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Reshape Targets and Mean for RHS in Cholesky solver #2587

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Reshape Targets and Mean for RHS in Cholesky solver #2587

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02ac2c9
Reshape Targets and Mean for RHS in Cholesky solver
Richard2926 Sep 12, 2024
f5216c3
Handle Batched Computation
Richard2926 Sep 12, 2024
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4 changes: 3 additions & 1 deletion gpytorch/models/exact_prediction_strategies.py
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Expand Up @@ -193,7 +193,9 @@ def get_fantasy_strategy(self, inputs, targets, full_inputs, full_targets, full_
prefix = string.ascii_lowercase[: max(fant_train_covar.dim() - self.mean_cache.dim() - 1, 0)]
ftcm = torch.einsum(prefix + "...yz,...z->" + prefix + "...y", [fant_train_covar, self.mean_cache])

small_system_rhs = targets - fant_mean - ftcm
targets_ = torch.reshape(targets, (-1, ftcm.shape[-1]))
fant_mean_ = torch.reshape(fant_mean, (-1, ftcm.shape[-1]))
small_system_rhs = targets_ - fant_mean_ - ftcm
small_system_rhs = small_system_rhs.unsqueeze(-1)
# Schur complement of a spd matrix is guaranteed to be positive definite
schur_cholesky = psd_safe_cholesky(schur_complement)
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