configs/unstructured_sparsity/lcs_p.yaml [5:17]:
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parameters:
  regime: "sparse"
  dataset: "cifar10"
  script: "train_indep.py"
  save_dir: "saved_models/unstructured_sparsity/"
  epochs: 200 # The number of epochs to train for
  batch_size: 128 # Train and test batch sizes
  warmup_budget: 80 # decays topk from 1 to target topk over this percentage of epochs
  test_freq: 20 # Will run test after this many epochs
  learning_rate: 0.1 # Optimizer learning rate
  momentum: 0.9 # Optimizer momentum
  weight_decay: 0.0005 # L2 regularization parameter
  conv_type: "StandardConv" # convolution layer for first layer of network
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configs/unstructured_sparsity/target_topk.yaml [5:17]:
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parameters:
  regime: "sparse"
  dataset: "cifar10"
  script: "train_indep.py"
  save_dir: "saved_models/unstructured_sparsity/"
  epochs: 200 # The number of epochs to train for
  batch_size: 128 # Train and test batch sizes
  warmup_budget: 80 # decays topk from 1 to the target over this percentage of epochs
  test_freq: 20 # Will run test after this many epochs
  learning_rate: 0.1 # Optimizer learning rate
  momentum: 0.9 # Optimizer momentum
  weight_decay: 0.0005 # L2 regularization parameter
  conv_type: "StandardConv"
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