MLproject

name: flooding-experiments

# conda_env: conda.yaml

entry_points:
  synthetic:
    parameters:
      dataset: {type: str, default: 'gaussian'}
      label_noise: {type: float, default: 0.0}
      noise_level: {type: float, default: 0.0}
      gradient_norm: {type: float, default: -1.0}
      learning_rate: {type: float, default: 0.001}
      batch_size_tr: {type: integer, default: 200}
      batch_size_te: {type: integer, default: 500}
      training_samples: {type: integer, default: 100}
      validation_samples: {type: integer, default: 100}
      dimension: {type: integer, default: 10}
      model: {type: string, default: 'mlp_model'}
      middle_dim: {type: integer, default: 100}
      optimizer: {type: string, default: 'sgd'}
      epochs: {type: integer, default: 100}
      weight_decay: {type: float, default: 0.0}
      momentum: {type: float, default: 0.0}
      flood_level: {type: float, default: 0.0}
      negative_gaussian_mean: {type: float, default: 1.0}
      random_seed: {type: integer, default: 0}
      gpu_id: {type: integer, default: 0}
      tags: {type: string, default: ""}
      labels: {type: string, default: "synthetic"}      
      save_model: {type: string, default: "False"}                
    command: "python -m synthetic.demo_synth -ds {dataset} -ln {label_noise} -nl {noise_level} -gn {gradient_norm} -lr {learning_rate} -bstr {batch_size_tr} -bste {batch_size_te} -ts {training_samples} -vs {validation_samples} -d {dimension} -m {model} -md {middle_dim} -e {epochs} -wd {weight_decay} -mm {momentum} -fl {flood_level} -ngm {negative_gaussian_mean} -rs {random_seed} -tg {tags} -lb {labels} -opt {optimizer} -gpu {gpu_id} -sm {save_model}"