\   r   T)r   r   rr   rF   rG   r   setattrr   rK   r?   r<   r'   r   torch_model_directoryry   rz   r{   
model_namer&   rh   rH   r   r"   r=   r>   r   )r   r   rK   r[   rZ   r6   r   llamas           r   mainr   
  s`   D>D
KK+dV$%:D D*dnn67DID-$*A*AU*JRWX\W]P^_D(ELL)9)9:;//277<<3DDN"0td6P6PH;;dHn6HI~~-.2mmU]]{{MFE !*(N,>e\b

  dHn6HX]flmr   __main__r   )r   argparse.Namespacer   r   )NN)r   r   rZ   r}   r[   boolr6   dictr\   zNone | torch.nn.Moduler   zNone | AutoConfig)r   z	list[str])&
__future__r   rv   loggingry   rB   rE   rV   r<   benchmark_helperr   dist_settingsr   r   llama_inputsr   r   r	   r
   r   r   llama_torchr   transformersr   onnxruntimerL   	getLoggerrF   r   r+   rh   r   r   __name__seedrandommanual_seedr;   r   r   <module>r      s    #   	    ) ,  * # 			2	K P -1 $Y
YY Y 	Y
 *Y YxaH  $nN zDIINN4EdF	 r   