more experiments wv

eval/run_xtimes_femnist_alphas.sh

@@ -70,7 +70,7 @@ echo samples per user: $samples_per_user
 #random_seeds=("90" "91" "92" "93" "94")
 random_seeds=("97")
 # "bior2.2" "rbio2.2"
-alphas=("0.0091" "0.0455" "0.182" "0.273") #
+alphas=("0.91" "0.182" "0.273") #"0.0091" "0.0455"
 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_femnist_sharing_16bit.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.Elias16f
+compression_class = Elias16f
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.Sharing
+sharing_class = Sharing

eval/step_configs/config_femnist_sharing_fzip14.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.EliasFpzipLossy14
+compression_class = EliasFpzipLossy14
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.Sharing
+sharing_class = Sharing

eval/step_configs/config_femnist_sharing_fzip18.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.EliasFpzipLossy
+compression_class = EliasFpzipLossy
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.Sharing
+sharing_class = Sharing

eval/step_configs/config_femnist_sharing_q8.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.Elias8bitQuant
+compression_class = Elias8bitQuant
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.Sharing
+sharing_class = Sharing

eval/step_configs/config_femnist_topkacc_16bit.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/data/test
+; python list of fractions below
+sizes =
+
+[OPTIMIZER_PARAMS]
+optimizer_package = torch.optim
+optimizer_class = SGD
+lr = 0.001
+
+# There are 734463 femnist samples
+[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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.Elias16f
+compression_class = Elias16f
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.PartialModel
+sharing_class = PartialModel
+alpha = 0.1
+accumulation = True
+accumulate_averaging_changes = True
\ No newline at end of file

eval/step_configs/config_femnist_topkacc_fzp14.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/data/test
+; python list of fractions below
+sizes =
+
+[OPTIMIZER_PARAMS]
+optimizer_package = torch.optim
+optimizer_class = SGD
+lr = 0.001
+
+# There are 734463 femnist samples
+[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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.EliasFpzipLossy14
+compression_class = EliasFpzipLossy14
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.PartialModel
+sharing_class = PartialModel
+alpha = 0.1
+accumulation = True
+accumulate_averaging_changes = True
\ No newline at end of file

eval/step_configs/config_femnist_topkacc_fzp18.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/data/test
+; python list of fractions below
+sizes =
+
+[OPTIMIZER_PARAMS]
+optimizer_package = torch.optim
+optimizer_class = SGD
+lr = 0.001
+
+# There are 734463 femnist samples
+[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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.EliasFpzipLossy
+compression_class = EliasFpzipLossy
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.PartialModel
+sharing_class = PartialModel
+alpha = 0.1
+accumulation = True
+accumulate_averaging_changes = True
\ No newline at end of file

eval/step_configs/config_femnist_topkacc_q8.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/data/test
+; python list of fractions below
+sizes =
+
+[OPTIMIZER_PARAMS]
+optimizer_package = torch.optim
+optimizer_class = SGD
+lr = 0.001
+
+# There are 734463 femnist samples
+[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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.Elias8bitQuant
+compression_class = Elias8bitQuant
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.PartialModel
+sharing_class = PartialModel
+alpha = 0.1
+accumulation = True
+accumulate_averaging_changes = True
\ No newline at end of file

eval/step_configs/config_femnist_wavelet_16bit.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/data/test
+; python list of fractions below
+sizes = 
+
+[OPTIMIZER_PARAMS]
+optimizer_package = torch.optim
+optimizer_class = SGD
+lr = 0.001
+
+# There are 734463 femnist samples
+[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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.Elias16f
+compression_class = Elias16f
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.Wavelet
+sharing_class = Wavelet
+change_based_selection = True
+alpha = 0.1
+wavelet=rbio2.2
+level= None
+accumulation = True
+accumulate_averaging_changes = True

eval/step_configs/config_femnist_wavelet_fzp14.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/data/test
+; python list of fractions below
+sizes = 
+
+[OPTIMIZER_PARAMS]
+optimizer_package = torch.optim
+optimizer_class = SGD
+lr = 0.001
+
+# There are 734463 femnist samples
+[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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.EliasFpzipLossy14
+compression_class = EliasFpzipLossy14
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.Wavelet
+sharing_class = Wavelet
+change_based_selection = True
+alpha = 0.1
+wavelet=rbio2.2
+level= None
+accumulation = True
+accumulate_averaging_changes = True

eval/step_configs/config_femnist_wavelet_fzp18.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/data/test
+; python list of fractions below
+sizes = 
+
+[OPTIMIZER_PARAMS]
+optimizer_package = torch.optim
+optimizer_class = SGD
+lr = 0.001
+
+# There are 734463 femnist samples
+[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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.EliasFpzipLossy
+compression_class = EliasFpzipLossy
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.Wavelet
+sharing_class = Wavelet
+change_based_selection = True
+alpha = 0.1
+wavelet=rbio2.2
+level= None
+accumulation = True
+accumulate_averaging_changes = True

eval/step_configs/config_femnist_wavelet_q8.ini

+[DATASET]
+dataset_package = decentralizepy.datasets.Femnist
+dataset_class = Femnist
+random_seed = 97
+model_class = CNN
+train_dir = /mnt/nfs/shared/leaf/data/femnist/per_user_data/train
+test_dir = /mnt/nfs/shared/leaf/data/femnist/data/test
+; python list of fractions below
+sizes = 
+
+[OPTIMIZER_PARAMS]
+optimizer_package = torch.optim
+optimizer_class = SGD
+lr = 0.001
+
+# There are 734463 femnist samples
+[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.TCP
+comm_class = TCP
+addresses_filepath = ip_addr_6Machines.json
+compression_package = decentralizepy.compression.Elias8bitQuant
+compression_class = Elias8bitQuant
+compress = True
+
+[SHARING]
+sharing_package = decentralizepy.sharing.Wavelet
+sharing_class = Wavelet
+change_based_selection = True
+alpha = 0.1
+wavelet=rbio2.2
+level= None
+accumulation = True
+accumulate_averaging_changes = True