§
    ù²Åj|  ã                   óÄ   — d dl Z d dlZ d dl mZmZ d dlmZ d dlmZ ddlm	Z	 ddl
mZmZ e j        j        	 dd
ededededef
d„¦   «         Z G d„ dej        ¦  «        ZdS )é    N)ÚnnÚTensor)Ú_pair)Ú_assert_has_opsé   )Ú_log_api_usage_onceé   )Úcheck_roi_boxes_shapeÚconvert_boxes_to_roi_formatç      ð?ÚinputÚboxesÚoutput_sizeÚspatial_scaleÚreturnc                 óÂ  — t           j                             ¦   «         s2t           j                             ¦   «         st	          t
          ¦  «         t          ¦   «          t          |¦  «         |}t          |¦  «        }t          |t           j
        ¦  «        st          |¦  «        }t           j        j                             | |||d         |d         ¦  «        \  }}|S )aŸ  
    Performs Position-Sensitive Region of Interest (RoI) Pool operator
    described in R-FCN

    Args:
        input (Tensor[N, C, H, W]): The input tensor, i.e. a batch with ``N`` elements. Each element
            contains ``C`` feature maps of dimensions ``H x W``.
        boxes (Tensor[K, 5] or List[Tensor[L, 4]]): the box coordinates in (x1, y1, x2, y2)
            format where the regions will be taken from.
            The coordinate must satisfy ``0 <= x1 < x2`` and ``0 <= y1 < y2``.
            If a single Tensor is passed, then the first column should
            contain the index of the corresponding element in the batch, i.e. a number in ``[0, N - 1]``.
            If a list of Tensors is passed, then each Tensor will correspond to the boxes for an element i
            in the batch.
        output_size (int or Tuple[int, int]): the size of the output (in bins or pixels) after the pooling
            is performed, as (height, width).
        spatial_scale (float): a scaling factor that maps the box coordinates to
            the input coordinates. For example, if your boxes are defined on the scale
            of a 224x224 image and your input is a 112x112 feature map (resulting from a 0.5x scaling of
            the original image), you'll want to set this to 0.5. Default: 1.0

    Returns:
        Tensor[K, C / (output_size[0] * output_size[1]), output_size[0], output_size[1]]: The pooled RoIs.
    r   r	   )ÚtorchÚjitÚis_scriptingÚ
is_tracingr   Úps_roi_poolr   r
   r   Ú
isinstancer   r   ÚopsÚtorchvision)r   r   r   r   ÚroisÚoutputÚ_s          úLC:\Projects\Historical\venv\Lib\site-packages\torchvision/ops/ps_roi_pool.pyr   r      s¿   € õ> Œ9×!Ò!Ñ#Ô#ð )­E¬I×,@Ò,@Ñ,BÔ,Bð )Ý�KÑ(Ô(Ð(ÝÑÔÐÝ˜%Ñ Ô Ð Ø€DÝ˜Ñ$Ô$€KÝ�d�EœLÑ)Ô)ð 1Ý*¨4Ñ0Ô0ˆÝ”	Ô%×1Ò1°%¸¸}ÈkÐZ[ÌnÐ^iÐjkÔ^lÑmÔm�I€FˆAØ€Mó    c                   óL   ‡ — e Zd ZdZdedefˆ fd„Zdededefd„Zde	fd	„Z
ˆ xZS )
Ú	PSRoIPoolz"
    See :func:`ps_roi_pool`.
    r   r   c                 ó‚   •— t          ¦   «                              ¦   «          t          | ¦  «         || _        || _        d S ©N)ÚsuperÚ__init__r   r   r   )Úselfr   r   Ú	__class__s      €r   r%   zPSRoIPool.__init__;   s=   ø€ Ý‰Œ×ÒÑÔÐÝ˜DÑ!Ô!Ð!Ø&ˆÔØ*ˆÔÐÐr   r   r   r   c                 ó:   — t          ||| j        | j        ¦  «        S r#   )r   r   r   )r&   r   r   s      r   ÚforwardzPSRoIPool.forwardA   s   € Ý˜5 $¨Ô(8¸$Ô:LÑMÔMÐMr   c                 óD   — | j         j        › d| j        › d| j        › d�}|S )Nz(output_size=z, spatial_scale=ú))r'   Ú__name__r   r   )r&   Úss     r   Ú__repr__zPSRoIPool.__repr__D   s1   € ØŒ~Ô&ÐlÐl°TÔ5EÐlÐlÐW[ÔWiÐlÐlÐlˆØˆr   )r,   Ú
__module__Ú__qualname__Ú__doc__ÚintÚfloatr%   r   r)   Ústrr.   Ú__classcell__)r'   s   @r   r!   r!   6   s    ø€ € € € € ðð ð+ Cð +¸ð +ð +ð +ð +ð +ð +ðN˜Vð N¨6ð N°fð Nð Nð Nð Nð˜#ð ð ð ð ð ð ð ð r   r!   )r   )r   Útorch.fxr   r   Útorch.nn.modules.utilsr   Útorchvision.extensionr   Úutilsr   Ú_utilsr
   r   ÚfxÚwrapr2   r3   r   ÚModuler!   © r   r   ú<module>r?      s  ðØ €€€Ø €€€Ø Ð Ð Ð Ð Ð Ð Ð Ø (Ð (Ð (Ð (Ð (Ð (Ø 1Ð 1Ð 1Ð 1Ð 1Ð 1à 'Ð 'Ð 'Ð 'Ð 'Ð 'Ø FÐ FÐ FÐ FÐ FÐ FÐ FÐ Fð „„ð
 ð	'ð 'Øð'àð'ð ð'ð ð	'ð
 ð'ð 'ð 'ñ „ð'ðTð ð ð ð �”	ñ ô ð ð ð r   