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Propagate generator kwargs to transfer-learning fallback (#5277) #5277

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Propagate generator kwargs to transfer-learning fallback (#5277) #5277

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6fb1946
Preserve numeric contour arrays through Plotly serialization (#5278)
saitcakmak Aug 18, 2026
451d179
Propagate generator kwargs to transfer-learning fallback (#5277)
saitcakmak Aug 18, 2026
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11 changes: 8 additions & 3 deletions ax/adapter/transfer_learning/adapter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -788,8 +788,10 @@ def transfer_learning_generator_specs_constructor(
model's input constructor.
fit_tracking_metrics: Whether to fit the generator on tracking metrics. Passed
to the `TransferLearningAdapter`.
additional_generator_kwargs: Additional kwargs to be passed
to the BoTorchGenerator
additional_generator_kwargs: Additional kwargs to be passed to each
BoTorchGenerator. When model selection is enabled, these kwargs must be
compatible with both the transfer learning model and the single-task
fallback.

Returns:
A tuple containing BOTL generator specs in case model selection is not enabled,
Expand Down Expand Up @@ -839,7 +841,10 @@ def transfer_learning_generator_specs_constructor(
]
if use_model_selection:
botl_specs.append(
GeneratorSpec(generator_enum=Generators.BOTORCH_MODULAR),
GeneratorSpec(
generator_enum=Generators.BOTORCH_MODULAR,
generator_kwargs=additional_generator_kwargs,
),
)
best_model_selector = SingleDiagnosticBestModelSelector(
diagnostic="Rank correlation",
Expand Down
6 changes: 3 additions & 3 deletions ax/analysis/plotly/surface/contour.py
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Expand Up @@ -384,9 +384,9 @@ def _prepare_plot(

fig = go.Figure(
data=go.Contour(
z=z_values,
x=z_grid.columns.values,
y=z_grid.index.values,
z=z_values.tolist(),
x=z_grid.columns.tolist(),
y=z_grid.index.tolist(),
colorscale=METRIC_CONTINUOUS_COLOR_SCALE,
showscale=True,
colorbar={
Expand Down
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