misc testing

Author: pabloprf

src/mitim_modules/portals/PORTALStools.py

@@ -9,9 +9,7 @@
 
 def selectSurrogate(output, surrogateOptions, CGYROrun=False):
 
-    print(
-        f'\t- Selecting surrogate options for "{output}" to be run'
-    )
+    print(f'\t- Selecting surrogate options for "{output}" to be run')
 
     if output is not None:
         # If it's a target, just linear

src/mitim_tools/opt_tools/BOTORCHtools.py

@@ -17,15 +17,8 @@
 from botorch.models.transforms.input import InputTransform
 from botorch.models.transforms.outcome import OutcomeTransform, Standardize
 from botorch.models.utils import validate_input_scaling
-from botorch.models.utils.gpytorch_modules import (
-    get_covar_module_with_dim_scaled_prior,
-    get_gaussian_likelihood_with_lognormal_prior,
-)
 from botorch.utils.types import DEFAULT
-from gpytorch.likelihoods.gaussian_likelihood import FixedNoiseGaussianLikelihood
-from gpytorch.means.constant_mean import ConstantMean
 from gpytorch.models.exact_gp import ExactGP
-from gpytorch.module import Module
 from torch import Tensor
 
 from linear_operator.operators import CholLinearOperator, DiagLinearOperator
@@ -136,7 +129,6 @@ def __init__(
                 batch_shape=self._aug_batch_shape, variables=variables
             )
 
-
         """
 		-----------------------------------------------------------------------
 		GP Kernel - Covariance
@@ -562,23 +554,15 @@ def __init__(self, *gp_models):
     def prepareToGenerateCommons(self):
         self.models[0].input_transform.tf1.flag_to_store = True
         # Make sure that this ModelListGP evaluation is fresh
-        if (
-            "parameters_combined"
-            in self.models[0].input_transform.tf1.surrogate_parameters
-        ):
-            del self.models[0].input_transform.tf1.surrogate_parameters[
-                "parameters_combined"
-            ]
+        if ("surrogate_parameters" in self.models[0].input_transform.tf1.__dict__) and \
+            ("parameters_combined" in self.models[0].input_transform.tf1.surrogate_parameters):
+            del self.models[0].input_transform.tf1.surrogate_parameters["parameters_combined"]
 
     def cold_startCommons(self):
         self.models[0].input_transform.tf1.flag_to_store = False
-        if (
-            "parameters_combined"
-            in self.models[0].input_transform.tf1.surrogate_parameters
-        ):
-            del self.models[0].input_transform.tf1.surrogate_parameters[
-                "parameters_combined"
-            ]
+        if ("surrogate_parameters" in self.models[0].input_transform.tf1.__dict__) and \
+            ("parameters_combined" in self.models[0].input_transform.tf1.surrogate_parameters):
+            del self.models[0].input_transform.tf1.surrogate_parameters["parameters_combined"]
 
     def transform_inputs(self, X):
         self.prepareToGenerateCommons()