configs/mnist/agg_ensemble.yaml [46:89]:
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    optim:
        class_name: torch.optim.Adadelta
        lr: 1.
    model:
        class_name: crlapi.sl.architectures.mlp.MLP
        size_layers: 64
        n_layers: 2
     
    kornia_augs:

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/mnist/kensemble.yaml [46:89]:
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    optim:
        class_name: torch.optim.Adadelta
        lr: 1.
    model:
        class_name: crlapi.sl.architectures.mlp.MLP
        size_layers: 64
        n_layers: 2
     
    kornia_augs:

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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