156 lines
12 KiB
TeX
156 lines
12 KiB
TeX
[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.ConvTranspose2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_upsample() for <class 'torch.nn.modules.upsampling.Upsample'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.container.Sequential'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.ConvTranspose2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_upsample() for <class 'torch.nn.modules.upsampling.Upsample'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.container.Sequential'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.ConvTranspose2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_upsample() for <class 'torch.nn.modules.upsampling.Upsample'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.container.Sequential'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.ConvTranspose2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_upsample() for <class 'torch.nn.modules.upsampling.Upsample'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.container.Sequential'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.ConvTranspose2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_upsample() for <class 'torch.nn.modules.upsampling.Upsample'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.container.Sequential'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.ConvTranspose2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_upsample() for <class 'torch.nn.modules.upsampling.Upsample'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.container.Sequential'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.ConvTranspose2d'>.
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[INFO] Register count_convNd() for <class 'torch.nn.modules.conv.Conv2d'>.
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[INFO] Register count_normalization() for <class 'torch.nn.modules.batchnorm.BatchNorm2d'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.pooling.MaxPool2d'>.
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[INFO] Register count_linear() for <class 'torch.nn.modules.linear.Linear'>.
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[INFO] Register count_upsample() for <class 'torch.nn.modules.upsampling.Upsample'>.
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[INFO] Register zero_ops() for <class 'torch.nn.modules.container.Sequential'>.
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\begin{table}[!ht]
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\centering
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\renewcommand{\arraystretch}{1.15}
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\begin{tabularx}{\linewidth}{lXXXXXXXX}
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\hline
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& \multicolumn{4}{c}{\textbf{Encoders}} & \multicolumn{4}{c}{\textbf{Autoencoders}} \\
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\cline{2-9}
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\textbf{Latent $z$} & \textbf{LeNet Params} & \textbf{LeNet MACs} & \textbf{Eff. Params} & \textbf{Eff. MACs} & \textbf{LeNet Params} & \textbf{LeNet MACs} & \textbf{Eff. Params} & \textbf{Eff. MACs} \\
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\hline
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32 & 525.29K & 27.92M & 263.80K & 29.82M & 1.05M & 54.95M & 532.35K & 168.49M \\
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64 & 1.05M & 28.44M & 525.94K & 30.08M & 2.10M & 56.00M & 1.06M & 169.02M \\
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128 & 2.10M & 29.49M & 1.05M & 30.61M & 4.20M & 58.10M & 2.11M & 170.07M \\
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256 & 4.20M & 31.59M & 2.10M & 31.65M & 8.39M & 62.29M & 4.20M & 172.16M \\
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512 & 8.39M & 35.78M & 4.20M & 33.75M & 16.78M & 70.68M & 8.40M & 176.36M \\
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768 & 12.58M & 39.98M & 6.29M & 35.85M & 25.17M & 79.07M & 12.59M & 180.55M \\
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1024 & 16.78M & 44.17M & 8.39M & 37.95M & 33.56M & 87.46M & 16.79M & 184.75M \\
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\hline
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\end{tabularx}
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\caption{Parameter and MAC counts for SubTer variants across latent dimensionalities.}
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\label{tab:subter_counts}
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\end{table}
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