run reddit dynamic jwins

eval/run_xtimes_reddit_rws.sh

@@ -54,7 +54,7 @@ export PYTHONFAULTHANDLER=1
 # Base configs for which the gird search is done
 # tests=("step_configs/config_reddit_sharing_topKdynamicGraph.ini")
 # tests=("step_configs/config_reddit_sharing_topKsharingasyncrw.ini" "step_configs/config_reddit_sharing_topKdpsgdrwasync.ini" "step_configs/config_reddit_sharing_topKdpsgdrw.ini")
-tests=("step_configs/config_reddit_sharing_dynamicGraph.ini") # ("step_configs/config_reddit_sharing_dpsgdrwasync0.ini")
+tests=("step_configs/config_reddit_sharing_dynamicGraphJwins.ini") # ("step_configs/config_reddit_sharing_dpsgdrwasync0.ini")
 # tests=("step_configs/config_reddit_sharing_dpsgdrw.ini" "step_configs/config_reddit_sharing_dpsgdrwasync.ini" "step_configs/config_reddit_sharing_sharingasyncrw.ini" "step_configs/config_reddit_sharing_sharingrw.ini")
 # Learning rates
 lr="1"
@@ -71,7 +71,7 @@ echo samples per user: $samples_per_user
 
 # random_seeds for which to rerun the experiments
 # random_seeds=("90" "91" "92" "93" "94")
-random_seeds=("90")
+random_seeds=("90" "91" "92")
 echo batchsize: $batchsize
 echo communication rounds per global epoch: $comm_rounds_per_global_epoch
 # calculating how many batches there are in a global epoch for each user/proc

eval/step_configs/config_reddit_sharing_dynamicGraphJwins.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Reddit
+dataset_class = Reddit
+random_seed = 97
+model_class = RNN
+train_dir = /mnt/nfs/shared/leaf/data/reddit_new/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/reddit_new/new_small_data/test
+; python list of fractions below
+sizes =
+
+[OPTIMIZER_PARAMS]
+optimizer_package = torch.optim
+optimizer_class = SGD
+lr = 0.001
+
+[TRAIN_PARAMS]
+training_package = decentralizepy.training.Training
+training_class = Training
+rounds = 47
+full_epochs = False
+batch_size = 16
+shuffle = True
+loss_package = torch.nn
+loss_class = CrossEntropyLoss
+
+[COMMUNICATION]
+comm_package = decentralizepy.communication.TCPRandomWalkRouting
+comm_class = TCPRandomWalkRouting
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.Eliaszfplossy1
+compression_class = Eliaszfplossy1
+compress = True
+sampler = equi
+
+[SHARING]
+sharing_package = decentralizepy.sharing.JwinsDynamicGraph
+sharing_class = JwinsDynamicGraph
+alpha=0.0833
+lower_bound=0.2
+metro_hastings=False
+change_based_selection = True
+wavelet=sym2
+level= None
+accumulation = True
+accumulate_averaging_changes = True
\ No newline at end of file