
     Ti~                        S SK Jr  S SKJr  S SKrS SKrS SKrS SKr	S SK
Jr  SS jrS\	R                  R                  SSS4             SS	 jjr      SS
 jr      SS jrg)    )annotations)AnyN)irc                   0 nU R                   R                   GHR  nUR                  R                  n[	        UR
                  R                  5      n[        S U 5       5      (       d  [        SUR                   S35      e[	        S U 5       5      nUR                  [        R                  R                  :X  a  U(       aH  [        R                  R                   " U6 R#                  [        R$                  5      XR                  '   M  [        R                  R!                  S5      R#                  [        R$                  5      XR                  '   GM=  [        SUR                   35      e   U$ )Nc              3  :   #    U  H  n[        US 5      v   M     g7f)	dim_valueN)hasattr.0ds     Z/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/onnxscript/rewriter/testing.py	<genexpr>)generate_random_inputs.<locals>.<genexpr>   s     :Eq71k**Es   zInput z has dynamic shape dimensions.c              3  8   #    U  H  oR                   v   M     g 7f)N)r   r
   s     r   r   r      s     15akk5s      zNot implemented for input type )graphinputtypetensor_typetupleshapedimall
ValueErrorname	elem_typeonnxTensorProtoFLOATnprandomrandnastypefloat32)modelfeedsr   
input_typer   s        r   generate_random_inputsr(      s   E""ZZ++
j&&**+:E:::vejj\1OPQQ15114#3#3#9#99$&IIOOU$;$B$B2::$Njj!$&IIOOA$6$=$=bjj$Ijj!>z?S?S>TUVV # L    r   gMbP?Fc                H   [        U [        R                  5      (       a  [        R                  R	                  U 5      n [        U[        R                  5      (       a  [        R                  R	                  U5      nUc  [        U 5      nUnO[        U[        5      (       a  UnUnO~[        U R                  R                  U5       V	V
s0 s H  u  pU	R                  U
_M     nn	n
[        UR                  R                  U5       V	V
s0 s H  u  pU	R                  U
_M     nn	n
U(       aY  [        U R                  5       U5      nUR                  SU5      n[        UR                  5       U5      nUR                  SU5      nOr[        U R                  5       U5      n[        R                   " 5       nSUl        UR                  SUUS9n[        UR                  5       U5      nUR                  SUUS9n[$        R&                  R)                  XXESS9  gs  sn
n	f s  sn
n	f )a  Assert that the two models are numerically equal.

Args:
    original_model_proto: The original model proto or ir.Model.
    rewritten_model_proto: The rewritten by the rules model proto or ir.Model.
    args: The positional arguments to pass to the model.
    ort_optimization_level: Onnxruntime optimization level.
    rtol: Relative tolerance.
    atol: Absolute tolerance.
    use_reference: If True, use ONNX reference implementation instead of ONNXRuntime.
N   )run_optionsT)rtolatol	equal_nan)
isinstancer   Modelserdeserialize_modelr(   dictzipr   r   r   _reference_sessionSerializeToStringrun_ort_session_initializerort
RunOptionslog_severity_levelr    testingassert_allclose)original_model_protorewritten_model_protoargsort_optimization_levelr-   r.   use_referenceoriginal_proto_ort_inputsthe_rewritten_proto_ort_inputskvoriginal_evaluatororiginal_outputsrewritten_evaluatorthe_rewritten_outputs$original_proto_ort_inference_sessionr,   )the_rewritten_proto_ort_inference_sessions                     r   assert_numerically_equalrN   !   s    * &11!xx778LM'22 " 8 89N O|$:;O$P!)B&	D$		$(!)-& #&&:&@&@&F&F"M%
"M$!AFFAI"M 	" %
 #&&;&A&A&G&G"N*
"N$!AFFAI"N 	' *
 / 2246L
 .11$8QR0!3357M
 !4 7 7>\ ] 0H 2246L0
, nn&)*&?CC+ D 
 5M!3357M5
1 !J M M0k !N !
 JJdQU  I%
*
s   H
Hc                    SSK nUR                  " 5       nSUl        Xl        Sn[	        UR
                  " 5       5      nU Vs/ s H  ofU;   d  M
  UPM     nnUR                  " XUS9$ s  snf )zFInitialize an ONNX Runtime inference session with the specified model.r   Nr+   )CUDAExecutionProviderCPUExecutionProvider)	providerssess_options)onnxruntimeSessionOptionsr<   graph_optimization_levelsetget_available_providersInferenceSession)r%   rB   r:   session_optionspossible_providersavailable_providersproviderrR   s           r   r9   r9   k   s~     ((*O)*O&/E, c99;<!3!3XCV7V!3   YYs   	A)A)c                    [        U [        [        45      (       a  [        R                  " U 5      nOU n[        R
                  R                  U5      $ )z@Initialize an ONNX reference evaluator with the specified model.)r0   strbytesr   load_from_string	referenceReferenceEvaluator)r%   rB   model_protos      r   r6   r6      sA    
 %#u&&++E2 >>,,[99r)   )r%   zonnx.ModelProtoreturnzdict[str, Any])r?   onnx.ModelProto | ir.Modelr@   rf   rA   z'tuple[Any, ...] | dict[str, Any] | NonerB   ort.GraphOptimizationLevelr-   floatr.   rh   rC   bool)r%   str | bytesrB   rg   re   zort.InferenceSession)r%   rj   rB   rg   re   z!onnx.reference.ReferenceEvaluator)
__future__r   typingr   numpyr    r   onnx.referencerT   r:   
onnxscriptr   r(   GraphOptimizationLevelORT_ENABLE_ALLrN   r9   r6    r)   r   <module>rs      s    #      * 599<9S9S9b9bG4G5G 2G 7	G
 G G GTZZ0JZZ(::0J:&:r)   