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S~~"".t~~223 ^^ % % 1jAYAY[][d[d6e GGOO((//ctyyt~~OgOgOtOtIt?u  ~~'',,8t~~77<<= 4::| ,DJJ">DIIaRXjDY ! Z GGNN4::0055 6 djjooryy 1 GGNN4::??11 2 GGNN4::??// 0 2r2r|returnc|j\}}}}|j}tj||jk(d|jd|dtj||jk(d|jd|d||z}||z}|j |}|j ||j||z}|jddd}|S)NzWrong image height! Expected z but got !zWrong image width! Expected rr r) r{rrxryrrreshaperjpermute) rIr|nchwpn_hn_ws r3_process_inputz VisionTransformer._process_input sWW 1a OO a4??*.KDOOK\\efgehhi,jk a4??*.J4??J[[defdggh,ij1f1f NN1  IIa#) 4 IIaA r2c|j|}|jd}|jj|dd}t j ||gd}|j |}|dddf}|j|}|S)Nrrrz)rr{rexpandrxcatrr)rIr|rbatch_class_tokens r3rzVisionTransformer.forward!s    " GGAJ!,,33Ar2> II(!,! 4 LLO adG JJqMr2)r(r)r*r`rr-rr+rbrrrxr/listr"r?rrrrcrds@r3rrsE#&-15`_'s training recipe.  num_paramsrr_metrics_ops _file_size_docsurl transformsrz>https://download.pytorch.org/models/vit_b_16_swag-9ac1b537.pthr resize_size interpolationi^-)rrg~jtSU@giX@gˡEK@g|?5^t@ These weights are learnt via transfer learning by end-to-end fine-tuning the original `SWAG `_ weights on ImageNet-1K data. rrrrrrzAhttps://download.pytorch.org/models/vit_b_16_lc_swag-4e70ced5.pth+https://github.com/pytorch/vision/pull/5793gbX9xT@gQ X@ These weights are composed of the original frozen `SWAG `_ trunk weights and a linear classifier learnt on top of them trained on ImageNet-1K data. rrrrrrrNr(r)r*rrr r IMAGENET1K_V1r BICUBIC_COMMON_SWAG_METAIMAGENET1K_SWAG_E2E_V1IMAGENET1K_SWAG_LINEAR_V1DEFAULTr1r2r3rr_s# G.#>  ""f##  ! M,% L +33    ""##  ! 4!( O +33    C""##  ! !6Gr2rc XeZdZedeediedddddd d id d d dZeZy)rz9https://download.pytorch.org/models/vit_b_32-d86f8d99.pthrri1BrzNhttps://github.com/pytorch/vision/tree/main/references/classification#vit_b_32rg|?5^R@gW@rgA`Т@gl u@rrrN r(r)r*rrr rrrr1r2r3rrs\ G.#>  ""f##  ! M,Gr2rc eZdZedeeddieddddd d d id d ddZedeeddejie dddddd iddddZ edeeddejie ddddddd id d d d!Z eZ y")#rz9https://download.pytorch.org/models/vit_l_16-852ce7e3.pthr)rri#rzNhttps://github.com/pytorch/vision/tree/main/references/classification#vit_l_16rg|?5^S@gFԨW@rgףp= N@g;O$@a These weights were trained from scratch by using a modified version of TorchVision's `new training recipe `_. rrz>https://download.pytorch.org/models/vit_l_16_swag-4f3808c9.pthri0)rrgjtV@gT㥛ĠX@gƟv@gy&11@rrzAhttps://download.pytorch.org/models/vit_l_16_lc_swag-4d563306.pthrgMbXIU@g^I [X@rrNrr1r2r3rrs% G.#3O  #"f##  " M.% L +33    #"##  " 4!( O +33    C#"##  " !6Gr2rc XeZdZedeediedddddd d id d d dZeZy)rz9https://download.pytorch.org/models/vit_l_32-c7638314.pthrri[ErzNhttps://github.com/pytorch/vision/tree/main/references/classification#vit_l_32rg|?5>S@gGzDW@rgK7.@gE@rrrNrr1r2r3rrs\ G.#>  #"f#"  " M,Gr2rc eZdZedeeddejiedddddd id d d d Z edeeddejieddddddd iddddZ e Z y)rz>https://download.pytorch.org/models/vit_h_14_swag-80465313.pthri%)rrrgS#V@g#~jX@rg~jŏ@gK7I@rrrzAhttps://download.pytorch.org/models/vit_h_14_lc_swag-c1eb923e.pthrri@%rgZd;OmU@gQnX@g= ףpd@gI k֢@rrN) r(r)r*rrr r rrrrrr1r2r3rr2s$ L +33    #"##  " 4!