Wandb sweep and PyTorchLightning CLI

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I found the solution here : Multi-level nesting in yaml for sweeps

and I used the ${args_json_file} as parameter

So the resulting file look like :

program: training.py
method: grid
metric:
  goal: minimize
  name: val/loss.min
parameters:
  seed_everything:
    distribution: int_uniform
    max: 10
    min: 0
  model.class_path:
    value: models.zoo.LitGCN
  model.init_args.hidden_channels:
    values: [32, 64, 128, 256]
  model.init_args.gcn_num_layer:
    distribution: int_uniform
    min: 1
    max: 8
  model.init_args.mlp_num_layer:
    distribution: int_uniform
    min: 1
    max: 8
  model.init_args.dropout:
    values: [0.0, 0.1, 0.2, 0.3, 0.4, 0.5]
  model.init_args.learning_rate:
    values: [0.0001, 0.001, 0.01, 0.1]

command:
  - .venv/bin/python
  - ${program}
  - fit
  - -c
  - ${args_json_file}
  - -c=configs/data/sulcalgraphs_32_all-features.yaml
  - -c=configs/trainers/usual.yaml
  - -c=configs/lr_scheduler/reduce_on_plateau.yaml