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MobileNet V3 main class Args: inverted_residual_setting (List[InvertedResidualConfig]): Network structure last_channel (int): The number of channels on the penultimate layer num_classes (int): Number of classes block (Optional[Callable[..., nn.Module]]): Module specifying inverted residual building block for mobilenet norm_layer (Optional[Callable[..., nn.Module]]): Module specifying the normalization layer to use dropout (float): The droupout probability z1The inverted_residual_setting should not be emptycSsg|]}t|tqSr)) isinstancer).0sr)r)r* sz(MobileNetV3.__init__..zDThe inverted_residual_setting should be List[InvertedResidualConfig]NgMbP?g{Gz?)epsZmomentumrr )r;r"r8r<rr:T)inplace)pr`Zfan_out)mode)"r?r+r r@rXrall TypeErrorr6rrZ BatchNorm2drrCr rBrrDfeaturesZAdaptiveAvgPool2davgpoolZLinearZDropout classifiermodulesZConv2dinitZkaiming_normal_weightZbiasZzeros_Z GroupNormZones_Znormal_)r(rSrTrUrEr8rVrWrFZfirstconv_output_channelsr7Zlastconv_input_channelsZlastconv_output_channelsmrGr)r*r+wsx             zMobileNetV3.__init__xcCs.||}||}t|d}||}|S)Nr)rerftorchflattenrgr(rlr)r)r* _forward_impls    zMobileNetV3._forward_implcCs ||SrK)rpror)r)r*rMs zMobileNetV3.forward)rQNNrR)r.r/r0listrr1rrrrOr4rr+rrprMrPr)r)rGr*rvs0 [ r?Farchr$ reduced_taildilatedrWc Ks|rdnd}|r dnd}tt|d}ttj|d}|dkr|dddddddd|ddd d dddd|d dd d dddd|d d d d dddd|d d dd dddd|d d dd dddd|d ddddddd|dddddddd|dddddddd|dddddddd|dddddddd|dddddddd|dd dd|ddd||d|d d|d|ddd||d|d d|d|ddd|g} |d|} | | fS|dkrZ|dddddddd|ddd d dddd|d ddd dddd|d d dd dddd|d d dd dddd|d d dd dddd|d d dddddd|dd dddddd|dd d d|ddd||d|d d!|d|ddd||d|d d!|d|ddd|g } |d"|} | | fStd#|)$Nr r)r$rr]FZRE@H(TxPr%ipiiirX`0i i@izUnsupported model type )rrr&r@) rsr$rtrurWZreduce_dividerr#Z bneck_confr&rSrTr)r)r*_mobilenet_v3_confsN          rrSrTweightsprogressrJcKsP|durt|dt|jdt||fi|}|dur&||j|dd|S)NrU categoriesT)rZ check_hash)rlenmetarZload_state_dictZget_state_dict)rSrTrrrWmodelr)r)r* _mobilenet_v3s r)rr)Zmin_sizerc @s~eZdZedeeddiedddddd id d d d dZedeedddiedddddd id ddd dZeZ dS)rzChttps://download.pytorch.org/models/mobilenet_v3_large-8738ca79.pth crop_sizeiS^https://github.com/pytorch/vision/tree/main/references/classification#mobilenetv3-large--small ImageNet-1Kg R@g(\V@zacc@1zacc@5g-?gw/5@zJThese weights were trained from scratch by using a simple training recipe.Z num_paramsZrecipeZ_metricsZ_ops _file_sizeZ_docsurlZ transformsrzChttps://download.pytorch.org/models/mobilenet_v3_large-5c1a4163.pth)rZ resize_sizezHhttps://github.com/pytorch/vision/issues/3995#new-recipe-with-reg-tuninggK7R@gNbX9$W@gZd5@a/ These weights improve marginally upon the results of the original paper by using a modified version of TorchVision's `new training recipe `_. N) r.r/r0rrr _COMMON_META IMAGENET1K_V1Z IMAGENET1K_V2DEFAULTr)r)r)r*r)sL  rc @sFeZdZedeeddiedddddd id d d d dZeZdS)rzChttps://download.pytorch.org/models/mobilenet_v3_small-047dcff4.pthrri&rrgnP@g}?5^U@rgv/?g r#@z} These weights improve upon the results of the original paper by using a simple training recipe. rrN) r.r/r0rrr rrrr)r)r)r*rUs( rZ pretrained)rT)rrcK2t|}tdi|\}}t||||fi|S)a Constructs a large MobileNetV3 architecture from `Searching for MobileNetV3 `__. Args: weights (:class:`~torchvision.models.MobileNet_V3_Large_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.MobileNet_V3_Large_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.mobilenet.MobileNetV3`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.MobileNet_V3_Large_Weights :members: rN)r)rverifyrrrrrWrSrTr)r)r*rm rcKr)a Constructs a small MobileNetV3 architecture from `Searching for MobileNetV3 `__. Args: weights (:class:`~torchvision.models.MobileNet_V3_Small_Weights`, optional): The pretrained weights to use. See :class:`~torchvision.models.MobileNet_V3_Small_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.mobilenet.MobileNetV3`` base class. Please refer to the `source code `_ for more details about this class. .. autoclass:: torchvision.models.MobileNet_V3_Small_Weights :members: rN)r)rrrrrr)r)r*rrr)rrFF)/collections.abcr functoolsrtypingrrrrmrrZops.miscr r rNZtransforms._presetsr utilsr Z_apirrr_metarZ_utilsrrr__all__rrOr6rr3r4r2rrqr1rrrrrrrr)r)r)r*s     Ak 1 ,