( O +33    C#"##  " !6%Gr2r pretrained)rT)rrc Rtj|}tdddddd||d|S)a Constructs a vit_b_16 architecture from `An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale `_. Args: weights (:class:`~torchvision.models.ViT_B_16_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.ViT_B_16_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.vision_transformer.VisionTransformer`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.ViT_B_16_Weights :members:   rrrirjr7rrr1)rverifyrrrrs r3rrkE(%%g.G      r2c Rtj|}tdddddd||d|S)a Constructs a vit_b_32 architecture from `An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale `_. Args: weights (:class:`~torchvision.models.ViT_B_32_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.ViT_B_32_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.vision_transformer.VisionTransformer`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.ViT_B_32_Weights :members: rrrrr1)rrrrs r3rrr r2c Rtj|}tdddddd||d|S)a Constructs a vit_l_16 architecture from `An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale `_. Args: weights (:class:`~torchvision.models.ViT_L_16_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.ViT_L_16_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.vision_transformer.VisionTransformer`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.ViT_L_16_Weights :members: rrr1)rrrrs r3rrE(%%g.G      r2c Rtj|}tdddddd||d|S)a Constructs a vit_l_32 architecture from `An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale `_. Args: weights (:class:`~torchvision.models.ViT_L_32_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.ViT_L_32_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.vision_transformer.VisionTransformer`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.ViT_L_32_Weights :members: r r rrrrr1)rrrrs r3rrrr2)rNc Rtj|}tdddddd||d|S)a Constructs a vit_h_14 architecture from `An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale `_. Args: weights (:class:`~torchvision.models.ViT_H_14_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.ViT_H_14_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.vision_transformer.VisionTransformer`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.ViT_H_14_Weights :members: r riirr1)rrrrs r3r r rr2r model_statezOrderedDict[str, torch.Tensor]interpolation_mode reset_headsc|d}|j\}}}|dk7rtd|j||zdzdz} | |k7r0|dz}| dz} |ddddddf} |ddddddf} | jddd} tt j |} | | z|k7rtd| | zd|| j d|| | } ||z} tjj| | |d }|j d|| }|jddd}tj| |gd }||d<|r;t}|jD]\}}|jd r|||<|}|S) aThis function helps interpolate positional embeddings during checkpoint loading, especially when you want to apply a pre-trained model on images with different resolution. Args: image_size (int): Image size of the new model. patch_size (int): Patch size of the new model. model_state (OrderedDict[str, torch.Tensor]): State dict of the pre-trained model. interpolation_mode (str): The algorithm used for upsampling. Default: bicubic. reset_heads (bool): If true, not copying the state of heads. Default: False. Returns: OrderedDict[str, torch.Tensor]: A state dict which can be loaded into the new model. zencoder.pos_embeddingrz%Unexpected position embedding shape: r NrzPseq_length is not a perfect square! Instead got seq_length_1d * seq_length_1d = z and seq_length = T)sizemode align_cornersrr)r{ ValueErrorrr+rrrr- functional interpolaterxrritems startswith)rrrrrrrrrjnew_seq_lengthpos_embedding_tokenpos_embedding_img seq_length_1dnew_seq_length_1dnew_pos_embedding_imgnew_pos_embeddingmodel_state_copykvs r3interpolate_embeddingsr*s* 78M - 3 3Az:Av@ATAT@UVWW J.14q8N #a !+Arr1H5)!QR(3.55aA>DIIj12 = (J 6bcptAdAcCCUV`Uab  .55a]Tab&*4!# 9 9 "# !:! !6 = =a^ \!6 = =aA F!II':r:sh #66 0H'66'B 9Z9+ s+ \!299!H#9bii#9LQ Qh    k " B&  d38n8KL{L^{4M{M`{46%{6%r,0@0N0N!OP6:T"23d]`evQ@,0@0N0N!OP6:T"23d]`evQ@,0@0N0N!OP6:T"23d]`evQ@,0@0N0N!OP6:T"23d]`evQ@!566:T"23d]`ev7H( KKK2K K  K & Kr2