o ϯi @sddlmZddlZddlmZ  ddejdeded efd d ZGd d d ej j Z Gdddej j Z Gdddej j Z dS))TupleN)convert_to_one_hot?labels num_classeslamlabel_smoothingcCs2t|||}t|d||}|||d|S)aJ This function converts class indices to one-hot vectors and mix labels, given the number of classes. Args: labels (torch.Tensor): Class labels. num_classes (int): Total number of classes. lam (float): lamba value for mixing labels. label_smoothing (float): Label smoothing value. rr)rflip)rrrr labels1labels2r O/home/ubuntu/.local/lib/python3.10/site-packages/pytorchvideo/transforms/mix.py _mix_labels s rc s`eZdZdZ   ddedededd ffd d Zd ejd ejde ejejffddZ Z S)MixUpzV Mixup: Beyond Empirical Risk Minimization (https://arxiv.org/abs/1710.09412) rralphar rreturnNc,ttjj|||_||_||_dS)z This implements MixUp for videos. Args: alpha (float): Mixup alpha value. label_smoothing (float): Label smoothing value. num_classes (int): Number of total classes. N) super__init__torch distributionsbetaBetamixup_beta_samplerr rselfrr r __class__r rr#  zMixUp.__init__xrcCs^|ddks Jd|j}|dd|}|||t||j||j}||fS)" The input is a batch of samples and their corresponding labels. Args: x (torch.Tensor): Input tensor. The input should be a batch of videos with shape (B, C, T, H, W). labels (torch.Tensor): Labels for input with shape (B). rz-MixUp cannot be applied to a single instance.r) sizersampler mul_add_rrr )rr!r mixup_lambda x_flipped new_labelsr r rforward6s z MixUp.forwardrrr) __name__ __module__ __qualname____doc__floatintrrTensorrr+ __classcell__r r rrrs*rc seZdZdZ   ddedededd ffd d Zd ed ededefddZdeededeefddZ de j dedee j effddZ de j de j dee j e j ffddZ ZS)CutMixz CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features (https://arxiv.org/abs/1905.04899) rrrrr rrNcr)z This implements CutMix for videos. Args: alpha (float): CutMix alpha value. label_smoothing (float): Label smoothing value. num_classes (int): Number of total classes. N) rrrrrrcutmix_beta_samplerr rrrr rrUr zCutMix.__init__value min_value max_valuecCstt|||S)zF Clip value based on minimum value and maximum value. )minmax)rr7r8r9r r r_cliphsz CutMix._clip input_shape cutmix_lamdacCsd|d}|dd\}}t||t||}}t|d}t|d} |||dd|} |||dd|} || |dd|} || |dd|} | | | | fS)z? Get a random square box given a lambda value. r#?N)r#r)r2rrandintitemr<)rr=r>ratioinput_hinput_wcut_hcut_wcycxylyhxlxhr r r _get_rand_boxos  zCutMix._get_rand_boxr!c Cs~|||\}}}}t||||}d||d|d}|dd||||f|d||||f<||fS)zC Perform CutMix and return corrected lambda value. rr@r.)rOr$r1r ) rr!r>rKrLrMrNbox_areacutmix_lamda_correctedr r r_cutmixs .zCutMix._cutmixrcCsj|ddks Jd|dks|dksJd|j}|||\}}t||j||j}||fS)r"rr#z.Cutmix cannot be applied to a single instance.zPlease correct input shape.)r$dimr6r%rSrrr )rr!rr>rRr*r r rr+s  zCutMix.forwardr,)r-r.r/r0r1r2rr<rrOrr3rSr+r4r r rrr5Os<   r5c sXeZdZdZ     ddededed ed ef fd d Zd ejdejfddZ Z S)MixVideozK Stochastically applies either MixUp or CutMix to the input video. r?rrr cutmix_prob mixup_alpha cutmix_alphar rcsXd|kr dksJdJdt||_t|||d|_t|||d|_dS)a Args: cutmix_prob (float): Probability of using CutMix. MixUp will be used with probability 1 - cutmix_prob. If cutmix_prob is 0, then MixUp is always used. If cutmix_prob is 1, then CutMix is always used. mixup_alpha (float): MixUp alpha value. cutmix_alpha (float): CutMix alpha value. label_smoothing (float): Label smoothing value. num_classes (int): Number of total classes. rrz)cutmix_prob should be between 0.0 and 1.0)rr rN)rrrXrmixupr5cutmix)rrXrYrZr rrr rrs$  zMixVideo.__init__r!rcCs,td|jkr|||S|||S)r"r#)rrandrCrXr\r[)rr!rr r rr+s  zMixVideo.forward)r?rrrr) r-r.r/r0r1r2rrr3r+r4r r rrrWs&rW)rr)typingrr"pytorchvideo.transforms.functionalrr3r2r1rnnModulerr5rWr r r rs"   1V