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This check seems incorrect when you have scalar observations, but several latent GPs: https://github.com/secondmind-labs/trieste/blob/develop/trieste/models/gpflow/models.py#L953
In that case dataset.observations.shape[-1] is one, but q_mu.shape[-1] is equal to num_latent.
dataset.observations.shape[-1]
q_mu.shape[-1]
num_latent
Possible fix is to use the likelihood's observation_dim, but I'm not sure it's defined all the time.
likelihood
observation_dim
The text was updated successfully, but these errors were encountered:
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This check seems incorrect when you have scalar observations, but several latent GPs:
https://github.com/secondmind-labs/trieste/blob/develop/trieste/models/gpflow/models.py#L953
In that case
dataset.observations.shape[-1]
is one, butq_mu.shape[-1]
is equal tonum_latent
.Possible fix is to use the
likelihood
'sobservation_dim
, but I'm not sure it's defined all the time.The text was updated successfully, but these errors were encountered: