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I tried to change k(the number of parities) from 2 to 4, and simply config the model as follows (copy the original model): { "epochs": 1, "lr": 0.01, "k": 4, "batch_size": 1024, "communication": { "communication_protocol": "FedSGD", "iteration_per_aggregation": 1 }, "dataset": { "dataset_name": "mnist", "num_classes": 10 }, "model_list": { "0": { "type": "MLP2", "input_dim": 392, "output_dim": 10, "path": "random_1428_10" }, "1": { "type": "MLP2", "input_dim": 392, "output_dim": 10, "path": "random_1428_10" }, "2": { "type": "MLP2", "input_dim": 392, "output_dim": 10, "path": "random_1428_10" }, "3": { "type": "MLP2", "input_dim": 392, "output_dim": 10, "path": "random_1428_10" }, "apply_trainable_layer": 1, "global_model": "ClassificationModelHostTrainableHead" }, "defense": { "name": "GaussianDP", "parameters": { "party": [ 1 ], "dp_strength": 0.0001 } }, "attack_list": { "0": { "name": "BatchLabelReconstruction", "parameters": { "party": [ 0 ], "lr": 0.05, "epochs": 10000 } }, "1": { "name": "DirectLabelScoring", "parameters": { "party": [ 0 ] } } } } then I found the matrix shapes don't match So I change the matrix shapes for all 4 models from 392*10 to 192 * 10, but it still does't work. Could you please tell me how to modify the model list, thanks!
The text was updated successfully, but these errors were encountered:
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I tried to change k(the number of parities) from 2 to 4, and simply config the model as follows (copy the original model):
{
"epochs": 1,
"lr": 0.01,
"k": 4,
"batch_size": 1024,
"communication": {
"communication_protocol": "FedSGD",
"iteration_per_aggregation": 1
},
"dataset": {
"dataset_name": "mnist",
"num_classes": 10
},
"model_list": {
"0": {
"type": "MLP2",
"input_dim": 392,
"output_dim": 10,
"path": "random_1428_10"
},
"1": {
"type": "MLP2",
"input_dim": 392,
"output_dim": 10,
"path": "random_1428_10"
},
"2": {
"type": "MLP2",
"input_dim": 392,
"output_dim": 10,
"path": "random_1428_10"
},
"3": {
"type": "MLP2",
"input_dim": 392,
"output_dim": 10,
"path": "random_1428_10"
},
"apply_trainable_layer": 1,
"global_model": "ClassificationModelHostTrainableHead"
},
"defense": {
"name": "GaussianDP",
"parameters": {
"party": [
1
],
"dp_strength": 0.0001
}
},
"attack_list": {
"0": {
"name": "BatchLabelReconstruction",
"parameters": {
"party": [
0
],
"lr": 0.05,
"epochs": 10000
}
},
"1": {
"name": "DirectLabelScoring",
"parameters": {
"party": [
0
]
}
}
}
}
then I found the matrix shapes don't match
So I change the matrix shapes for all 4 models from 392*10 to 192 * 10, but it still does't work.
Could you please tell me how to modify the model list, thanks!
The text was updated successfully, but these errors were encountered: