ó
    EñiK  ã                   ó^  • % S SK Jr  S SKJrJrJrJr  S SKrS SKJ	r	  SSK
Jr  SSKJr  SSKJrJrJr  SS	KJr  SS
KJrJr  / SQr " S S\	R0                  5      rS<S\\\\4      S\S\	R<                  4S jjr/ SQ/ SQ/ SQ/ SQS.r \!\\\\\4      4   \"S'   S\S\S\\   S\S\S\4S jr#S\SSS.r$ " S  S!\5      r% " S" S#\5      r& " S$ S%\5      r' " S& S'\5      r( " S( S)\5      r) " S* S+\5      r* " S, S-\5      r+ " S. S/\5      r,\" 5       \" S0\%RZ                  4S19SS2S3.S\\%   S\S\S\4S4 jj5       5       r.\" 5       \" S0\&RZ                  4S19SS2S3.S\\&   S\S\S\4S5 jj5       5       r/\" 5       \" S0\'RZ                  4S19SS2S3.S\\'   S\S\S\4S6 jj5       5       r0\" 5       \" S0\(RZ                  4S19SS2S3.S\\(   S\S\S\4S7 jj5       5       r1\" 5       \" S0\)RZ                  4S19SS2S3.S\\)   S\S\S\4S8 jj5       5       r2\" 5       \" S0\*RZ                  4S19SS2S3.S\\*   S\S\S\4S9 jj5       5       r3\" 5       \" S0\+RZ                  4S19SS2S3.S\\+   S\S\S\4S: jj5       5       r4\" 5       \" S0\,RZ                  4S19SS2S3.S\\,   S\S\S\4S; jj5       5       r5g)=é    )Úpartial)ÚAnyÚcastÚOptionalÚUnionNé   )ÚImageClassification)Ú_log_api_usage_onceé   )Úregister_modelÚWeightsÚWeightsEnum)Ú_IMAGENET_CATEGORIES)Ú_ovewrite_named_paramÚhandle_legacy_interface)ÚVGGÚVGG11_WeightsÚVGG11_BN_WeightsÚVGG13_WeightsÚVGG13_BN_WeightsÚVGG16_WeightsÚVGG16_BN_WeightsÚVGG19_WeightsÚVGG19_BN_WeightsÚvgg11Úvgg11_bnÚvgg13Úvgg13_bnÚvgg16Úvgg16_bnÚvgg19Úvgg19_bnc                   ó”   ^ • \ rS rSr SS\R
                  S\S\S\SS4
U 4S jjjr	S	\
R                  S\
R                  4S
 jrSrU =r$ )r   é#   ÚfeaturesÚnum_classesÚinit_weightsÚdropoutÚreturnNc                 óô  >• [         TU ]  5         [        U 5        Xl        [        R
                  " S5      U l        [        R                  " [        R                  " SS5      [        R                  " S5      [        R                  " US9[        R                  " SS5      [        R                  " S5      [        R                  " US9[        R                  " SU5      5      U l        U(       Ga‰  U R                  5        GHs  n[        U[        R                  5      (       ad  [        R                  R!                  UR"                  SSS9  UR$                  b,  [        R                  R'                  UR$                  S	5        M…  M‡  [        U[        R(                  5      (       aV  [        R                  R'                  UR"                  S
5        [        R                  R'                  UR$                  S	5        Mü  [        U[        R                  5      (       d  GM  [        R                  R+                  UR"                  S	S5        [        R                  R'                  UR$                  S	5        GMv     g g )N)é   r+   i b  i   T)ÚpÚfan_outÚrelu)ÚmodeÚnonlinearityr   r   g{®Gáz„?)ÚsuperÚ__init__r
   r%   ÚnnÚAdaptiveAvgPool2dÚavgpoolÚ
SequentialÚLinearÚReLUÚDropoutÚ
classifierÚmodulesÚ
