Thread equality constraints through adapter layer and TorchOptConfig (#5176)#5176
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Pull Request resolved: facebook#5176 Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
sdaulton
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Apr 17, 2026
…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Pull Request resolved: facebook#5176 Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #5176 +/- ##
========================================
Coverage 96.41% 96.41%
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Files 618 619 +1
Lines 68882 69114 +232
========================================
+ Hits 66410 66639 +229
- Misses 2472 2475 +3 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
Summary: Add support for linear equality constraints (`w^T x == b`) alongside existing inequality constraints (`w^T x <= b`) in Ax's `ParameterConstraint` class. This is the first diff in a stack that threads equality constraints all the way down to BoTorch's `optimize_acqf`. Changes: - Add `extract_coefficient_dict_from_equality` to `ax/utils/common/sympy.py` for parsing `"expr == bound"` strings (SymPy can't parse `==` directly since Python evaluates it as a boolean). - Extend `ParameterConstraint.__init__` to accept `equality=` kwarg alongside existing `inequality=` kwarg. Exactly one must be provided. - Add `is_equality` property. - Update `check()` to use `|w^T x - b| <= tol` for equality constraints. - Update `__repr__`, `clone()`, `clone_with_transformed_parameters()`. - Add comprehensive tests for equality constraints. Differential Revision: D100256486
Summary: Add support for parsing equality constraint strings (e.g. `"x1 + x2 == 3"`) in `constraint_from_str`. This extends the existing `<=`/`>=` parsing to also accept `==` as a comparison operator. - Add `_process_equality_constraint` function (analogous to `_process_linear_constraint`) that constructs `ParameterConstraint(equality=...)`. - Detect `==` in `constraint_from_str` and route to the new function. - Reject equality order constraints (`"x1 == x2"`) with a clear error message. - Update `INVALID_CONSTRAINT_ERROR_MSG` to document `==` support. Differential Revision: D100256487
Summary: Update `SearchSpace.check_membership_df` and `compute_chebyshev_center` to handle equality constraints alongside existing inequality constraints. - `check_membership_df`: branch on `constraint.is_equality` — use `|weighted_sum - bound| <= tol` for equality, `weighted_sum <= bound + tol` for inequality. - `compute_chebyshev_center`: separate equality and inequality constraints into `A_eq/b_eq` and `A_ub/b_ub` for `scipy.optimize.linprog`. Equality constraints don't get the `r * ||a_i||` augmentation since the inscribed ball center must lie on the hyperplane. - `check_membership` already works via the updated `constraint.check()`. Differential Revision: D100256478
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Pull Request resolved: facebook#5176 Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
sdaulton
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Apr 20, 2026
…acebook#5176) Summary: Add equality constraint extraction and propagation through the adapter layer to TorchOptConfig, enabling downstream generators to receive equality constraints. - Add `extract_equality_constraints` in `adapter_utils.py` (filters for `is_equality=True` constraints, returns `(A, b)` matrices). - Update `extract_parameter_constraints` to filter out equality constraints. - Add `equality_constraints` parameter to `validate_and_apply_final_transform` (now returns a 7-tuple). - Add `equality_constraints: tuple[Tensor, Tensor] | None` field to `TorchOptConfig`. - Update `TorchAdapter._get_transformed_model_gen_args` to extract equality constraints and pass them through to `TorchOptConfig`. Reviewed By: bletham Differential Revision: D100256480
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Summary:
Add equality constraint extraction and propagation through the adapter layer
to TorchOptConfig, enabling downstream generators to receive equality
constraints.
extract_equality_constraintsinadapter_utils.py(filters foris_equality=Trueconstraints, returns(A, b)matrices).extract_parameter_constraintsto filter out equality constraints.equality_constraintsparameter tovalidate_and_apply_final_transform(now returns a 7-tuple).
equality_constraints: tuple[Tensor, Tensor] | Nonefield toTorchOptConfig.TorchAdapter._get_transformed_model_gen_argsto extract equalityconstraints and pass them through to
TorchOptConfig.Reviewed By: bletham
Differential Revision: D100256480