debug for new gpr
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@ -27,6 +27,8 @@ FLIP_PROB_DECAY = 0.5
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# ---GPR CONSTANTS---
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# ---GPR CONSTANTS---
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USE_GPFLOW = True
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USE_GPFLOW = True
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GPR_DEBUG = True
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DEFAULT_LENGTH_SCALE = 2.0
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DEFAULT_LENGTH_SCALE = 2.0
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DEFAULT_MAGNITUDE = 1.0
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DEFAULT_MAGNITUDE = 1.0
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@ -41,7 +41,7 @@ from website.settings import (USE_GPFLOW, DEFAULT_LENGTH_SCALE, DEFAULT_MAGNITUD
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ACTOR_HIDDEN_SIZES, CRITIC_HIDDEN_SIZES,
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ACTOR_HIDDEN_SIZES, CRITIC_HIDDEN_SIZES,
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DNN_TRAIN_ITER, DNN_EXPLORE, DNN_EXPLORE_ITER,
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DNN_TRAIN_ITER, DNN_EXPLORE, DNN_EXPLORE_ITER,
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DNN_NOISE_SCALE_BEGIN, DNN_NOISE_SCALE_END,
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DNN_NOISE_SCALE_BEGIN, DNN_NOISE_SCALE_END,
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DNN_DEBUG, DNN_DEBUG_INTERVAL)
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DNN_DEBUG, DNN_DEBUG_INTERVAL, GPR_DEBUG)
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from website.settings import INIT_FLIP_PROB, FLIP_PROB_DECAY
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from website.settings import INIT_FLIP_PROB, FLIP_PROB_DECAY
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from website.types import VarType
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from website.types import VarType
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@ -627,6 +627,7 @@ def configuration_recommendation(recommendation_input):
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opt_kwargs['learning_rate'] = DEFAULT_LEARNING_RATE
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opt_kwargs['learning_rate'] = DEFAULT_LEARNING_RATE
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opt_kwargs['maxiter'] = MAX_ITER
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opt_kwargs['maxiter'] = MAX_ITER
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opt_kwargs['bounds'] = [X_min, X_max]
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opt_kwargs['bounds'] = [X_min, X_max]
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opt_kwargs['debug'] = GPR_DEBUG
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ucb_beta = 'get_beta_td'
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ucb_beta = 'get_beta_td'
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opt_kwargs['ucb_beta'] = ucb.get_ucb_beta(ucb_beta, scale=DEFAULT_UCB_SCALE,
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opt_kwargs['ucb_beta'] = ucb.get_ucb_beta(ucb_beta, scale=DEFAULT_UCB_SCALE,
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t=i + 1., ndim=X_scaled.shape[1])
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t=i + 1., ndim=X_scaled.shape[1])
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