isinstanceÚConv2dÚinitÚkaiming_normal_ÚweightÚbiasÚ	constant_ÚBatchNorm2dÚnormal_)Úselfr%   r&   r'   r(   ÚmÚ	__class__s         €ÚS/home/mande/repo/quber/.venv/lib/python3.13/site-packages/torchvision/models/vgg.pyr2   ÚVGG.__init__$   s‰  ø€ ô 	‰ÑÔÜ˜DÔ!Ø ŒÜ×+Ò+¨FÓ3ˆŒÜŸ-š-Ü�IŠI�k 4Ó(Ü�GŠG�D‹MÜ�JŠJ˜Ñ!Ü�IŠI�d˜DÓ!Ü�GŠG�D‹MÜ�JŠJ˜Ñ!Ü�IŠI�d˜KÓ(ó
ˆŒ÷ Ø—\‘\—^�Ü˜a¤§¡×+Ñ+Ü—G‘G×+Ñ+¨A¯H©H¸9ÐSYÐ+ÑZØ—v‘vÑ)ÜŸ™×)Ñ)¨!¯&©&°!Ö4ñ *ä ¤2§>¡>×2Ñ2Ü—G‘G×%Ñ% a§h¡h°Ô2Ü—G‘G×%Ñ% a§f¡f¨aÖ0Ü ¤2§9¡9×-Ô-Ü—G‘G—O‘O A§H¡H¨a°Ô6Ü—G‘G×%Ñ% a§f¡f¨a×0ò $ð ó    Úxc                 óš   • U R                  U5      nU R                  U5      n[        R                  " US5      nU R	                  U5      nU$ )Nr   )r%   r5   ÚtorchÚflattenr:   )rE   rK   s     rH   ÚforwardÚVGG.forwardA   s@   € Ø�M‰M˜!ÓˆØ�L‰L˜‹OˆÜ�MŠM˜!˜QÓˆØ�O‰O˜AÓˆØˆrJ   )r5   r:   r%   )iè  Tg      à?)Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__r3   ÚModuleÚintÚboolÚfloatr2   rM   ÚTensorrO   Ú__static_attributes__Ú__classcell__)rG   s   @rH   r   r   #   s\   ø† àhkñ1ØŸ	™	ð1Ø03ð1ØJNð1Ø`eð1à	÷1ð 1ð:˜Ÿ™ð ¨%¯,©,÷ ò rJ   r   ÚcfgÚ
batch_normr)   c                 ón  • / nSnU  H™  nUS:X  a  U[         R                  " SSS9/-  nM$  [        [        U5      n[         R                  " X4SSS9nU(       a.  X%[         R
                  " U5      [         R                  " SS9/-  nOX%[         R                  " SS9/-  nUnM›     [         R                  " U6 $ )	Né   ÚMr   )Úkernel_sizeÚstrider   )ra   ÚpaddingT)Úinplace)r3   Ú	MaxPool2dr   rV   r=   rC   r8   r6   )r\   r]   ÚlayersÚin_channelsÚvÚconv2ds         rH   Úmake_layersrj   I   s¢   € Ø €FØ€KÛˆØ�‹8Ø”r—|’|°¸!Ñ<Ð=Ñ=ŠFä”S˜!“ˆAÜ—Y’Y˜{¸1ÀaÑHˆFÞØ¤2§>¢>°!Ó#4´b·g²gÀdÑ6KÐLÑL‘à¤2§7¢7°4Ñ#8Ð9Ñ9�ØŠKñ ô �=Š=˜&Ð!Ð!rJ   )é@   r`   é€   r`   é   rm   r`   é   rn   r`   rn   rn   r`   )rk   rk   r`   rl   rl   r`   rm   rm   r`   rn   rn   r`   rn   rn   r`   )rk   rk   r`   rl   rl   r`   rm   rm   rm   r`   rn   rn   rn   r`   rn   rn   rn   r`   )rk   rk   r`   rl   rl   r`   rm   rm   rm   rm   r`   rn   rn   rn   rn   r`   rn   rn   rn   rn   r`   )ÚAÚBÚDÚEÚcfgsÚweightsÚprogressÚkwargsc                 óö   • Ub8  SUS'   UR                   S   b#  [        US[        UR                   S   5      5        [        [	        [
        U    US940 UD6nUb  UR                  UR                  USS95        U$ )NFr'   Ú
categoriesr&   )r]   T)ru   Ú
check_hash)Úmetar   Úlenr   rj   rs   Úload_state_dictÚget_state_dict)r\   r]   rt   ru   rv   Úmodels         rH   Ú_vggr   b   s   € ØÑØ!&ˆˆ~ÑØ�<‰<˜Ñ%Ñ1Ü! &¨-¼¸W¿\¹\È,Ñ=WÓ9XÔYÜ”œD ™I°*Ñ=ÑHÀÑH€EØÑØ×Ñ˜g×4Ñ4¸hÐSWÐ4ÐXÔYØ€LrJ   )é    r€   zUhttps://github.com/pytorch/vision/tree/main/references/classification#alexnet-and-vggzNThese weights were trained from scratch by using a simplified training recipe.)Úmin_sizerx   ÚrecipeÚ_docsc            
       óN   • \ rS rSr\" S\" \SS90 \ESSSSS	.0S
SS.ES9r\r	Sr
g)r   éu   z6https://download.pytorch.org/models/vgg11-8a719046.pthéà   ©Ú	crop_sizeihUëúImageNet-1Kgáz®GAQ@gÕxé&1(V@©zacc@1zacc@5çV-²�o@g=
×£p­@©Ú
num_paramsÚ_metricsÚ_opsÚ
_file_size©ÚurlÚ
transformsrz   © N©rQ   rR   rS   rT   r   r   r	   Ú_COMMON_METAÚIMAGENET1K_V1ÚDEFAULTrZ   r”   rJ   rH   r   r   u   sQ   † ÙØDÙÐ.¸#Ñ>ð
