khSn ddlZddlmZddlmZmZmZmZddlZddlm Z ddl m Z m Z gdZde d ed ed e d eeef d ZGddeZGddej&j(ZGddej&j(ZGddej&j(ZGddej&j(Zy)N)Enum)DictListOptionalTuple)Tensor) functionalInterpolationMode)AutoAugmentPolicy AutoAugment RandAugmentTrivialAugmentWideAugMiximgop_name magnitude interpolationfillc |dk(rKtj|dddgdtjtj|dg||ddg}|S|dk(rKtj|dddgddtjtj|g||ddg}|S|dk(r+tj|dt |dgd|ddg|}|S|d k(r+tj|ddt |gd|ddg|}|S|d k(rtj |||| }|S|d k(rtj|d|z}|S|d k(rtj|d|z}|S|dk(rtj|d|z}|S|dk(rtj|d|z}|S|dk(r!tj|t |}|S|dk(rtj||}|S|dk(rtj|}|S|dk(rtj|}|S|dk(rtj|}|S|dk(r |St!d|d)NShearXr?)angle translatescaleshearrrcenterShearY TranslateX)rrrrrr TranslateYRotaterr BrightnessColorContrast Sharpness PosterizeSolarize AutoContrastEqualizeInvertIdentityzThe provided operator  is not recognized.)Faffinemathdegreesatanintrotateadjust_brightnessadjust_saturationadjust_contrastadjust_sharpness posterizesolarize autocontrastequalizeinvert ValueError)rrrrrs ^/var/www/teggl/fontify/venv/lib/python3.12/site-packages/torchvision/transforms/autoaugment.py _apply_oprA s(hh !f<< ) 45s;'q6  F Js H hh !f TYYy%9:;'q6  l JY L hh 9~q)'* V JE L hh #i.)'* B J1 H hhsI]N. J- L !!#sY7* J) G !!#sY7& J% J S9_5" J! K   cIo6 J K kk#s9~. J J jji( J N "nnS! J J jjo J H hhsm J J   J1':MNOOceZdZdZdZdZdZy)r zoAutoAugment policies learned on different datasets. Available policies are IMAGENET, CIFAR10 and SVHN. imagenetcifar10svhnN)__name__ __module__ __qualname____doc__IMAGENETCIFAR10SVHNrBr@r r ]sHG DrBr c (eZdZdZej ejdfdededee e ddffd Z dede e e e e eefe e e eefffdZd ed e eefdee e eefffd Zed ede eeeffd ZdedefdZde fdZxZS)r a?AutoAugment data augmentation method based on `"AutoAugment: Learning Augmentation Strategies from Data" `_. If the image is torch Tensor, it should be of type torch.uint8, and it is expected to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions. If img is PIL Image, it is expected to be in mode "L" or "RGB". Args: policy (AutoAugmentPolicy): Desired policy enum defined by :class:`torchvision.transforms.autoaugment.AutoAugmentPolicy`. Default is ``AutoAugmentPolicy.IMAGENET``. interpolation (InterpolationMode): Desired interpolation enum defined by :class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.NEAREST``. If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported. fill (sequence or number, optional): Pixel fill value for the area outside the transformed image. If given a number, the value is used for all bands respectively. Npolicyrrreturncxt|||_||_||_|j ||_yN)super__init__rPrr _get_policiespolicies)selfrPrr __class__s r@rUzAutoAugment.__init__ys8  * **62 rBc|tjk(rgdS|tjk(rgdS|tjk(rgdSt d|d)N)))r(皙?)r"333333? )r)r]r*r]Nr+皙?Nr+r]N))r(r])r(r]r+r[N)r)皙?)rir"rdr\))r)r]re))r(rdr`r+rN))r"rjrm)r)r]r\)re)r(r[rg)rlr%r[r))r"r[r^re))r+rNrcr,r]Nrn)r%r]rk)r&rr\)rl)r%r))r%rdr\)r)rdrf))r'r[rfrq))rr]r`rn)rorerhr_rprrrb))r,皙?N)r&rjrg))r"ffffff?rs)r 333333?r^))r'rdr )r'?rm))r?r\r!rvr^))r*ryNr+rxN))rrjrf)r(rwrf))r%r[rm)r$r]rf))r'rwr^)r$rvr^)re)r+ryN))r&r]rf)r'r]r`))r%rvrf)r ryr\))r+rwN)r*r[N))r!r[rm)r'rjrg))r$rxrg)r%rjr\))r)ryrs)r,rN)r+rjNra)r|re))r%rxr^re)r*rdN)r)rjr\))r$rurm)r%rvr))r)r[r`r*rxN))r!rxr^rz)r~)r)rdrm)rcrt)rzr~))rrxrk)r,rjN)rrxr\r,rvN)re)r)r]rgr,rxNrere)r"rxrm)rr})r)r,r[N))rrxr`)r)rjrg)rr}r)r)r)rwrm))rrdr\r)r{)r!r]rgr))r&rwrmr"rdrk)r,rdN)r!rrs))rrvrg)r)r[r\)rqr))rrwrf)r rxrm))rrurgrq))r)rvrs)r!r]rf))rrdrkr))rrvr^)r!rdrm))rrdr`)r*rvN))rrvrsrtzThe provided policy r.)r rKrLrMr?)rXrPs r@rVzAutoAugment._get_policiessk &// / 6(00 0 6(-- - 83F8;NOP PrBnum_bins image_sizectjdd|dftjdd|dftjdd|dz|dftjdd|dz|dftjdd|dftjdd|dftjdd|dftjdd|dftjdd|dfd tj||dz d z z jj z d ftjd d|d ftj dd ftj dd ftj dd fd S)NrrwTt?r r>@rxr\rkFo@)rrr r!r"r$r%r&r'r(r)r*r+r,)torchlinspacearangeroundr4tensorrXrrs r@_augmentation_spacezAutoAugment._augmentation_spaces^~~c394@~~c394@ >>#}z!