syne_tune/optimizer/schedulers/searchers/bayesopt/gpautograd/learncurve/likelihood.py [66:76]:
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        if mean is None:
            mean = ScalarMeanFunction()
        if initial_noise_variance is None:
            initial_noise_variance = INITIAL_NOISE_VARIANCE
        if encoding_type is None:
            encoding_type = DEFAULT_ENCODING
        self.encoding = create_encoding(
             encoding_type, initial_noise_variance, NOISE_VARIANCE_LOWER_BOUND,
             NOISE_VARIANCE_UPPER_BOUND, 1, Gamma(mean=0.1, alpha=0.1))
        self.mean = mean
        self.kernel = kernel
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syne_tune/optimizer/schedulers/searchers/bayesopt/gpautograd/likelihood.py [48:58]:
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        if mean is None:
            mean = ScalarMeanFunction()
        if initial_noise_variance is None:
            initial_noise_variance = INITIAL_NOISE_VARIANCE
        if encoding_type is None:
            encoding_type = DEFAULT_ENCODING
        self.encoding = create_encoding(
             encoding_type, initial_noise_variance, NOISE_VARIANCE_LOWER_BOUND,
             NOISE_VARIANCE_UPPER_BOUND, 1, Gamma(mean=0.1, alpha=0.1))
        self.mean = mean
        self.kernel = kernel
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