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bugfix: confused output dim and num_latents in svgp

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James Hensman 2015-04-30 11:46:52 +01:00
parent 762e1e75b0
commit e9ff315a19
1 changed files with 2 additions and 2 deletions
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4
GPy/inference/latent_function_inference/svgp.py
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@ -8,8 +8,8 @@ class SVGP(LatentFunctionInference):
def inference(self, q_u_mean, q_u_chol, kern, X, Z, likelihood, Y, mean_function=None, Y_metadata=None, KL_scale=1.0, batch_scale=1.0):
num_inducing = Z.shape[0]
num_data, num_outputs = Y.shape
num_data, _ = Y.shape
num_inducing, num_outputs = q_u_mean.shape
#expand cholesky representation
L = choleskies.flat_to_triang(q_u_chol)