diff --git a/inputJsonsFiles/ConnectionMap/conn_synt_distributed_w5_c3_6r_3s_3d.json b/inputJsonsFiles/ConnectionMap/conn_synt_distributed_w5_c3_6r_3s_3d.json index 4554b8bf4..7cd6c1f6a 100755 --- a/inputJsonsFiles/ConnectionMap/conn_synt_distributed_w5_c3_6r_3s_3d.json +++ b/inputJsonsFiles/ConnectionMap/conn_synt_distributed_w5_c3_6r_3s_3d.json @@ -6,6 +6,6 @@ "r3":["r4", "c1","s2"], "r4":["r5", "c2","s3"], "r5":["r6", "c3"], - "r6":["r3", "r4"] + "r6":["r3", "r4", "r1"] } } diff --git a/inputJsonsFiles/DistributedConfig/dc_AEC_1d_2c_1s_4r_4w.json b/inputJsonsFiles/DistributedConfig/dc_AEC_1d_2c_1s_4r_4w.json index 8e55a7f8b..16887b6b1 100644 --- a/inputJsonsFiles/DistributedConfig/dc_AEC_1d_2c_1s_4r_4w.json +++ b/inputJsonsFiles/DistributedConfig/dc_AEC_1d_2c_1s_4r_4w.json @@ -54,14 +54,64 @@ { "name": "c1", "port": "8083", - "workers": "" + "workers": "w1,w2" }, { "name": "c2", "port": "8084", - "workers": "" + "workers": "w3,w4" } ], - "workers": [], - "model_sha": {} + "workers": [ + { + "name": "w1", + "model_sha": "d8df752e0a2e8f01de8f66e9cec941cdbc65d144ecf90ab7713e69d65e7e82aa" + }, + { + "name": "w2", + "model_sha": "d8df752e0a2e8f01de8f66e9cec941cdbc65d144ecf90ab7713e69d65e7e82aa" + }, + { + "name": "w3", + "model_sha": "d8df752e0a2e8f01de8f66e9cec941cdbc65d144ecf90ab7713e69d65e7e82aa" + }, + { + "name": "w4", + "model_sha": "d8df752e0a2e8f01de8f66e9cec941cdbc65d144ecf90ab7713e69d65e7e82aa" + } + ], + "model_sha": { + "d8df752e0a2e8f01de8f66e9cec941cdbc65d144ecf90ab7713e69d65e7e82aa": { + "modelType": "9", + "_doc_modelType": " nn:0 | approximation:1 | classification:2 | forecasting:3 | image-classification:4 | text-classification:5 | text-generation:6 | auto-association:7 | autoencoder:8 | ae-classifier:9 |", + "modelArgs": "", + "layersSizes": "64,32,16,8,16,32,64,64", + "_doc_layersSizes": "List of postive integers [L0, L1, ..., LN]", + "layerTypesList": "1,3,3,3,3,3,3,10", + "_doc_LayerTypes": " Default:0 | Scaling:1 | CNN:2 | Perceptron:3 | Pooling:4 | Probabilistic:5 | LSTM:6 | Reccurrent:7 | Unscaling:8 |", + "layers_functions": "1,6,6,6,6,6,6,1", + "_doc_layers_functions_activation": " Threshold:1 | Sign:2 | Logistic:3 | Tanh:4 | Linear:5 | ReLU:6 | eLU:7 | SeLU:8 | Soft-plus:9 | Soft-sign:10 | Hard-sigmoid:11 |", + "_doc_layer_functions_pooling": " none:1 | Max:2 | Avg:3 |", + "_doc_layer_functions_probabilistic": " Binary:1 | Logistic:2 | Competitive:3 | Softmax:4 |", + "_doc_layer_functions_scaler": " none:1 | MinMax:2 | MeanStd:3 | STD:4 | Log:5 |", + "lossMethod": "6", + "_doc_lossMethod": " SSE:1 | MSE:2 | NSE:3 | MinkowskiE:4 | WSE:5 | CEE:6 |", + "lr": "0.01", + "_doc_lr": "Positve float", + "epochs": "1", + "_doc_epochs": "Positve Integer", + "optimizer": "5", + "_doc_optimizer": " GD:0 | CGD:1 | SGD:2 | QuasiNeuton:3 | LVM:4 | ADAM:5 |", + "optimizerArgs": "", + "_doc_optimizerArgs": "String", + "infraType": "0", + "_doc_infraType": " opennn:0 | wolfengine:1 |", + "distributedSystemType": "0", + "_doc_distributedSystemType": " none:0 | fedClientAvg:1 | fedServerAvg:2 |", + "distributedSystemArgs": "", + "_doc_distributedSystemArgs": "String", + "distributedSystemToken": "none", + "_doc_distributedSystemToken": "Token that associates distributed group of workers and parameter-server" + } + } } \ No newline at end of file diff --git a/inputJsonsFiles/DistributedConfig/dc_dist_2d_3c_2s_3r_6w.json b/inputJsonsFiles/DistributedConfig/dc_dist_2d_3c_2s_3r_6w.json index 958ea78fa..9d80fa85e 100644 --- a/inputJsonsFiles/DistributedConfig/dc_dist_2d_3c_2s_3r_6w.json +++ b/inputJsonsFiles/DistributedConfig/dc_dist_2d_3c_2s_3r_6w.json @@ -18,8 +18,8 @@ "entities": "mainServer,c1,c2,r1,r2,s1,apiServer" }, { - "name": "c0vm1", - "ipv4": "10.0.0.4", + "name": "minionms", + "ipv4": "10.0.0.31", "entities": "c3,r3,s2" } ], diff --git a/inputJsonsFiles/experimentsFlow/exp_AEC_1d_2c_1s_4r_4w.json b/inputJsonsFiles/experimentsFlow/exp_AEC_1d_2c_1s_4r_4w.json new file mode 100644 index 000000000..206cec585 --- /dev/null +++ b/inputJsonsFiles/experimentsFlow/exp_AEC_1d_2c_1s_4r_4w.json @@ -0,0 +1,40 @@ +{ + "experimentName": "anomaly_detection_skab", + "experimentType": "classification", + "batchSize": 100, + "csvFilePath": "/tmp/nerlnet/data/NerlnetData-master/nerlnet/skab/skab_full.csv", + "numOfFeatures": "8", + "numOfLabels": "1", + "headersNames": "Anomaly", + "Phases": + [ + { + "phaseName": "training_phase", + "phaseType": "training", + "sourcePieces": + [ + { + "sourceName": "s1", + "startingSample": "0", + "numOfBatches": "120", + "workers": "w1,w2,w3,w4", + "nerltensorType": "float" + } + ] + }, + { + "phaseName": "prediction_phase", + "phaseType": "prediction", + "sourcePieces": + [ + { + "sourceName": "s1", + "startingSample": "12000", + "numOfBatches": "60", + "workers": "w1,w2,w3,w4", + "nerltensorType": "float" + } + ] + } +] +}