§
    ù²ÅjM  ã                   óX  — U d dl mZ d dlmZmZmZ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 ddlmZmZmZ dd	lmZ dd
lmZmZ g d¢Z G d„ dej        ¦  «        Zd=deeeef                  dedej        fd„Z g d¢g d¢g d¢g d¢dœZ!eeeeeef                  f         e"d<   dededee         dededefd„Z#deddd œZ$ G d!„ d"e¦  «        Z% G d#„ d$e¦  «        Z& G d%„ d&e¦  «        Z' G d'„ d(e¦  «        Z( G d)„ d*e¦  «        Z) G d+„ d,e¦  «        Z* G d-„ d.e¦  «        Z+ G d/„ d0e¦  «        Z, e¦   «          ed1e%j-        f¬2¦  «        dd3d4œdee%         dededefd5„¦   «         ¦   «         Z. e¦   «          ed1e&j-        f¬2¦  «        dd3d4œdee&         dededefd6„¦   «         ¦   «         Z/ e¦   «          ed1e'j-        f¬2¦  «        dd3d4œdee'         dededefd7„¦   «         ¦   «         Z0 e¦   «          ed1e(j-        f¬2¦  «        dd3d4œdee(         dededefd8„¦   «         ¦   «         Z1 e¦   «          ed1e)j-        f¬2¦  «        dd3d4œdee)         dededefd9„¦   «         ¦   «         Z2 e¦   «          ed1e*j-        f¬2¦  «        dd3d4œdee*         dededefd:„¦   «         ¦   «         Z3 e¦   «          ed1e+j-        f¬2¦  «        dd3d4œdee+         dededefd;„¦   «         ¦   «         Z4 e¦   «          ed1e,j-        f¬2¦  «        dd3d4œdee,         dededefd<„¦   «         ¦   «         Z5dS )>é    )Úpartial)ÚAnyÚcastÚDictÚListÚ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                   óf   ‡ — e Zd Z	 ddej        dedededd	f
ˆ fd
„Zde	j
        de	j
        fd„Zˆ xZS )r   éè  Tç      à?ÚfeaturesÚnum_classesÚinit_weightsÚdropoutÚreturnNc                 ó–  •— t          ¦   «                              ¦   «          t          | ¦  «         || _        t	          j        d¦  «        | _        t	          j        t	          j        dd¦  «        t	          j	        d¦  «        t	          j
        |¬¦  «        t	          j        dd¦  «        t	          j	        d¦  «        t	          j
        |¬¦  «        t	          j        d|¦  «        ¦  «        | _        |�rQ|                      ¦   «         D �]=}t          |t          j        ¦  «        rTt          j                             |j        dd¬¦  «         |j        �%t          j                             |j        d	¦  «         Œqt          |t          j        ¦  «        rKt          j                             |j        d
