fc-deep-learning/config.yml at master · FeatureCloud/fc-deep-learning · GitHub

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fc_deep:
  local_dataset:
    train: "train.npz"
    test: "test.npz"
#    train: "train.npz"
#    test: "test.npz"
#    central_test: "mnist.npz"
    central_test: null
#    detail: {} ## no detail should be an empty dict.
    detail:
      sep: ','
      label: "Group"
    init_model: "model.pt"

  centralized: True

  simulation:
    clients_dir: c1,c2,c3 # Comma separated list of clients' directories

  logic:
#    mode: "file"
#    dir: "."
    mode: "directory"
    dir: "data"


  result:
    pred: "y_pred.csv"
    target: "y_test.csv"
    model: "model.pt"


  fed_hyper_params:
    max_iter: 1
    n_classes: 10
    federated_model: 'FedAvg.py'
    global_updates: WEIGHTS_STOPPING
    param: { }


  use_smpc: True

  trainer:
    name: 'FedMMB.py'
    param: {}
    local_update: WEIGHTS_N_SAMPLES
    data_loader: ImageLoader # True: using torchvision Dataloader, False using custom Dataloader
    optimizer:
      name: 'SGD'
      param:
        lr: 0.1
    loss:
      name: 'focal_loss.py'
      #      param: null
      param:
        alpha:
          - 0.2
          - 0.3
          - 0.3
          - 0.2
        gamma: 1.1
    metrics:
      - name: 'Accuracy'
        package: 'torchmetrics.classification'
        param:
          task: 'multiclass'
          num_classes: 4

  train_config:
    verbose: False
    batch_size: 32
    test_batch_size: 32
    epochs: 1
    lr: 0.1
    batch_count: 1
    device: gpu # options{gpu, cpu}


  #      - name: 'RMSE'
#        params: null


  model: # 'cnn' or 'cnn.py' or layers_dict
    name: 'cnn.py'
    n_classes: 10
    in_features: 1
#    name: 'cnn'
#    n_classes: 10
#    - type: 'Conv2d'
#      param:
#        in_channels: None
#        out_channels: 32
#        kernel_size: 3
#        stride: 1
#        padding: 1
#        bias: True
#    - type: 'MaxPool2d'
#      param:
#        kernel_size: 2
#        stride: 2
#    - type: 'ReLU'
#    - type: 'Conv2d'
#      param:
#        in_channels: 32
#        out_channels: 64
#    - type: 'MaxPool2d'
#    - type: 'ReLU'
#    - type: 'Flatten'
#    - type: 'Linear'
#      param:
#        in_features: None
#        out_features: 128
#        bias: True
#    - type: 'ReLU'
#    - type: 'Linear'
#      param:
#        in_features: 128
#        out_features: 10