U
    <jgK                     @   s  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 dddddddddddddddddgZG dd dejZdDeeeef  eejddd Z d!d"d#d"d$d$d"d%d%d"d%d%d"gd!d!d"d#d#d"d$d$d"d%d%d"d%d%d"gd!d!d"d#d#d"d$d$d$d"d%d%d%d"d%d%d%d"gd!d!d"d#d#d"d$d$d$d$d"d%d%d%d%d"d%d%d%d%d"gd&Z!eeeeeef  f e"d'< eeee eeed(d)d*Z#d+ed,d-d.Z$G d/d deZ%G d0d deZ&G d1d deZ'G d2d deZ(G d3d deZ)G d4d deZ*G d5d deZ+G d6d deZ,e ed7e%j-fd8dd9d:ee% eeed;d<dZ.e ed7e&j-fd8dd9d:ee& eeed;d=dZ/e ed7e'j-fd8dd9d:ee' eeed;d>dZ0e ed7e(j-fd8dd9d:ee( eeed;d?dZ1e ed7e)j-fd8dd9d:ee) eeed;d@dZ2e ed7e*j-fd8dd9d:ee* eeed;dAdZ3e ed7e+j-fd8dd9d:ee+ eeed;dBdZ4e ed7e,j-fd8dd9d:ee, eeed;dCdZ5dS )E    )partial)AnycastDictListOptionalUnionN   )ImageClassification)_log_api_usage_once   )register_modelWeightsWeightsEnum)_IMAGENET_CATEGORIES)_ovewrite_named_paramhandle_legacy_interfaceVGGVGG11_WeightsVGG11_BN_WeightsVGG13_WeightsVGG13_BN_WeightsVGG16_WeightsVGG16_BN_WeightsVGG19_WeightsVGG19_BN_Weightsvgg11vgg11_bnvgg13vgg13_bnvgg16vgg16_bnvgg19vgg19_bnc                       sB   e Zd Zdejeeedd fddZe	j
e	j
dd	d
Z  ZS )r     T      ?N)featuresnum_classesinit_weightsdropoutreturnc                    s   t    t|  || _td| _ttddt	dtj
|dtddt	dtj
|dtd|| _|r|  D ]}t|tjrtjj|jddd |jd k	rtj|jd	 q~t|tjrtj|jd
 tj|jd	 q~t|tjr~tj|jd	d tj|jd	 q~d S )N)   r+   i b  i   T)pZfan_outZrelu)modeZnonlinearityr   r   g{Gz?)super__init__r   r&   nnZAdaptiveAvgPool2davgpool
SequentialZLinearReLUZDropout
classifiermodules
isinstanceConv2dinitZkaiming_normal_ZweightZbiasZ	constant_BatchNorm2dZnormal_)selfr&   r'   r(   r)   m	__class__ :/tmp/pip-unpacked-wheel-xh8d94dr/torchvision/models/vgg.pyr/   $   s2    





	
zVGG.__init__)xr*   c                 C   s.   |  |}| |}t|d}| |}|S )Nr   )r&   r1   torchflattenr4   )r:   r@   r>   r>   r?   forwardA   s
    


zVGG.forward)r$   Tr%   )__name__
__module____qualname__r0   Moduleintboolfloatr/   rA   ZTensorrC   __classcell__r>   r>   r<   r?   r   #   s           F)cfg
batch_normr*   c                 C   s   g }d}| D ]x}|dkr.|t jdddg7 }qtt|}t j||ddd}|rl||t |t jddg7 }n||t jddg7 }|}qt j| S )	N   Mr	   )kernel_sizeZstrider   )rP   paddingT)Zinplace)r0   Z	MaxPool2dr   rH   r7   r9   r3   r2   )rL   rM   ZlayersZin_channelsvZconv2dr>   r>   r?   make_layersI   s    
rS   @   rO         i   )ABDEcfgs)rL   rM   weightsprogresskwargsr*   c                 K   sl   |d k	r4d|d< |j d d k	r4t|dt|j d  ttt|  |df|}|d k	rh||j|dd |S )NFr(   
categoriesr'   )rM   T)r]   Z
check_hash)metar   lenr   rS   r[   Zload_state_dictZget_state_dict)rL   rM   r\   r]   r^   modelr>   r>   r?   _vggb   s    rc   )    rd   zUhttps://github.com/pytorch/vision/tree/main/references/classification#alexnet-and-vggzNThese weights were trained from scratch by using a simplified training recipe.)Zmin_sizer_   recipe_docsc                	   @   s>   e Zd Zedeeddedddddid	d
ddZeZdS )r   z6https://download.pytorch.org/models/vgg11-8a719046.pth   	crop_sizeihUImageNet-1KgzGAQ@gx&1(V@zacc@1zacc@5V-o@g=
ףp@
num_params_metrics_ops
_file_sizeurlZ
transformsr`   N	rD   rE   rF   r   r   r
   _COMMON_METAIMAGENET1K_V1DEFAULTr>   r>   r>   r?   r   u   s   
c                	   @   s>   e Zd Zedeeddedddddid	d
ddZeZdS )r   z9https://download.pytorch.org/models/vgg11_bn-6002323d.pthrg   rh   ijrj   gHzQ@gp=