Øð
à#àØ#Ø#ñ ðð Ø ò
ñ€Mð  ƒGrJ   r   c            
       óN   • \ rS rSr\" S\" \SS90 \ESSSSS	.0S
SS.ES9r\r	Sr
g)r   é‰   z9https://download.pytorch.org/models/vgg11_bn-6002323d.pthr†   r‡   ièjër‰   gHáz®—Q@g¤p=
×sV@rŠ   r‹   gj¼t“®@rŒ   r‘   r”   Nr•   r”   rJ   rH   r   r   ‰   óQ   † ÙØGÙÐ.¸#Ñ>ð
Øð
à#àØ#Ø#ñ ðð Ø!ò
ñ€Mð  ƒGrJ   r   c            
       óN   • \ rS rSr\" S\" \SS90 \ESSSSS	.0S
SS.ES9r\r	Sr
g)r   é�   z6https://download.pytorch.org/models/vgg13-19584684.pthr†   r‡   i(&îr‰   g¬Zd{Q@g9´Èv¾OV@rŠ   çV-²�&@g…ëQ¸¸@rŒ   r‘   r”   Nr•   r”   rJ   rH   r   r   �   óQ   † ÙØDÙÐ.¸#Ñ>ð
Øð
à#àØ#Ø#ñ ðð Ø!ò
ñ€Mð  ƒGrJ   r   c            
       óN   • \ rS rSr\" S\" \SS90 \ESSSSS	.0S
SS.ES9r\r	Sr
g)r   é±   z9https://download.pytorch.org/models/vgg13_bn-abd245e5.pthr†   r‡   i(=îr‰   g/Ý$�åQ@g-²�ï—V@rŠ   rž   g=
×£p¹@rŒ   r‘   r”   Nr•   r”   rJ   rH   r   r   ±   sQ   † ÙØGÙÐ.¸#Ñ>ð
Øð
à#àØ#Ø#ñ ðð Ø ò
ñ€Mð  ƒGrJ   r   c                   ó¦   • \ rS rSr\" S\" \SS90 \ESSSSS	.0S
SS.ES9r\" S\" \SSSS90 \ESSSS\	" S5      \	" S5      S	.0S
SSS.ES9r
\rSrg)r   éÅ   z6https://download.pytorch.org/models/vgg16-397923af.pthr†   r‡   i(+?r‰   gÙÎ÷SãåQ@gœÄ °r˜V@rŠ   çq=
×£ð.@gî|?5^~€@rŒ   r‘   zIhttps://download.pytorch.org/models/vgg16_features-amdegroot-88682ab5.pth)g;pÎˆÒÞÞ?gÌ°�N]Ý?g|
€ñÚ?)çp?r¥   r¥   )rˆ   ÚmeanÚstdNz5https://github.com/amdegroot/ssd.pytorch#training-ssdÚnang#Ûù~j~€@a`  
                These weights can't be used for classification because they are missing values in the `classifier`
                module. Only the `features` module has valid values and can be used for feature extraction. The weights
                were trained using the original input standardization method as described in the paper.
            )r�   rx   r‚   rŽ   r�   r�   rƒ   r”   )rQ   rR   rS   rT   r   r   r	   r–   r—   rX   ÚIMAGENET1K_FEATURESr˜   rZ   r”   rJ   rH   r   r   Å   s¸   † ÙØDÙÐ.¸#Ñ>ð
Øð
à#àØ#Ø#ñ ðð Ø!ò
ñ€Mñ  "àWÙØØØ,Ø7ñ	
ð
Øð
à#ØØMàÙ" 5›\Ù" 5›\ñ ðð Ø!ðò
ñÐð: ƒGrJ   r   c            
       óN   • \ rS rSr\" S\" \SS90 \ESSSSS	.0S
SS.ES9r\r	Sr
g)r   éö   z9https://download.pytorch.org/models/vgg16_bn-6c64b313.pthr†   r‡   i(L?r‰   g×£p=
WR@g/Ý$áV@rŠ   r¤   g°rh‘í~€@rŒ   r‘   r”   Nr•   r”   rJ   rH   r   r   ö   r›   rJ   r   c            
       óN   • \ rS rSr\" S\" \SS90 \ESSSSS	.0S
SS.ES9r\r	Sr
g)r   i
  z6https://download.pytorch.org/models/vgg19-dcbb9e9d.pthr†   r‡   i(0�r‰   gòÒMbR@gòÒMb¸V@rŠ   çoƒÀÊ¡3@gÅ °rh �@rŒ   r‘   r”   Nr•   r”   rJ   rH   r   r   
  rŸ   rJ   r   c            
       óN   • \ rS rSr\" S\" \SS90 \ESSSSS	.0S
SS.ES9r\r	Sr
g)r   i  z9https://download.pytorch.org/models/vgg19_bn-c79401a0.pthr†   r‡   i([�r‰   gË¡E¶ó�R@gÙÎ÷SãõV@rŠ   r­   g /Ý$!�@rŒ   r‘   r”   Nr•   r”   rJ   rH   r   r     sQ   † ÙØGÙÐ.¸#Ñ>ð
Øð
à#àØ#Ø#ñ ðð Ø!ò
ñ€Mð  ƒGrJ   r   Ú
pretrained)rt   T)rt   ru   c                 óH   • [         R                  U 5      n [        SSX40 UD6$ )a4  VGG-11 from `Very Deep Convolutional Networks for Large-Scale Image Recognition <https://arxiv.org/abs/1409.1556>`__.