¦  «         t          j                             |j        d	¦  «         ŒÖt          |t          j        ¦  «        rKt          j                             |j        d	d¦  «         t          j                             |j        d	¦  «         �Œ=d S d S )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         €úGC:\Projects\Historical\venv\Lib\site-packages\torchvision/models/vgg.pyr5   zVGG.__init__$   sØ  ø€ õ 	‰Œ×ÒÑÔÐÝ˜DÑ!Ô!Ð!Ø ˆŒÝÔ+¨FÑ3Ô3ˆŒÝœ-ÝŒI�k 4Ñ(Ô(ÝŒG�D‰MŒMÝŒJ˜Ð!Ñ!Ô!ÝŒI�d˜DÑ!Ô!ÝŒG�D‰MŒMÝŒJ˜Ð!Ñ!Ô!ÝŒI�d˜KÑ(Ô(ñ
ô 
ˆŒð ñ 	1Ø—\’\‘^”^ð 
1ñ 
1�Ý˜a¥¤Ñ+Ô+ð 	1Ý”G×+Ò+¨A¬H¸9ÐSYÐ+ÑZÔZÐZØ”vÐ)Ýœ×)Ò)¨!¬&°!Ñ4Ô4Ð4øÝ ¥2¤>Ñ2Ô2ð 1Ý”G×%Ò% a¤h°Ñ2Ô2Ð2Ý”G×%Ò% a¤f¨aÑ0Ô0Ð0Ð0Ý ¥2¤9Ñ-Ô-ð 1Ý”G—O’O A¤H¨a°Ñ6Ô6Ð6Ý”G×%Ò% a¤f¨aÑ0Ô0Ð0ùð	1ð 	1ð
1ð 
1ó    Úxc                 ó®   — |                       |¦  «        }|                      |¦  «        }t          j        |d¦  «        }|                      |¦  «        }|S )Nr   )r(   r8   ÚtorchÚflattenr=   )rH   rM   s     rK   ÚforwardzVGG.forwardA   sI   € Ø�MŠM˜!ÑÔˆØ�LŠL˜‰OŒOˆÝŒM˜!˜QÑÔˆØ�OŠO˜AÑÔˆØˆrL   )r&   Tr'   )Ú__name__Ú
__module__Ú__qualname__r6   ÚModuleÚintÚboolÚfloatr5   rO   ÚTensorrQ   Ú__classcell__)rJ   s   @rK   r   r   #   s•   ø€ € € € € àhkð1ð 1Øœ	ð1Ø03ð1ØJNð1Ø`eð1à	ð1ð 1ð 1ð 1ð 1ð 1ð:˜œð ¨%¬,ð ð ð ð ð ð ð ð rL   r   FÚcfgÚ
batch_normr,   c                 ód  — g }d}| D ]œ}|dk    r|t          j        dd¬¦  «        gz  }Œ#t          t          |¦  «        }t          j        ||dd¬¦  «        }|r.||t          j        |¦  «        t          j        d¬¦  «        gz  }n||t          j        d¬¦  «        gz  }|}Œ�t          j        |Ž S )	Né   ÚMr
   )Úkernel_sizeÚstrider   )r`   ÚpaddingT)Úinplace)r6   Ú	MaxPool2dr   rV   r@   rF   r;   r9   )r[   r\   ÚlayersÚin_channelsÚvÚconv2ds         rK   Úmake_layersri   I   sÉ   € Ø €FØ€KØð 
ð 
ˆØ�Š8ˆ8Ø•r”|°¸!Ð<Ñ<Ô<Ð=Ñ=ˆFˆFå•S˜!‘”ˆAÝ”Y˜{¨A¸1ÀaÐHÑHÔHˆFØð :Ø˜6¥2¤>°!Ñ#4Ô#4µb´gÀdÐ6KÑ6KÔ6KÐLÑL��à˜6¥2¤7°4Ð#8Ñ#8Ô#8Ð9Ñ9�ØˆKˆKÝŒ=˜&Ð!Ð!rL   )é@   r_   é€   r_   é   rl   r_   é   rm   r_   rm   rm   r_   )rj   rj   r_   rk   rk   r_   rl   rl   r_   rm   rm   r_   rm   rm   r_   )rj   rj   r_   rk   rk   r_   rl   rl   rl   r_   rm   rm   rm   r_   rm   rm   rm   r_   )rj   rj   r_   rk   rk   r_   rl   rl   rl   rl   r_   rm   rm   rm   rm   r_   rm   rm   rm   rm   r_   )ÚAÚBÚDÚEÚcfgsÚweightsÚprogressÚkwargsc                 ó&  — |�;d|d<   |j         d         �)t          |dt          |j         d         ¦  «        ¦  «         t          t	          t