sV@rk   rl   gjt@rm   rr   Nrt   r>   r>   r>   r?   r      s   
c                	   @   s>   e Zd Zedeeddedddddid	d
ddZeZdS )r   z6https://download.pytorch.org/models/vgg13-19584684.pthrg   rh   i(&rj   gZd{Q@g9vOV@rk   V-&@gQ@rm   rr   Nrt   r>   r>   r>   r?   r      s   
c                	   @   s>   e Zd Zedeeddedddddid	d
ddZeZdS )r   z9https://download.pytorch.org/models/vgg13_bn-abd245e5.pthrg   rh   i(=rj   g/$Q@g-V@rk   rx   g=
ףp@rm   rr   Nrt   r>   r>   r>   r?   r      s   
c                   @   s~   e Zd Zedeeddedddddid	d
ddZedeeddddeddddededdid	ddddZ	eZ
dS )r   z6https://download.pytorch.org/models/vgg16-397923af.pthrg   rh   i(+?rj   gSQ@g rV@rk   q=
ף.@g|?5^~@rm   rr   zIhttps://download.pytorch.org/models/vgg16_features-amdegroot-88682ab5.pth)g;pΈ?gN]?g|
?)p?rz   rz   )ri   ZmeanZstdNz5https://github.com/amdegroot/ssd.pytorch#training-ssdnang#~j~@a`  
                These weights can't be used for classification because they are missing values in the `classifier`
                module. Only the `features` module has valid values and can be used for feature extraction. The weights
                were trained using the original input standardization method as described in the paper.
            )rn   r_   re   ro   rp   rq   rf   )rD   rE   rF   r   r   r
   ru   rv   rJ   ZIMAGENET1K_FEATURESrw   r>   r>   r>   r?   r      sJ   
c                	   @   s>   e Zd Zedeeddedddddid	d
ddZeZdS )r   z9https://download.pytorch.org/models/vgg16_bn-6c64b313.pthrg   rh   i(L?rj   gףp=
WR@g/$V@rk   ry   grh~@rm   rr   Nrt   r>   r>   r>   r?   r      s   
c                	   @   s>   e Zd Zedeeddedddddid	d
ddZeZdS )r   z6https://download.pytorch.org/models/vgg19-dcbb9e9d.pthrg   rh   i(0rj   gMbR@gMbV@rk   oʡ3@g rh @rm   rr   Nrt   r>   r>   r>   r?   r   
  s   
c                	   @   s>   e Zd Zedeeddedddddid	d
ddZeZdS )r   z9https://download.pytorch.org/models/vgg19_bn-c79401a0.pthrg   rh   i([rj   gˡER@gSV@rk   r|   g/$!@rm   rr   Nrt   r>   r>   r>   r?   r     s   
Z
pretrained)r\   T)r\   r]   )r\   r]   r^   r*   c                 K   s   t | } tdd| |f|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:
    rW   F)r   verifyrc   r\   r]   r^   r>   r>   r?   r   2  s    
c                 K   s   t | } tdd| |f|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:
    rW   T)r   r}   rc   r~   r>   r>   r?   r   L  s    
c                 K   s   t | } tdd| |f|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:
    rX   F)r   r}   rc   r~   r>   r>   r?   r   f  s    
c                 K   s   t | } tdd| |f|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:
    rX   T)r   r}   rc   r~   r>   r>   r?   r     s    
c                 K   s   t | } tdd| |f|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:
    rY   F)r   r}   rc   r~   r>   r>   r?   r      s    
c                 K   s   t | } tdd| |f|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:
    rY   T)r   r}   rc   r~   r>   r>   r?   r!     s    
c                 K   s   t | } tdd| |f|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:
    rZ   F)r   r}   rc   r~   r>   r>   r?   r"     s    
c                 K   s   t | } tdd| |f|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:
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