Args:
    weights (:class:`~torchvision.models.VGG11_Weights`, optional): The
        pretrained weights to use. See
        :class:`~torchvision.models.VGG11_Weights` below for
        more details, and possible values. By default, no pre-trained
        weights are used.
    progress (bool, optional): If True, displays a progress bar of the
        download to stderr. Default is True.
    **kwargs: parameters passed to the ``torchvision.models.vgg.VGG``
        base class. Please refer to the `source code
        <https://github.com/pytorch/vision/blob/main/torchvision/models/vgg.py>`_
        for more details about this class.

.. autoclass:: torchvision.models.VGG11_Weights
    :members:
ro   F)r   Úverifyr   ©rt   ru   rv   s      rH   r   r   2  ó(   € ô* ×"Ñ" 7Ó+€Gä��U˜GÑ8°Ñ8Ð8rJ   c                 óH   • [         R                  U 5      n [        SSX40 UD6$ )a@  VGG-11-BN from `Very Deep Convolutional Networks for Large-Scale Image Recognition <https://arxiv.org/abs/1409.1556>`__.

Args:
    weights (:class:`~torchvision.models.VGG11_BN_Weights`, optional): The
        pretrained weights to use. See
        :class:`~torchvision.models.VGG11_BN_Weights` below for
        more details, and possible values. By default, no pre-trained
        weights are used.
    progress (bool, optional): If True, displays a progress bar of the
        download to stderr. Default is True.
    **kwargs: parameters passed to the ``torchvision.models.vgg.VGG``
        base class. Please refer to the `source code
        <https://github.com/pytorch/vision/blob/main/torchvision/models/vgg.py>`_
        for more details about this class.

.. autoclass:: torchvision.models.VGG11_BN_Weights
    :members:
ro   T)r   r±   r   r²   s      rH   r   r   L  ó(   € ô* ×%Ñ% gÓ.€Gä��T˜7Ñ7°Ñ7Ð7rJ   c                 óH   • [         R                  U 5      n [        SSX40 UD6$ )a4  VGG-13 from `Very Deep Convolutional Networks for Large-Scale Image Recognition <https://arxiv.org/abs/1409.1556>`__.