}/LhWY]^ >>#}z!}/LhWY]^~~c4:DA >>#sH=tDnnS#x8$?S(;TB..c8yy"#"2"23"7&% c6 "$e -d }x/!*./Qa//%)__S5G%H" eU**2?-6t}}\7R-S f )A)LQx1}%,W%5" FFRF^E*\":"?"?"ABdg eAh!m%IWitGYGY`de  f 0s"D2ch|jjd|jd|jdS)Nz(policy=, fill=))rYrGrPr)rXs r@__repr__zAutoAugment.__repr__s/..))*(4;;-wtyykQRSSrB)rGrHrIrJr rKr NEARESTrrrrUrstrr4rVrrboolr staticmethodrrr __classcell__rYs@r@r r hs)$%6$>$>+<+D+D&* 3! 3) 3tE{# 3  3XQ'XQ eE#uhsm34eCQT `_. If the image is torch Tensor, it should be of type torch.uint8, and it is expected to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions. If img is PIL Image, it is expected to be in mode "L" or "RGB". Args: num_ops (int): Number of augmentation transformations to apply sequentially. magnitude (int): Magnitude for all the transformations. num_magnitude_bins (int): The number of different magnitude values. interpolation (InterpolationMode): Desired interpolation enum defined by :class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.NEAREST``. If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported. fill (sequence or number, optional): Pixel fill value for the area outside the transformed image. If given a number, the value is used for all bands respectively. rsr^Nnum_opsrnum_magnitude_binsrrrQcht|||_||_||_||_||_yrS)rTrUrrrrr)rXrrrrrrYs r@rUzRandAugment.__init__2s5  ""4* rBrrctjddftjdd|dftjdd|dftjdd|dz|dftjdd|dz|dftjdd|dftjdd |dftjdd |dftjdd |dftjdd |dfd tj||dz d z z j j z dftjd d|dftjddftjddfd S)NrFrwTrr rrrxr\rkrr-rrr r!r"r$r%r&r'r(r)r*r+rrrrrr4rs r@rzRandAugment._augmentation_spaceAs^c*E2~~c394@~~c394@ >>#}z!}/LhWY]^ >>#}z!}/LhWY]^~~c4:DA >>#sH=tDnnS#x8$?S(;TB..c8*84G!(!1 JDNOOVWDWj8==?@]`I%--40T! C)4CUCU\`aC b 0s"E8c |jjd|jd|jd|jd|j d|j d }|S)Nz (num_ops=z , magnitude=z, num_magnitude_bins=, interpolation=rr)rYrGrrrrrrXss r@rzRandAugment.__repr__osg~~&&'(||n4>>*#D$;$;#<t112dii[   rB)rGrHrIrJr rr4rrrrUrrrrrrrrrrs@r@rrs("$+<+D+D&*     )  tE{#    C U38_ QUVY[`agimam[nVnQo &6f6 # rBrc eZdZdZdej dfdededeee ddffd Z d ede e e eefffd Zd edefd Zde fd ZxZS)raDataset-independent data-augmentation with TrivialAugment Wide, as described in `"TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation" `_. If the image is torch Tensor, it should be of type torch.uint8, and it is expected to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions. If img is PIL Image, it is expected to be in mode "L" or "RGB". Args: num_magnitude_bins (int): The number of different magnitude values. interpolation (InterpolationMode): Desired interpolation enum defined by :class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.NEAREST``. If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported. fill (sequence or number, optional): Pixel fill value for the area outside the transformed image. If given a number, the value is used for all bands respectively. rNrrrrQcLt|||_||_||_yrS)rTrUrrr)rXrrrrYs r@rUzTrivialAugmentWide.