a PSic @sddlZddlZddlmmZddlmZmZddlmZdee e e e e edd d Z dee e e e e edd d Z ejd Gd ddejZejd GdddeZdS)N)nnTensor)_log_api_usage_onceFư>T)inputp block_sizeinplaceepstrainingreturnc Cs^tjstjstt|dks,|dkr`. Args: input (Tensor[N, C, H, W]): The input tensor or 4-dimensions with the first one being its batch i.e. a batch with ``N`` rows. p (float): Probability of an element to be dropped. block_size (int): Size of the block to drop. inplace (bool): If set to ``True``, will do this operation in-place. Default: ``False``. eps (float): A value added to the denominator for numerical stability. Default: 1e-6. training (bool): apply dropblock if is ``True``. Default: ``True``. Returns: Tensor[N, C, H, W]: The randomly zeroed tensor after dropblock. ?4drop probability has to be between 0 and 1, but got .z#input should be 4 dimensional. Got dimensions.rdtypedevicervalue)rrstride kernel_sizepadding)torchjit is_scripting is_tracingr drop_block2d ValueErrorndimsizeminemptyrr bernoulli_Fpad max_pool2dnumelsummul_) rrr r r r NCHWgammanoisenormalize_scaler6V/var/www/html/django/DPS/env/lib/python3.9/site-packages/torchvision/ops/drop_block.pyr" s*   ,,  r"cCs~tjstjstt|dks,|dkr`. Args: input (Tensor[N, C, D, H, W]): The input tensor or 5-dimensions with the first one being its batch i.e. a batch with ``N`` rows. p (float): Probability of an element to be dropped. block_size (int): Size of the block to drop. inplace (bool): If set to ``True``, will do this operation in-place. Default: ``False``. eps (float): A value added to the denominator for numerical stability. Default: 1e-6. training (bool): apply dropblock if is ``True``. Default: ``True``. Returns: Tensor[N, C, D, H, W]: The randomly zeroed tensor after dropblock. rrrrz#input should be 5 dimensional. Got rrrrrr)rrrr)rrr r!r drop_block3dr#r$r%r&r'rrr(r)r* max_pool3dr,r-r.)rrr r r r r/r0Dr1r2r3r4r5r6r6r7r;7s2  <,  r;csNeZdZdZdeeeeddfdd Zeedd d Z e d d d Z Z S) DropBlock2dz# See :func:`drop_block2d`. FrNrr r r r cs&t||_||_||_||_dSN)super__init__rr r r selfrr r r  __class__r6r7rBqs  zDropBlock2d.__init__rr cCst||j|j|j|j|jSz Args: input (Tensor): Input feature map on which some areas will be randomly dropped. Returns: Tensor: The tensor after DropBlock layer. )r"rr r r r rDrr6r6r7forwardyszDropBlock2d.forward)r cCs*|jjd|jd|jd|jd}|S)Nz(p=z , block_size=z , inplace=))rF__name__rr r )rDsr6r6r7__repr__s&zDropBlock2d.__repr__)Fr) rL __module__ __qualname____doc__floatintboolrBrrJstrrN __classcell__r6r6rEr7r>ls r>cs@eZdZdZd eeeeddfdd Zeedd d Z Z S) DropBlock3dz# See :func:`drop_block3d`. FrNr?cst||||dSr@)rArBrCrEr6r7rBszDropBlock3d.__init__rGcCst||j|j|j|j|jSrH)r;rr r r r rIr6r6r7rJszDropBlock3d.forward)Fr) rLrOrPrQrRrSrTrBrrJrVr6r6rEr7rWsrW)FrT)FrT)rZtorch.fxtorch.nn.functionalr functionalr)rutilsrrRrSrTr"r;fxwrapModuler>rWr6r6r6r7s$   /  2