Added cifar10 and mnist scaling figures

main.tex

@@ -283,7 +283,7 @@ We solve this problem by decoupling the gradient averaging from the weight avera
          \includegraphics[width=\textwidth]{figures/d-cliques-mnist-init-clique-avg-effect-fcc-test-accuracy}
          \caption{\label{fig:d-cliques-mnist-init-clique-avg-effect-fcc-test-accuracy} Fully-Connected}
      \end{subfigure}
-\caption{\label{fig:d-cliques-mnist-initialization-effect} MNIST: Effects of Clique Averaging and Uniform Initialization on Convergence Speed. (100 nodes, non-IID, D-Cliques, bsz=128)}
+\caption{\label{fig:d-cliques-mnist-init-clique-avg-effect} MNIST: Effects of Clique Averaging and Uniform Initialization on Convergence Speed. (100 nodes, non-IID, D-Cliques, bsz=128)}
 \end{figure}
 
     \begin{figure}[htbp]
@@ -298,27 +298,38 @@ We solve this problem by decoupling the gradient averaging from the weight avera
          %\includegraphics[width=0.7\textwidth]{figures/d-cliques-mnist-vs-1-node-test-accuracy}
          \caption{\label{fig:mnist-clique-clustering-fcc} Fully-Connected}
      \end{subfigure}
-\caption{\label{fig:d-cliques-mnist-initialization-effect} MNIST: Effects of Clustering within Cliques on Convergence Speed.}
+\caption{\label{fig:d-cliques-mnist-clique-clustering} MNIST: Effects of Clustering within Cliques on Convergence Speed.}
 \end{figure}
 
      \begin{figure}[htbp]
          \centering
-         % To regenerate the figure, from directory results/scaling
-% python ../../../learn-topology/tools/plot_convergence.py 10/mnist/fully-connected-cliques/all/2021-03-10-14:40:35-CET ../mnist/fully-connected-cliques/all/2021-03-10-10:19:44-CET 1000/mnist/fully-connected-cliques/all/2021-03-10-16:44:35-CET --labels '10 nodes bsz=128' '100 nodes bsz=128' '1000 nodes bsz=128 (45)' --legend 'lower right' --yaxis test-accuracy --save-figure ../../figures/d-cliques-mnist-scaling-fully-connected-cst-bsz.png --ymin 80 --add-min-max
-         \begin{subfigure}[b]{0.48\textwidth}
-         \centering
-         \includegraphics[width=\textwidth]{figures/d-cliques-mnist-scaling-fully-connected-cst-bsz}
-         \caption{Constant Batch-Size}
-     \end{subfigure}
+%         % To regenerate the figure, from directory results/scaling
+%% python ../../../learn-topology/tools/plot_convergence.py 10/mnist/fully-connected-cliques/all/2021-03-10-14:40:35-CET ../mnist/fully-connected-cliques/all/2021-03-10-10:19:44-CET 1000/mnist/fully-connected-cliques/all/2021-03-10-16:44:35-CET --labels '10 nodes bsz=128' '100 nodes bsz=128' '1000 nodes bsz=128 (45)' --legend 'lower right' --yaxis test-accuracy --save-figure ../../figures/d-cliques-mnist-scaling-fully-connected-cst-bsz.png --ymin 80 --add-min-max
+%         \begin{subfigure}[b]{0.48\textwidth}
+%         \centering
+%         \includegraphics[width=\textwidth]{figures/d-cliques-mnist-scaling-fully-connected-cst-bsz}
+%         \caption{FCC: Constant Batch-Size}
+%     \end{subfigure}
+     
               % To regenerate the figure, from directory results/scaling
 % python ../../../learn-topology/tools/plot_convergence.py 10/mnist/fully-connected-cliques/all/2021-03-12-09:13:27-CET ../mnist/fully-connected-cliques/all/2021-03-10-10:19:44-CET 1000/mnist/fully-connected-cliques/all/2021-03-12-09:13:28-CET --labels '10 nodes bsz=1280' '100 nodes bsz=128' '1000 nodes bsz=13' --legend 'lower right' --yaxis test-accuracy --save-figure ../../figures/d-cliques-mnist-scaling-fully-connected-cst-updates.png --ymin 80 --add-min-max
-\hfill
-      \begin{subfigure}[b]{0.48\textwidth}
+
+      \begin{subfigure}[b]{0.7\textwidth}
          \centering
          \includegraphics[width=\textwidth]{figures/d-cliques-mnist-scaling-fully-connected-cst-updates}
-         \caption{Constant Nb Updates per Epoch}
+         \caption{Fully-Connected}
      \end{subfigure}
-     \caption{\label{fig:d-cliques-mnist-scaling-fully-connected} MNIST: Scaling Behaviour of Fully-Connected D-Clique}
+
+     
+     % To regenerate the figure, from directory results/scaling
+% python ../../../learn-topology/tools/plot_convergence.py 10/mnist/clique-ring/all/ ../mnist/clique-ring/all/ 1000/mnist/clique-ring/all/ --labels '10 nodes bsz=1280' '100 nodes bsz=128' '1000 nodes bsz=13' --legend 'lower right' --yaxis test-accuracy --save-figure ../../figures/d-cliques-mnist-scaling-clique-ring-cst-updates.png --ymin 80 --add-min-max
+         \begin{subfigure}[b]{0.7\textwidth}
+         \centering
+         \includegraphics[width=\textwidth]{figures/d-cliques-mnist-scaling-clique-ring-cst-updates}
+         \caption{Ring}
+     \end{subfigure}  
+     
+     \caption{\label{fig:d-cliques-mnist-scaling-fully-connected} MNIST: D-Clique Scaling Behaviour (Constant Updates per Epoch)}
      \end{figure}
      
