Add constant_constraint to ConstantMean #2082
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Balandat
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| :type constant_prior: ~gpytorch.priors.Prior, optional | ||
| :param constant_constraint: Constraint for constant parameter :math:`C`. | ||
| :type constant_constraint: ~gpytorch.priors.Interval, optional | ||
| :param batch_shape: The batch shape of the learned constant(s) (default: []). | ||
| :type batch_shape: torch.Size, optional |
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consistency nit
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| :type constant_prior: ~gpytorch.priors.Prior, optional | |
| :param constant_constraint: Constraint for constant parameter :math:`C`. | |
| :type constant_constraint: ~gpytorch.priors.Interval, optional | |
| :param batch_shape: The batch shape of the learned constant(s) (default: []). | |
| :type batch_shape: torch.Size, optional | |
| :type constant_prior: ~gpytorch.priors.Prior, optional. | |
| :param constant_constraint: Constraint for constant parameter :math:`C`. | |
| :type constant_constraint: ~gpytorch.priors.Interval, optional. | |
| :param batch_shape: The batch shape of the learned constant(s) (default: []). | |
| :type batch_shape: torch.Size, optional. |
| :param batch_shape: The batch shape of the learned constant(s) (default: []). | ||
| :type batch_shape: torch.Size, optional | ||
|
|
||
| :var torch.Tensor constant: :math:`C` parameter |
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| :var torch.Tensor constant: :math:`C` parameter | |
| :var torch.Tensor constant: :math:`C` parameter. |
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| else: # Weird edge case where someone set both `prior` and `constant_prior` | ||
| warnings.warn( | ||
| "You have set both the `constant_prior` and the deprecated `prior` arguments for ConstantMean. " | ||
| "`prior` is deprecated, and will be ignored.", | ||
| DeprecationWarning, | ||
| ) |
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I think this is weird enough that we may just want to throw an error here?
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cornellius-gp/gpytorch#2082 changed the shape of the mean constant (and did some other things). These changes fix the resulting unit test breakages.
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cornellius-gp/gpytorch#2082 changed the shape of the mean constant (and did some other things). These changes fix the resulting unit test breakages.
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Summary: cornellius-gp/gpytorch#2082 changed the shape of the mean constant (and did some other things). These changes fix the resulting unit test breakages. This requires the botorch change pytorch/botorch#1343 Pull Request resolved: facebook#1055 Reviewed By: lena-kashtelyan Differential Revision: D38527699 Pulled By: Balandat fbshipit-source-id: 86a9a9fb272cebb923e2fafc76fd44624f1069d0
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Summary: cornellius-gp/gpytorch#2082 changed the shape of the mean constant (and did some other things). These changes fix the resulting unit test breakages. Pull Request resolved: #1343 Reviewed By: saitcakmak Differential Revision: D38527688 Pulled By: Balandat fbshipit-source-id: a9878b3ff5d045b18c3330f4e0707a3ee4be2553
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Summary: cornellius-gp/gpytorch#2082 changed the shape of the mean constant (and did some other things). These changes fix the resulting unit test breakages. This requires the botorch change pytorch/botorch#1343 Pull Request resolved: #1055 Reviewed By: lena-kashtelyan Differential Revision: D38527699 Pulled By: Balandat fbshipit-source-id: e2c13d78d4ce25e35152a0e19a23e2b107627d37
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Previously, ConstantMean only supported a prior on the constant (not a constraint). This PR adds a
constant_constraintkwarg to ConstantMean.Backwards compatibility
There are two non-backwards compatible changes to ConstantMean, though there is a state_dict hook to ensure that previous state dicts can be loaded:
constantparameter is renamed toraw_constant.raw_constantis now*batch_shape, rather than*batch_shape x 1.[Fixes #2074]