Args:
    weights (:class:`~torchvision.models.VGG13_Weights`, optional): The
        pretrained weights to use. See
        :class:`~torchvision.models.VGG13_Weights` below for
        more details, and possible values. By default, no pre-trained
        weights are used.
    progress (bool, optional): If True, displays a progress bar of the
        download to stderr. Default is True.
    **kwargs: parameters passed to the ``torchvision.models.vgg.VGG``
        base class. Please refer to the `source code
        <https://github.com/pytorch/vision/blob/main/torchvision/models/vgg.py>`_
        for more details about this class.

.. autoclass:: torchvision.models.VGG13_Weights
    :members:
rp   F)r   r±   r   r²   s      rH   r   r   f  r³   rJ   c                 óH   • [         R                  U 5      n [        SSX40 UD6$ )a@  VGG-13-BN from `Very Deep Convolutional Networks for Large-Scale Image Recognition <https://arxiv.org/abs/1409.1556>`__.

Args:
    weights (:class:`~torchvision.models.VGG13_BN_Weights`, optional): The
        pretrained weights to use. See
        :class:`~torchvision.models.VGG13_BN_Weights` below for
        more details, and possible values. By default, no pre-trained
        weights are used.
    progress (bool, optional): If True, displays a progress bar of the
        download to stderr. Default is True.
    **kwargs: parameters passed to the ``torchvision.models.vgg.VGG``
        base class. Please refer to the `source code
        <https://github.com/pytorch/vision/blob/main/torchvision/models/vgg.py>`_
        for more details about this class.

.. autoclass:: torchvision.models.VGG13_BN_Weights
    :members:
rp   T)r   r±   r   r²   s      rH   r   r   €  rµ   rJ   c                 óH   • [         R                  U 5      n [        SSX40 UD6$ )a4  VGG-16 from `Very Deep Convolutional Networks for Large-Scale Image Recognition <https://arxiv.org/abs/1409.1556>`__.

Args:
    weights (:class:`~torchvision.models.VGG16_Weights`, optional): The
        pretrained weights to use. See
        :class:`~torchvision.models.VGG16_Weights` below for
        more details, and possible values. By default, no pre-trained
        weights are used.
    progress (bool, optional): If True, displays a progress bar of the
        download to stderr. Default is True.
    **kwargs: parameters passed to the ``torchvision.models.vgg.VGG``
        base class. Please refer to the `source code
        <https://github.com/pytorch/vision/blob/main/torchvision/models/vgg.py>`_
        for more details about this class.

.. autoclass:: torchvision.models.VGG16_Weights
    :members:
rq   F)r   r±   r   r²   s      rH   r   r   š  r³   rJ   c                 óH   • [         R                  U 5      n [        SSX40 UD6$ )a@  VGG-16-BN from `Very Deep Convolutional Networks for Large-Scale Image Recognition <https://arxiv.org/abs/1409.1556>`__.

Args:
    weights (:class:`~torchvision.models.VGG16_BN_Weights`, optional): The
        pretrained weights to use. See
        :class:`~torchvision.models.VGG16_BN_Weights` below for
        more details, and possible values. By default, no pre-trained
        weights are used.
    progress (bool, optional): If True, displays a progress bar of the
        download to stderr. Default is True.
    **kwargs: parameters passed to the ``torchvision.models.vgg.VGG``
        base class. Please refer to the `source code
        <https://github.com/pytorch/vision/blob/main/torchvision/models/vgg.py>`_
        for more details about this class.

.. autoclass:: torchvision.models.VGG16_BN_Weights
    :members:
rq   T)r   r±   r   r²   s      rH   r    r    ´  rµ   rJ   c                 óH   • [         R                  U 5      n [        SSX40 UD6$ )a4  VGG-19 from `Very Deep Convolutional Networks for Large-Scale Image Recognition <https://arxiv.org/abs/1409.1556>`__.

Args:
    weights (:class:`~torchvision.models.VGG19_Weights`, optional): The
        pretrained weights to use. See
        :class:`~torchvision.models.VGG19_Weights` below for
        more details, and possible values. By default, no pre-trained
        weights are used.
    progress (bool, optional): If True, displays a progress bar of the
        download to stderr. Default is True.
    **kwargs: parameters passed to the ``torchvision.models.vgg.VGG``
        base class. Please refer to the `source code
        <https://github.com/pytorch/vision/blob/main/torchvision/models/vgg.py>`_
        for more details about this class.