 Show scaling effect for 10, 100, 1000 nodes (with decreasing sample sizes) for Clique Ring, Hierarchical, Fully-Connected.
@@ -365,6 +376,51 @@ In addition, it is important that all nodes are initialized with the same model
 \caption{\label{fig:d-cliques-cifar10-convolutional} D-Cliques with Convolutional Network on CIFAR10.}
 \end{figure}
 
+
+     
+    \begin{figure}[htbp]
+     \centering
+     % To regenerate the figure, from directory results/cifar10
+     % python ../../../learn-topology/tools/plot_convergence.py clique-ring/all/2021-03-10-11:58:43-CET no-init/clique-ring/all/2021-03-13-18:28:30-CET no-clique-avg/clique-ring/all/2021-03-13-18:27:09-CET  no-init-no-clique-avg/clique-ring/all/2021-03-13-18:29:58-CET --add-min-max --yaxis test-accuracy --labels 'with clique avg., with uniform init.' 'with clique avg., without uniform init.'  'without clique avg., with uniform init.'   'without clique avg., without uniform init.' --legend 'lower right' --ymax 75  --save-figure ../../figures/d-cliques-cifar10-init-clique-avg-effect-ring-test-accuracy.png  
+      \begin{subfigure}[b]{0.48\textwidth}
+         \centering
+         \includegraphics[width=\textwidth]{figures/d-cliques-cifar10-init-clique-avg-effect-ring-test-accuracy}
+         \caption{\label{fig:d-cliques-cifar10-init-clique-avg-effect-ring-test-accuracy} Ring}
+     \end{subfigure}
+     % To regenerate the figure, from directory results/cifar10
+     %python ../../../learn-topology/tools/plot_convergence.py fully-connected-cliques/all/2021-03-10-13:58:57-CET no-init/fully-connected-cliques/all/2021-03-13-18:32:55-CET no-clique-avg/fully-connected-cliques/all/2021-03-13-18:31:36-CET  no-init-no-clique-avg/fully-connected-cliques/all/2021-03-13-18:34:35-CET --add-min-max --yaxis test-accuracy --labels 'with clique avg., with uniform init.' 'with clique avg., without uniform init.'  'without clique avg., with uniform init.'   'without clique avg., without uniform init.' --legend 'lower right'  --ymax 75 --save-figure ../../figures/d-cliques-cifar10-init-clique-avg-effect-fcc-test-accuracy.png 
+       \begin{subfigure}[b]{0.48\textwidth}
+         \centering
+         \includegraphics[width=\textwidth]{figures/d-cliques-cifar10-init-clique-avg-effect-fcc-test-accuracy}
+         \caption{\label{fig:d-cliques-cifar10-init-clique-avg-effect-fcc-test-accuracy} Fully-Connected}
+     \end{subfigure}
+\caption{\label{fig:d-cliques-cifar10-init-clique-avg-effect} CIFAR10: Effects of Clique Averaging and Uniform Initialization on Convergence Speed. (100 nodes, non-IID, D-Cliques, bsz=20)}
+\end{figure}
+
+    \begin{figure}[htbp]
+     \centering   
+      \begin{subfigure}[b]{0.48\textwidth}
+         \centering
+         %\includegraphics[width=0.7\textwidth]{figures/d-cliques-cifar10-vs-1-node-test-accuracy}
+         \caption{\label{fig:cifar10-clique-clustering-ring} Ring}
+     \end{subfigure}
+       \begin{subfigure}[b]{0.48\textwidth}
+         \centering
+         %\includegraphics[width=0.7\textwidth]{figures/d-cliques-cifar10-vs-1-node-test-accuracy}
+         \caption{\label{fig:cifar10-clique-clustering-fcc} Fully-Connected}
+     \end{subfigure}
+\caption{\label{fig:d-cliques-cifar10-clique-clustering} CIFAR10: Effects of Clustering within Cliques on Convergence Speed.}
+\end{figure}
+
+     \begin{figure}[htbp]
+              % To regenerate the figure, from directory results/scaling
+% python ../../../learn-topology/tools/plot_convergence.py 10/cifar10/fully-connected-cliques/all/2021-03-12-09:13:27-CET ../cifar10/fully-connected-cliques/all/2021-03-10-10:19:44-CET 1000/cifar10/fully-connected-cliques/all/2021-03-12-09:13:28-CET --labels '10 nodes bsz=1280' '100 nodes bsz=128' '1000 nodes bsz=13' --legend 'lower right' --yaxis test-accuracy --save-figure ../../figures/d-cliques-cifar10-scaling-fully-connected-cst-updates.png --ymin 80 --add-min-max
+         \centering
+         %\includegraphics[width=\textwidth]{figures/d-cliques-cifar10-scaling-fully-connected-cst-updates}
+     \caption{\label{fig:d-cliques-cifar10-scaling-fully-connected} CIFAR10: Scaling Behaviour of Fully-Connected D-Clique (Constant Updates Per Epoch)}
+     \end{figure}
+
+
 \subsection{Comparison to similar topologies}
 
 Similar number of maximum hops but no or less clustering than D-Cliques (and no unbiasing of gradient).