Пример #1
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 def get_knob_config():
     return {
         'learning_rate': FloatKnob(1e-2, 1e-1, is_exp=True),
         'num_leaves': IntegerKnob(20, 60),
         'colsample_bytree': FloatKnob(1e-1, 1),
         'subsample': FloatKnob(1e-1, 1),
         'max_depth': IntegerKnob(1, 10),
     }
Пример #2
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 def get_knob_config():
     return {
         'n_estimators': IntegerKnob(50, 200),
         'min_child_weight': IntegerKnob(1, 6),
         'max_depth': IntegerKnob(1, 10),
         'gamma': FloatKnob(0.0, 1.0, is_exp=False),
         'subsample': FloatKnob(0.5, 1.0, is_exp=False),
         'colsample_bytree': FloatKnob(0.1, 0.7, is_exp=False)
     }
Пример #3
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 def get_knob_config():
     return {
         'alpha': FloatKnob(0.001, 0.01),
         'normalize': CategoricalKnob([True, False]),
         'copy_X': CategoricalKnob([True, False]),
         'tol': FloatKnob(1e-05, 1e-04),
         'solver': CategoricalKnob(['svd', 'sag']),
         'random_state': IntegerKnob(1, 123)
     }
Пример #4
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 def get_knob_config():
     return {
         'epochs': FixedKnob(15),
         'learning_rate': FloatKnob(0.001, 0.07),
         'decay_rate': FloatKnob(5e-5, 1e-4, is_exp=True),
         'momentum': FloatKnob(0.1, 0.3, 0.6),
         'batch_size': CategoricalKnob([32, 64, 128]),
         'max_image_size': FixedKnob(28)
     }
Пример #5
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 def get_knob_config():
     return {
         'epochs': FixedKnob(1),
         'word_embed_dims': IntegerKnob(16, 128),
         'word_rnn_hidden_size': IntegerKnob(16, 128),
         'word_dropout': FloatKnob(1e-3, 2e-1, is_exp=True),
         'learning_rate': FloatKnob(1e-2, 1e-1, is_exp=True),
         'batch_size': CategoricalKnob([16, 32, 64, 128]),
     }
Пример #6
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 def get_knob_config():
     return {
         'criterion': CategoricalKnob(['mse', 'mae']),
         'splitter': CategoricalKnob(['best', 'random']),
         'min_samples_split': IntegerKnob(2, 5),
         'max_features': CategoricalKnob(['auto', 'sqrt']),
         'random_state': IntegerKnob(1, 123),
         'min_impurity_decrease': FloatKnob(0.0, 0.2),
         'min_impurity_split': FloatKnob(1e-07, 1e-03)
     }
Пример #7
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 def get_knob_config():
     return {
         'C': IntegerKnob(2, 3),
         'kernel': CategoricalKnob(['poly', 'rbf', 'linear']),
         'degree': IntegerKnob(2, 3),
         'gamma': CategoricalKnob(['scale', 'auto']),
         'coef0': FloatKnob(0.0, 0.1),
         'shrinking': CategoricalKnob([True, False]),
         'tol': FloatKnob(1e-03, 1e-01, is_exp=True),
         'decision_function_shape': CategoricalKnob(['ovo', 'ovr']),
         'probability': CategoricalKnob([True, False]),
     }
Пример #8
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 def get_knob_config():
     return {
         'C': FloatKnob(1.0, 1.5),
         'tol': FloatKnob(1e-03, 1e-01, is_exp=True),
         'validation_fraction': FloatKnob(0.01, 0.1),
         'n_iter_no_change': IntegerKnob(3, 5),
         'shuffle': CategoricalKnob([True, False]),
         'loss': CategoricalKnob(['hinge', 'squared_hinge']),
         'random_state': IntegerKnob(1, 2),
         'warm_start': CategoricalKnob([True, False]),
         'average': IntegerKnob(1, 5),
     }
Пример #9
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 def get_knob_config():
     return {
         'max_epochs': FixedKnob(10),
         'learning_rate': FloatKnob(1e-5, 1e-2, is_exp=True),
         'batch_size': CategoricalKnob([16, 32, 64, 128]),
         'max_image_size': CategoricalKnob([32, 64, 128, 224]),
     }
Пример #10
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 def get_knob_config():
     return {
         'epochs': FixedKnob(15),
         'batch_size': CategoricalKnob([32, 64, 128]),
         'l_rate': FloatKnob(0.0001, 0.001, 0.01),
         'max_image_size': CategoricalKnob([28, 32])
     }
Пример #11
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 def get_knob_config():
     return {
         'penalty': CategoricalKnob(['l1', 'l2']),
         'tol': FloatKnob(0.0001, 0.001),
         'C': IntegerKnob(4, 15),
         'fit_intercept': CategoricalKnob([True, False]),
         'solver': CategoricalKnob(['lbfgs', 'liblinear']),
     }
Пример #12
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    def get_knob_config():
        return {
            'trial_epochs': FixedKnob(300),
            'lr': FloatKnob(1e-4, 1, is_exp=True),
            'lr_decay': FloatKnob(1e-3, 1e-1, is_exp=True),
            'opt_momentum': FloatKnob(0.7, 1, is_exp=True),
            'opt_weight_decay': FloatKnob(1e-5, 1e-3, is_exp=True),
            'batch_size': CategoricalKnob([32, 64, 128]),
            'drop_rate': FloatKnob(0, 0.4),
            'max_image_size': FixedKnob(32),
            'share_params': PolicyKnob('SHARE_PARAMS'),

            # Affects whether training is shortened by using early stopping
            'quick_train': PolicyKnob('EARLY_STOP'),
            'early_stop_train_val_samples': FixedKnob(1024),
            'early_stop_patience_epochs': FixedKnob(5)
        }
Пример #13
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 def get_knob_config():
     return {
         'max_iter': FixedKnob(20),
         'kernel': CategoricalKnob(['rbf', 'linear', 'poly']),
         'gamma': CategoricalKnob(['scale', 'auto']),
         'C': FloatKnob(1e-4, 1e4, is_exp=True),
         'max_image_size': CategoricalKnob([16, 32])
     }
Пример #14
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 def get_knob_config():
     return {
         'max_epochs': FixedKnob(10),
         'hidden_layer_count': IntegerKnob(1, 2),
         'hidden_layer_units': IntegerKnob(2, 128),
         'learning_rate': FloatKnob(1e-5, 1e-1, is_exp=True),
         'batch_size': CategoricalKnob([16, 32, 64, 128]),
         'max_image_size': CategoricalKnob([16, 32, 48]),
         'quick_train':
         PolicyKnob('EARLY_STOP')  # Whether early stopping would be used
     }
Пример #15
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 def get_knob_config():
     return {
         'c1': FloatKnob(0.001, 0.01),
         'c2': FloatKnob(0.01, 0.1),
         'max_iterations': FixedKnob(10)
     }
Пример #16
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 def get_knob_config():
     return {
         'var_smoothing': FloatKnob(1e-07, 1e-05, is_exp=True),
     }
Пример #17
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 def get_knob_config():
     return {
         'epoch': IntegerKnob(5, 10),
         'learning_rate': FloatKnob(1e-3, 1e-1, is_exp=True),
         'layer_dim': CategoricalKnob([50, 100, 250])
     }
Пример #18
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 def get_knob_config():
     return {
         'var_smoothing': FloatKnob(1e-07, 1e-05),
     }