closes #6, loosen reqs

environment.yml

@@ -1,30 +1,18 @@
-name: torch
+name: vectopt
 channels:
 - conda-forge
 - pytorch
 - gpytorch
-- nvidia
-- gurobi
-- mosek
 dependencies:
-- python=3.10
-- pytorch=2.0.1
-- pytorch-cuda=11.7
-- gpytorch=1.11.0
-- botorch=0.10.0
-- pymoo=0.5.0
+- python>=3.10
+- gpytorch
+- botorch<0.12.0
 - cvxpy
 - scikit-learn
 - scipy
-- oyaml
-- gpy
-- jupyter
 - matplotlib
 - numpy
-- pandas
-- seaborn
 - jupyter
-- gurobi
 - pytest
 - pytest-cov
 - flake8
@@ -34,4 +22,4 @@ dependencies:
 - bandit
 - sphinx_rtd_theme
 - pip:
-    - docs/requirements.txt
+    - -r docs/requirements.txt

requirements.txt

@@ -1,17 +1,10 @@
-torch==2.0.1
-gpytorch==1.11.0
-botorch==0.10.0
-pymoo==0.5.0
+gpytorch
+botorch<0.12.0
 cvxpy
 scikit-learn
 scipy
-oyaml
-gpy
-jupyter
 matplotlib
 numpy
-pandas
-seaborn
 jupyter
 pytest
 pytest-cov
@@ -20,5 +13,6 @@ flake8-print
 pydocstyle
 black
 bandit
+sphinx_rtd_theme
 
 -r docs/requirements.txt

vectoptal/acquisition/acquisition.py

@@ -7,7 +7,6 @@
 from vectoptal.models import Model, ModelList
 from vectoptal.design_space import DiscreteDesignSpace
 
-import torch
 import numpy as np
 
 
@@ -270,8 +269,7 @@ def optimize_acqf_discrete(
 
     chosen = 0
     while chosen < q:
-        with torch.no_grad():
-            acq_values = acq(choices)
+        acq_values = acq(choices)
 
         best_idx = np.argmax(acq_values)
         candidate_list.append(choices[best_idx])