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from .gfo_wrapper import _BaseOptimizer_ |
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def try_import_experimental_opt(): |
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try: |
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from experimental_optimization_strategies import ( |
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RandomAnnealingOptimizer as _RandomAnnealingOptimizer_, |
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ParallelAnnealingOptimizer as _ParallelAnnealingOptimizer_, |
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EnsembleOptimizer as _EnsembleOptimizer_, |
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LocalBayesianOptimizer as _LocalBayesianOptimizer_, |
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VariableResolutionBayesianOptimizer as _VariableResolutionBayesianOptimizer_, |
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EvoSubSpaceBayesianOptimizer as _EvoSubSpaceBayesianOptimizer_, |
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) |
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except ImportError as e: |
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pass |
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else: |
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class RandomAnnealingOptimizer(_BaseOptimizer_): |
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def __init__(self, **opt_params): |
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super().__init__(**opt_params) |
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self._OptimizerClass = _RandomAnnealingOptimizer_ |
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class ParallelAnnealingOptimizer(_BaseOptimizer_): |
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def __init__(self, **opt_params): |
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super().__init__(**opt_params) |
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self._OptimizerClass = _ParallelAnnealingOptimizer_ |
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class EnsembleOptimizer(_BaseOptimizer_): |
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def __init__(self, **opt_params): |
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super().__init__(**opt_params) |
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self._OptimizerClass = _EnsembleOptimizer_ |
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class LocalBayesianOptimizer(_BaseOptimizer_): |
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def __init__(self, **opt_params): |
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super().__init__(**opt_params) |
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self._OptimizerClass = _LocalBayesianOptimizer_ |
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class VariableResolutionBayesianOptimizer(_BaseOptimizer_): |
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def __init__(self, **opt_params): |
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super().__init__(**opt_params) |
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self._OptimizerClass = _VariableResolutionBayesianOptimizer_ |
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class EvoSubSpaceBayesianOptimizer(_BaseOptimizer_): |
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def __init__(self, **opt_params): |
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super().__init__(**opt_params) |
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self._OptimizerClass = _EvoSubSpaceBayesianOptimizer_ |
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