          |          |¬¦  «        fi |¤Ž}|�*|                     |                     |d¬¦  «        ¦  «         |S )NFr*   Ú
categoriesr)   )r\   T)rt   Ú
check_hash)Úmetar   Úlenr   ri   rr   Úload_state_dictÚget_state_dict)r[   r\   rs   rt   ru   Úmodels         rK   Ú_vggr~   b   s™   € ØÐØ!&ˆˆ~ÑØŒ<˜Ô%Ð1Ý! &¨-½¸W¼\È,Ô=WÑ9XÔ9XÑYÔYÐYÝ•�D œI°*Ð=Ñ=Ô=ÐHÐHÀÐHÐH€EØÐØ×Ò˜g×4Ò4¸hÐSWÐ4ÑXÔXÑYÔYÐYØ€LrL   )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_sizerw   ÚrecipeÚ_docsc            
       ó`   — e Zd Z ed eed¬¦  «        i e¥dddddœid	d
dœ¥¬¦  «        ZeZdS )r   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
transformsry   N©	rR   rS   rT   r   r   r   Ú_COMMON_METAÚIMAGENET1K_V1ÚDEFAULT© rL   rK   r   r   u   s€   € € € € € Ø�GØDØ�7Ð.¸#Ð>Ñ>Ô>ð
Øð
à#àØ#Ø#ð ð  ðð Ø ð
ð 
ð 
ðñ ô €Mð  €G€G€GrL   r   c            
       ó`   — e Zd Z ed eed¬¦  «        i e¥dddddœid	d
dœ¥¬¦  «        ZeZdS )r   z9https://download.pytorch.org/models/vgg11_bn-6002323d.pthr„   r…   ièjër‡   gHáz®—Q@g¤p=
×sV@rˆ   r‰   gj¼t“®@rŠ   r�   Nr’   r–   rL   rK   r   r   ‰   ó€   € € € € € Ø�GØGØ�7Ð.¸#Ð>Ñ>Ô>ð
Øð
à#àØ#Ø#ð ð  ðð Ø!ð
ð 
ð 
ðñ ô €Mð  €G€G€GrL   r   c            
       ó`   — e Zd Z ed eed¬¦  «        i e¥dddddœid	d
dœ¥¬¦  «        ZeZdS )r   z6https://download.pytorch.org/models/vgg13-19584684.pthr„   r…   i(&îr‡   g¬Zd{Q@g9´Èv¾OV@rˆ   çV-²�&@g…ëQ¸¸@rŠ   r�   Nr’   r–   rL   rK   r   r   �   ó€   € € € € € Ø�GØDØ�7Ð.¸#Ð>Ñ>Ô>ð
Øð
à#àØ#Ø#ð ð  ðð Ø!ð
ð 
ð 
ðñ ô €Mð  €G€G€GrL   r   c            
       ó`   — e Zd Z ed eed¬¦  «        i e¥dddddœid	d
dœ¥¬¦  «        ZeZdS )r   z9https://download.pytorch.org/models/vgg13_bn-abd245e5.pthr„   r…   i(=îr‡   g/Ý$�åQ@g-²�ï—V@rˆ   rš   g=
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Øð
à#àØ#Ø#ð ð  ðð Ø ð
ð 
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ðñ ô €Mð  €G€G€GrL   r   c                   óÜ   — e Zd Z ed eed¬¦  «        i e¥dddddœid	d
dœ¥¬¦  «        Z ed eeddd¬¦  «        i e¥dddd ed¦  «         ed¦  «        dœid	dddœ¥¬¦  «        Z	eZ
dS )r   z6https://download.pytorch.org/models/vgg16-397923af.pthr„   r…   i(+?r‡   gÙÎ÷SãåQ@gœÄ °r˜V@rˆ   çq=
