Updated experiments.sh for previous results to follow new directory conventions

results/cifar10/1-node-iid/experiments.sh

 #!/usr/bin/env bash
-TOOLS=../../../../learn-topology/tools; CWD="$(pwd)"; cd $TOOLS
+TOOLS=../../../../../Software/non-iid-topology-simulator/tools/v1; CWD="$(pwd)"; cd $TOOLS
 BSZS='
     2000
     '
@@ -8,7 +8,7 @@ LRS='
     '
 for BSZ in $BSZS; 
     do for LR in $LRS;
-        do python sgp-mnist.py --nb-nodes 1 --nb-epochs 100 --local-classes 10 --seed 1 --nodes-per-class 1 1 1 1 1 1 1 1 1 1 --global-train-ratios 1 1 1 1 1 1 1 1 1 1 --dist-optimization d-psgd --topology fully_connected --metric dissimilarity --learning-momentum 0.9 --sync-per-mini-batch 1 --results-directory $CWD/all --learning-rate $LR --batch-size $BSZ "$@" --single-process --dataset cifar10 --model gn-lenet --accuracy-logging-interval 10 --validation-set-ratio 0.5 --single-process --nb-logging-processes 1
+        do python simulate.py --nb-nodes 1 --nb-epochs 100 --local-classes 10 --seed 1 --nodes-per-class 1 1 1 1 1 1 1 1 1 1 --global-train-ratios 1 1 1 1 1 1 1 1 1 1 --dist-optimization d-psgd --topology fully_connected --metric dissimilarity --learning-momentum 0.9 --sync-per-mini-batch 1 --results-directory $CWD/all --learning-rate $LR --batch-size $BSZ "$@" --single-process --dataset cifar10 --model gn-lenet --accuracy-logging-interval 10 --validation-set-ratio 0.5 --single-process --nb-logging-processes 1
     done;
 done;
 

results/mnist/ring/iid/experiments.sh

 #!/usr/bin/env bash
-TOOLS=../../../../../learn-topology/tools; CWD="$(pwd)"; cd $TOOLS
+TOOLS=../../../../../../Software/non-iid-topology-simulator/tools/v1; CWD="$(pwd)"; cd $TOOLS
 BSZS='
     128
     '
@@ -8,7 +8,7 @@ LRS='
     '
 for BSZ in $BSZS; 
     do for LR in $LRS;
-        do python sgp-mnist.py --nb-nodes 100 --nb-epochs 100 --local-classes 10 --seed 1 --nodes-per-class 100 100 100 100 100 100 100 100 100 100 --global-train-ratios 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 --dist-optimization d-psgd --topology ring --metric random --learning-momentum 0. --sync-per-mini-batch 1 --results-directory $CWD/all --learning-rate $LR --batch-size $BSZ "$@" --parallel-training --nb-workers 10 --dataset mnist --model linear
+        do python simulate.py --nb-nodes 100 --nb-epochs 100 --local-classes 10 --seed 1 --nodes-per-class 100 100 100 100 100 100 100 100 100 100 --global-train-ratios 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 0.802568 --dist-optimization d-psgd --topology ring --metric random --learning-momentum 0. --sync-per-mini-batch 1 --results-directory $CWD/all --learning-rate $LR --batch-size $BSZ "$@" --parallel-training --nb-workers 10 --dataset mnist --model linear
     done;
 done;