Encoded DeepGPs. #873
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Encoded DeepGPs. #873
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uri-granta
approved these changes
Sep 17, 2024
| @@ -96,7 +97,9 @@ def sample(self, at: TensorType, *, jitter: float = DEFAULTS.JITTER) -> TensorTy | |||
| tf.debugging.assert_shapes([(at, [..., 1, None])]) | |||
| tf.debugging.assert_greater_equal(jitter, 0.0) | |||
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| samples = tf.repeat(at[..., None, :, :], self._sample_size, axis=-3) # [..., S, 1, D] | |||
| samples = tf.repeat( | |||
| self._encode(at[..., None, :, :]), self._sample_size, axis=-3 | |||
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any reason not to encode first thing?
at = self._encode(at)
samples = tf.repeat(at[..., None, :, :], self._sample_size, axis=-3) # [..., S, 1, D]There was a problem hiding this comment.
Mainly compactness.
| @@ -72,6 +72,7 @@ def __init__(self, sample_size: int, model: GPfluxPredictor): | |||
| ) | |||
| for _ in range(len(self._model_gpflux.f_layers)) | |||
| ] | |||
| self._encode = lambda x: model.encode(x) | |||
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out of curiosity, does the following work?
Suggested change
| self._encode = lambda x: model.encode(x) | |
| self._encode = model.encode |
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Good point. I think it does.
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Related issue(s)/PRs:
Summary
Add support for encoding to Deep GPs models.
Fully backwards compatible: yes
PR checklist