.. autoclass:: torchvision.models.VGG19_Weights
    :members:
rr   F)r   r±   r   r²   s      rH   r!   r!   Î  r³   rJ   c                 óH   • [         R                  U 5      n [        SSX40 UD6$ )a@  VGG-19_BN from `Very Deep Convolutional Networks for Large-Scale Image Recognition <https://arxiv.org/abs/1409.1556>`__.

Args:
    weights (:class:`~torchvision.models.VGG19_BN_Weights`, optional): The
        pretrained weights to use. See
        :class:`~torchvision.models.VGG19_BN_Weights` below for
        more details, and possible values. By default, no pre-trained
        weights are used.
    progress (bool, optional): If True, displays a progress bar of the
        download to stderr. Default is True.
    **kwargs: parameters passed to the ``torchvision.models.vgg.VGG``
        base class. Please refer to the `source code
        <https://github.com/pytorch/vision/blob/main/torchvision/models/vgg.py>`_
        for more details about this class.

.. autoclass:: torchvision.models.VGG19_BN_Weights
    :members:
rr   T)r   r±   r   r²   s      rH   r"   r"   è  rµ   rJ   )F)6Ú	functoolsr   Útypingr   r   r   r   rM   Útorch.nnr3   Útransforms._presetsr	   Úutilsr
   Ú_apir   r   r   Ú_metar   Ú_utilsr   r   Ú__all__rU   r   ÚlistÚstrrV   rW   r6   rj   rs   ÚdictÚ__annotations__r   r–   r   r   r   r   r   r   r   r   r—   r   r   r   r   r   r    r!   r"   r”   rJ   rH   Ú<module>rÉ      s  ðÞ ß -Ó -ã Ý å 5Ý 'ß 6Ñ 6Ý 'ß Bò€ô*#ˆ"�)‰)ô #ñL"�T˜%  S ™/Ñ*ð "¸ð "ÈÏÉõ "ò$ 
JÚ	RÚ	aÚ	pñ	*€€dˆ3��U˜3 ˜8‘_Ñ%Ð%Ñ&ó ðˆcð ˜tð ¨h°{Ñ.Cð Ètð Ð_bð Ðgjô ð Ø&ØeØañ	€ô�Kô ô(�{ô ô(�Kô ô(�{ô ô(.�Kô .ôb�{ô ô(�Kô ô(�{ô ñ( ÓÙ ,°×0KÑ0KÐ!LÑMØ04Àtò 9�h˜}Ñ-ð 9Àð 9ÐWZð 9Ð_bô 9ó Nó ð9ñ0 ÓÙ ,Ð0@×0NÑ0NÐ!OÑPØ6:ÈTò 8˜Ð"2Ñ3ð 8Àdð 8Ð]`ð 8Ðehô 8ó Qó ð8ñ0 ÓÙ ,°×0KÑ0KÐ!LÑMØ04Àtò 9�h˜}Ñ-ð 9Àð 9ÐWZð 9Ð_bô 9ó Nó ð9ñ0 ÓÙ ,Ð0@×0NÑ0NÐ!OÑPØ6:ÈTò 8˜Ð"2Ñ3ð 8Àdð 8Ð]`ð 8Ðehô 8ó Qó ð8ñ0 ÓÙ ,°×0KÑ0KÐ!LÑMØ04Àtò 9�h˜}Ñ-ð 9Àð 9ÐWZð 9Ð_bô 9ó Nó ð9ñ0 ÓÙ ,Ð0@×0NÑ0NÐ!OÑPØ6:ÈTò 8˜Ð"2Ñ3ð 8Àdð 8Ð]`ð 8Ðehô 8ó Qó ð8ñ0 ÓÙ ,°×0KÑ0KÐ!LÑMØ04Àtò 9�h˜}Ñ-ð 9Àð 9ÐWZð 9Ð_bô 9ó Nó ð9ñ0 ÓÙ ,Ð0@×0NÑ0NÐ!OÑPØ6:ÈTò 8˜Ð"2Ñ3ð 8Àdð 8Ð]`ð 8Ðehô 8ó Qó ñ8rJ   