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€ñÚ?)çp?rŸ   rŸ   )r†   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‹   rw   r�   rŒ   r�   rŽ   r‚   )rR   rS   rT   r   r   r   r“   r”   rX   ÚIMAGENET1K_FEATURESr•   r–   rL   rK   r   r   Å   s  € € € € € Ø�GØDØ�7Ð.¸#Ð>Ñ>Ô>ð
Øð
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ð 
ð 
ðñ ô €Mð  "˜'àWØ�7ØØØ,Ø7ð	
ñ 
ô 
ð
Øð
à#ØØMàØ"˜U 5™\œ\Ø"˜U 5™\œ\ð ð  ðð Ø!ðð
ð 
ð 
ðñ ô Ðð: €G€G€GrL   r   c            
       ó`   — e Zd Z ed eed¬¦  «        i e¥dddddœid	d
dœ¥¬¦  «        ZeZdS )r   z9https://download.pytorch.org/models/vgg16_bn-6c64b313.pthr„   r…   i(L?r‡   g×£p=
WR@g/Ý$áV@rˆ   rž   g°rh‘í~€@rŠ   r�   Nr’   r–   rL   rK   r   r   ö   r˜   rL   r   c            
       ó`   — e Zd Z ed eed¬¦  «        i e¥dddddœid	d
dœ¥¬¦  «        ZeZdS )r   z6https://download.pytorch.org/models/vgg19-dcbb9e9d.pthr„   r…   i(0�r‡   gòÒMbR@gòÒMb¸V@rˆ   çoƒÀÊ¡3@gÅ °rh �@rŠ   r�   Nr’   r–   rL   rK   r   r   
  r›   rL   r   c            
       ó`   — e Zd Z ed eed¬¦  «        i e¥dddddœid	d
dœ¥¬¦  «        ZeZdS )r   z9https://download.pytorch.org/models/vgg19_bn-c79401a0.pthr„   r…   i([�r‡   gË¡E¶ó�R@gÙÎ÷SãõV@rˆ   r¦   g /Ý$!�@rŠ   r�   Nr’   r–   rL   rK   r   r     s€   € € € € € Ø�GØGØ�7Ð.¸#Ð>Ñ>Ô>ð
Øð
à#àØ#Ø#ð ð  ðð Ø!ð
ð 
ð 
ðñ ô €Mð  €G€G€GrL   r   Ú
pretrained)rs   T)rs   rt   c                 óV   — t                                | ¦  «        } t          dd| |fi |¤ŽS )ap  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:
    rn   F)r   Úverifyr~   ©rs   rt   ru   s      rK   r   r   2  ó3   € õ* ×"Ò" 7Ñ+Ô+€Gå��U˜G XÐ8Ð8°Ð8Ð8Ð8rL   c                 óV   — t                                | ¦  «        } t          dd| |fi |¤ŽS )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:
    rn   T)r   rª   r~   r«   s      rK   r   r   L  ó3   € õ* ×%Ò% gÑ.Ô.€Gå��T˜7 HÐ7Ð7°Ð7Ð7Ð7rL   c                 óV   — t                                | ¦  «        } t          dd| |fi |¤ŽS )ap  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:
    ro   F)r   rª   r~   r«   s      rK   r   r   f  r¬   rL   c                 óV   — t                                | ¦  «        } t          dd| |fi |¤ŽS )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:
