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Higher epsilon to deal with numerical instabilities

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Dominik Moritz Roth 2022-08-17 19:31:54 +02:00
parent 64a7d5ec59
commit 86e6bfb65b
1 changed files with 1 additions and 1 deletions
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metastable_baselines/distributions/distributions.py
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@ -143,7 +143,7 @@ class UniversalGaussianDistribution(SB3_Distribution):
:param action_dim: Dimension of the action space.
"""
def __init__(self, action_dim: int, use_sde: bool = False, neural_strength: Strength = Strength.DIAG, cov_strength: Strength = Strength.DIAG, parameterization_type: ParametrizationType = ParametrizationType.NONE, enforce_positive_type: EnforcePositiveType = EnforcePositiveType.ABS, prob_squashing_type: ProbSquashingType = ProbSquashingType.NONE, epsilon=1e-6, sde_learn_features=False):
def __init__(self, action_dim: int, use_sde: bool = False, neural_strength: Strength = Strength.DIAG, cov_strength: Strength = Strength.DIAG, parameterization_type: ParametrizationType = ParametrizationType.NONE, enforce_positive_type: EnforcePositiveType = EnforcePositiveType.ABS, prob_squashing_type: ProbSquashingType = ProbSquashingType.NONE, epsilon=1e-3, sde_learn_features=False):
super(UniversalGaussianDistribution, self).__init__()
self.action_dim = action_dim
self.par_strength = cast_to_enum(neural_strength, Strength)