__init__s' "4* rBrctjddftjdd|dftjdd|dftjdd|dftjdd|dftjdd|dftjdd|dftjdd|dftjdd|dftjdd|dfdtj||dz d z z j j z dftjd d|dftjddftjddfd S) NrFgGz?Tg@@g`@r\r rgrrr)rXrs r@rz&TrivialAugmentWide._augmentation_spacesJc*E2~~c4:DA~~c4:DA >>#tX>E >>#tX>E~~c5(;TB >>#tX>EnnS$94@T8Q9Q4R &_6_f_:#rBrcNeZdZdZdddddej dfdeded ed ed ed ed e e eddffd Z dede eefde ee eefffdZej$j&defdZej$j&defdZdedefdZdedefdZdefdZxZS)raAugMix data augmentation method based on `"AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty" `_. If the image is torch Tensor, it should be of type torch.uint8, and it is expected to have [..., 1 or 3, H, W] shape, where ... means an arbitrary number of leading dimensions. If img is PIL Image, it is expected to be in mode "L" or "RGB". Args: severity (int): The severity of base augmentation operators. Default is ``3``. mixture_width (int): The number of augmentation chains. Default is ``3``. chain_depth (int): The depth of augmentation chains. A negative value denotes stochastic depth sampled from the interval [1, 3]. Default is ``-1``. alpha (float): The hyperparameter for the probability distributions. Default is ``1.0``. all_ops (bool): Use all operations (including brightness, contrast, color and sharpness). Default is ``True``. interpolation (InterpolationMode): Desired interpolation enum defined by :class:`torchvision.transforms.InterpolationMode`. Default is ``InterpolationMode.NEAREST``. If input is Tensor, only ``InterpolationMode.NEAREST``, ``InterpolationMode.BILINEAR`` are supported. fill (sequence or number, optional): Pixel fill value for the area outside the transformed image. If given a number, the value is used for all bands respectively. rmrTNseverity mixture_width chain_depthalphaall_opsrrrQct|d|_d|cxkr|jksntd|jd|d||_||_||_||_||_||_ ||_ y)Nrr z!The severity must be between [1, z]. Got z instead.) rTrU_PARAMETER_MAXr?rrrrrrr) rXrrrrrrrrYs r@rUzAugMix.__init__s  X4!4!44@ATAT@UU\]e\ffopq q  *&  * rBrrc tjdd|dftjdd|dftjd|ddz |dftjd|ddz |dftjdd|dfdtj||dz dz z jj z d ftjd d|d ftj dd ftj dd fd }|j rr|jtjdd |dftjdd |dftjdd |dftjdd |dfd |S)NrrwTr g@rrrkFr) rrr r!r"r(r)r*r+rx)r$r%r&r')rrrrr4rrupdate)rXrrrs r@rzAugMix._augmentation_spacesi~~c394@~~c394@ >>#z!}s/BHMtT >>#z!}s/BHMtT~~c4:DAu||H5(Q,!9KLSSUYY[[]bcsH=uE"\\#.6c*E2  << HH#(>>#sH#Et"L#nnS#x@$G!&S(!CT J"'..c8"Dd!K  rBc,tj|SrS)r/ pil_to_tensorrXrs r@_pil_to_tensorzAugMix._pil_to_tensorss##rBrc,tj|SrS)r/ to_pil_imagers r@_tensor_to_pilzAugMix._tensor_to_pils~~c""rBparamsc,tj|SrS)r_sample_dirichlet)rXrs r@rzAugMix._sample_dirichlets&&v..rBorig_imgc |j}tj|\}}}t|trC|}t|t t frt |g|z}n,|*|Dcgc] }t |}}n|j|}|j|j||f}t|j} |jdgtd|jz dz| z} | jdgdg| jdz zz} |j!t#j$|j&|j&g| j(j+| dd} |j!t#j$|j&g|j,z| j(j+| dd| dddfj| ddgz} | dddfj| | z}t/|j,D]u}| }|j0dkDr |j0n.t t#j2dddj5}t/|D]}t t#j2t7|dj5}t|j9|}||\}}|jdkDrJt |t#j2|j:dt"j< j5nd }|rt#j2d dr|d z}t?||||j@| }|jC| dd|fj| |zx|j| jE|jF }t|ts|jI|S|Scc}w)rNr rkr)devicerr)lowhighsizerrrsrr#)%rr/rrrr4rrrrrshapeviewmaxrrrrrrrexpandrrrrrrrrrrAradd_torr)rXrrrrrrrr orig_dimsbatch batch_dimsmcombined_weightsmixraugdepthrrrrrrs r@rzAugMix.forward!s]yy"#"2"28"<&% h 'C$e -d }x/!*./Qa//%%h/C**4+>+>PO !s1sxx<33i?@jjm_sejj1n'==   " " LL$**djj1%,, G N NzZ[}^` a   11 LL$**(:(::5<< P W WXbcdXegi j adGLL*Q-, -.1gll:&.t))* DAC(,(8(81(r s .. 0 ]M MM*/M@QMYabfglbmYnM`tT%((//tTnZ%((//ZzSSlUUXX__UrB