configs/cifar10/agg_ensemble_vgg.yaml [24:96]:
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    k: 3
    vote: False
    
    init_from_scratch: False
    cache_dl: True
    training_batch_size: 128
    training_num_workers: 4

    validation_proportion: 0.1
    validation_batch_size: 512
    validation_num_workers: 4
    
    train_replay_proportion: ${replay}
    validation_replay_proportion: ${replay}

    max_epochs: 100
    device: ${device}

    patience: 100
    patience_delta: 0.001

    optim:
        class_name: torch.optim.SGD
        lr: 0.01
        momentum: 0.9
        weight_decay: 1e-4

    model:
        class_name: crlapi.sl.architectures.vgg.VGG
        n_channels: 16
     
    kornia_augs:
      - name: RandomCrop
        size: [32, 32]
        padding: 4
        fill: -1.9
      - name: RandomHorizontalFlip
        p:    0.5

evaluation:
    mode: all_tasks
    batch_size: 512
    num_workers: 2
    device: ${device}

device: 'cuda'
data_dir: ~/.avalanche/data/ #/Users/denoyer/workspace/.data

# --- SLURM configuration
time: 1000
gpus: 1
partition: learnfair
n_megabatches: 2
replay: 0

hydra:
  launcher:
    nodes: 1
    mem_gb: 64
    max_num_timeout: 3
    cpus_per_task: 10
    signal_delay_s: 30
    timeout_min: ${time}
    gpus_per_node: ${gpus}
    tasks_per_node: ${gpus}
    submitit_folder: '/checkpoint/lucaspc/grow_moe_refac/output'
    partition: ${partition}
  job_logging:
    root:
      handlers: []

defaults:
  - hydra/launcher: submitit_slurm
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configs/cifar10/kensemble_vgg.yaml [24:96]:
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    k: 3
    vote: False
    
    init_from_scratch: False
    cache_dl: True
    training_batch_size: 128
    training_num_workers: 4

    validation_proportion: 0.1
    validation_batch_size: 512
    validation_num_workers: 4
    
    train_replay_proportion: ${replay}
    validation_replay_proportion: ${replay}

    max_epochs: 100
    device: ${device}

    patience: 100
    patience_delta: 0.001

    optim:
        class_name: torch.optim.SGD
        lr: 0.01
        momentum: 0.9
        weight_decay: 1e-4

    model:
        class_name: crlapi.sl.architectures.vgg.VGG
        n_channels: 16
     
    kornia_augs:
      - name: RandomCrop
        size: [32, 32]
        padding: 4
        fill: -1.9
      - name: RandomHorizontalFlip
        p:    0.5

evaluation:
    mode: all_tasks
    batch_size: 512
    num_workers: 2
    device: ${device}

device: 'cuda'
data_dir: ~/.avalanche/data/ #/Users/denoyer/workspace/.data

# --- SLURM configuration
time: 1000
gpus: 1
partition: learnfair
n_megabatches: 2
replay: 0

hydra:
  launcher:
    nodes: 1
    mem_gb: 64
    max_num_timeout: 3
    cpus_per_task: 10
    signal_delay_s: 30
    timeout_min: ${time}
    gpus_per_node: ${gpus}
    tasks_per_node: ${gpus}
    submitit_folder: '/checkpoint/lucaspc/grow_moe_refac/output'
    partition: ${partition}
  job_logging:
    root:
      handlers: []

defaults:
  - hydra/launcher: submitit_slurm
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