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manual/sweep_example.txt

+method: grid
+metric:
+  goal: minimize
+  name: val_loss
+early_terminate:
+  type: hyperband
+  min_iter: 3
+  eta: 2
+parameters:
+  image_max:
+    distribution: categorical
+    values:
+    - 1
+    - 2
+  images_gpu:
+    distribution: categorical
+    values:
+    - 1
+    - 2
+  learning:
+    distribution: categorical
+    values:
+    - 2
+    - 3
+  epochs:
+    distribution: constant
+    value: 30
+  early_stopping:
+    distribution: constant
+    value: 5
+  k_fold:
+    distribution: constant
+    value: 5
+  k_fold_val:
+    distribution: constant
+    value: 0
+  dataset_path:
+    distribution: constant
+    value: test_path
+  name_result_file:
+    distribution: constant
+    value: test_result
+  new_weights_path:
+    distribution: constant
+    value: test_sweep_
+  use_wandb:
+    distribution: constant
+    value: True
+  wandb_entity:
+    distribution: constant
+    value: "test_entity"
+  wandb_project:
+    distribution: constant
+    value: "test_project"
+  wandb_group:
+    distribution: constant
+    value: "test_group"
+  wandb_name:
+    distribution: constant
+    value: test_sweep
+program: train_droplet.py
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