    ro   T)r   rª   r~   r«   s      rK   r    r    €  r®   rL   c                 óV   — t                                | ¦  «        } t          dd| |fi |¤ŽS )ap  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:
    rp   F)r   rª   r~   r«   s      rK   r!   r!   š  r¬   rL   c                 óV   — t                                | ¦  «        } t          dd| |fi |¤ŽS )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:
    rp   T)r   rª   r~   r«   s      rK   r"   r"   ´  r®   rL   c                 óV   — t                                | ¦  «        } t          dd| |fi |¤ŽS )ap  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:
    rq   F)r   rª   r~   r«   s      rK   r#   r#   Î  r¬   rL   c                 óV   — t                                | ¦  «        } t          dd| |fi |¤ŽS )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:
    rq   T)r   rª   r~   r«   s      rK   r$   r$   è  r®   rL   )F)6Ú	functoolsr   Útypingr   r   r   r   r   r	   rO   Útorch.nnr6   Útransforms._presetsr   Úutilsr   Ú_apir   r   r   Ú_metar   Ú_utilsr   r   Ú__all__rU   r   ÚstrrV   rW   r9   ri   rr   Ú__annotations__r~   r“   r   r   r   r   r   r   r   r   r”   r   r   r   r    r!   r"   r#   r$   r–   rL   rK   ú<module>rÀ      sQ  ðØ Ð Ð Ð Ð Ð Ð Ø 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9Ð 9à €€€Ø Ð Ð Ð Ð Ð à 5Ð 5Ð 5Ð 5Ð 5Ð 5Ø 'Ð 'Ð 'Ð 'Ð 'Ð 'Ø 6Ð 6Ð 6Ð 6Ð 6Ð 6Ð 6Ð 6Ð 6Ð 6Ø 'Ð 'Ð 'Ð 'Ð 'Ð 'Ø BÐ BÐ BÐ BÐ BÐ BÐ BÐ Bðð ð €ð*#ð #ð #ð #ð #ˆ"Œ)ñ #ô #ð #ðL"ð "�T˜%  S œ/Ô*ð "¸ð "ÈÌð "ð "ð "ð "ð$ 
JÐ	IÐ	IØ	RÐ	RÐ	RØ	aÐ	aÐ	aØ	pÐ	pÐ	pð	*ð *€€dˆ3��U˜3 ˜8”_Ô%Ð%Ô&ð ð ñ ðˆcð ˜tð ¨h°{Ô.Cð Ètð Ð_bð Ðgjð ð ð ð ð Ø&ØeØað	ð €ðð ð ð ð �Kñ ô ð ð(ð ð ð ð �{ñ ô ð ð(ð ð ð ð �Kñ ô ð ð(ð ð ð ð �{ñ ô ð ð(.ð .ð .ð .ð .�Kñ .ô .ð .ðbð ð ð ð �{ñ ô ð ð(ð ð ð ð �Kñ ô ð ð(ð ð ð ð �{ñ ô ð ð( €ÑÔØÐ ,°Ô0KÐ!LÐMÑMÔMØ04Àtð 9ð 9ð 9�h˜}Ô-ð 9Àð 9ÐWZð 9Ð_bð 9ð 9ð 9ñ NÔMñ Ôð9ð0 €ÑÔØÐ ,Ð0@Ô0NÐ!OÐPÑPÔPØ6:ÈTð 8ð 8ð 8˜Ð"2Ô3ð 8Àdð 8Ð]`ð 8Ðehð 8ð 8ð 8ñ QÔPñ Ôð8ð0 €ÑÔØÐ ,°Ô0KÐ!LÐMÑMÔMØ04Àtð 9ð 9ð 9�h˜}Ô-ð 9Àð 9ÐWZð 9Ð_bð 9ð 9ð 9ñ NÔMñ Ôð9ð0 €ÑÔØÐ ,Ð0@Ô0NÐ!OÐPÑPÔPØ6:ÈTð 8ð 8ð 8˜Ð"2Ô3ð 8Àdð 8Ð]`ð 8Ðehð 8ð 8ð 8ñ QÔPñ Ôð8ð0 €ÑÔØÐ ,°Ô0KÐ!LÐMÑMÔMØ04Àtð 9ð 9ð 9�h˜}Ô-ð 9Àð 9ÐWZð 9Ð_bð 9ð 9ð 9ñ NÔMñ Ôð9ð0 €ÑÔØÐ ,Ð0@Ô0NÐ!OÐPÑPÔPØ6:ÈTð 8ð 8ð 8˜Ð"2Ô3ð 8Àdð 8Ð]`ð 8Ðehð 8ð 8ð 8ñ QÔPñ Ôð8ð0 €ÑÔØÐ ,°Ô0KÐ!LÐMÑMÔMØ04Àtð 9ð 9ð 9�h˜}Ô-ð 9Àð 9ÐWZð 9Ð_bð 9ð 9ð 9ñ NÔMñ Ôð9ð0 €ÑÔØÐ ,Ð0@Ô0NÐ!OÐPÑPÔPØ6:ÈTð 8ð 8ð 8˜Ð"2Ô3ð 8Àdð 8Ð]`ð 8Ðehð 8ð 8ð 8ñ QÔPñ Ôð8ð 8ð 8rL   