Adds errors asking users to install optional dependencies (#64)

* Adds safeguards for ax solvers

* Adds safety guards on imports for solvers

* Bumps minor version

Author: miguelgondu

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "poli-baselines"
-version = "1.0.0"
+version = "1.0.1"
 description = "poli-baselines, a library of discrete objective optimizers"
 readme = "README.md"
 authors = [{name="Miguel González-Duque", email="[email protected]"}]
@@ -94,7 +94,7 @@ markers = [
 profile = "black"
 
 [tool.bumpversion]
-current_version = "1.0.0"
+current_version = "1.0.1"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = poli_baselines
-version = 1.0.0
+version = 1.0.1
 author_email = [email protected]
 description = Baselines for Discrete Sequence Optimization, focusing on proteins
 long_description = file: readme.md

src/poli_baselines/__init__.py

@@ -1 +1 @@
-__version__ = "1.0.0"
+__version__ = "1.0.1"

src/poli_baselines/core/utils/ax/ax_solver.py

@@ -5,8 +5,18 @@
 
 import numpy as np
 import torch
-from ax.modelbridge.generation_strategy import GenerationStrategy
-from ax.service.ax_client import AxClient, ObjectiveProperties
+
+try:
+    from ax.modelbridge.generation_strategy import GenerationStrategy
+    from ax.service.ax_client import AxClient, ObjectiveProperties
+except ImportError as e:
+    raise ImportError(
+        "You are trying to use a solver that requires Ax. Install "
+        "the relevant optional dependencies with [ax] or [alebo].\n"
+        "You can do this by running e.g. \n"
+        "pip install 'poli-baselines[ax] @ git+https://github.com/MachineLearningLifeScience/poli-baselines.git'"
+    ) from e
+
 from numpy import ndarray
 from poli.core.abstract_black_box import AbstractBlackBox
 from poli.objective_repository import ToyContinuousBlackBox

src/poli_baselines/solvers/bayesian_optimization/baxus/baxus.py

@@ -4,8 +4,17 @@
 from typing import List
 
 import numpy as np
-from baxus.baxus import BAxUS as OriginalBAxUS
-from baxus.benchmarks.benchmark_function import Benchmark
+
+try:
+    from baxus.baxus import BAxUS as OriginalBAxUS
+    from baxus.benchmarks.benchmark_function import Benchmark
+except ImportError as e:
+    raise ImportError(
+        "You are trying to use the BAxUS solver. Install "
+        "the relevant optional dependencies with [baxus]. \n"
+        "You can do this by running: \n"
+        "pip install 'poli-baselines[baxus] @ git+https://github.com/MachineLearningLifeScience/poli-baselines.git'"
+    ) from e
 from poli.core.abstract_black_box import AbstractBlackBox
 
 from poli_baselines.core.abstract_solver import AbstractSolver

src/poli_baselines/solvers/bayesian_optimization/bounce/solver.py

@@ -10,7 +10,17 @@
 
 import numpy as np
 import torch
-from bounce.bounce import Bounce
+
+try:
+    from bounce.bounce import Bounce
+except ImportError as e:
+    raise ImportError(
+        "You are trying to use the Bounce solver. Install "
+        "the relevant optional dependencies with [bounce]. \n"
+        "You can do this by running: \n"
+        "pip install 'poli-baselines[bounce] @ git+https://github.com/MachineLearningLifeScience/poli-baselines.git'"
+    ) from e
+
 from poli.core.abstract_black_box import AbstractBlackBox
 from poli.core.util.seeding import seed_python_numpy_and_torch
 

src/poli_baselines/solvers/bayesian_optimization/lambo2/solver.py

@@ -27,13 +27,22 @@
 from pathlib import Path
 from uuid import uuid4
 
-import edlib
-import hydra
-import lightning as L
+try:
+    import edlib
+    import hydra
+    import lightning as L
+    from beignet import farthest_first_traversal
+    from omegaconf import OmegaConf
+except ImportError as e:
+    raise ImportError(
+        "You are trying to use the Lambo2 solver. Install "
+        "the relevant optional dependencies with [lambo2].\n"
+        "You can do this by running e.g. \n"
+        "pip install 'poli-baselines[lambo2] @ git+https://github.com/MachineLearningLifeScience/poli-baselines.git'"
+    ) from e
+
 import numpy as np
 import torch
-from beignet import farthest_first_traversal
-from omegaconf import OmegaConf
 from poli.core.abstract_black_box import AbstractBlackBox
 from poli.core.util.seeding import seed_python_numpy_and_torch
 

src/poli_baselines/solvers/bayesian_optimization/pr/solver.py

@@ -11,9 +11,18 @@
 from poli.core.abstract_black_box import AbstractBlackBox
 
 from poli_baselines.core.abstract_solver import AbstractSolver
-from poli_baselines.core.utils.bo_pr.run_one_replication import (
-    run_one_replication_on_poli_black_box,
-)
+
+try:
+    from poli_baselines.core.utils.bo_pr.run_one_replication import (
+        run_one_replication_on_poli_black_box,
+    )
+except ImportError as e:
+    raise ImportError(
+        "You are trying to use the Probabilistic Reparametrization solver. Install "
+        "the relevant optional dependencies with [pr]. \n"
+        "You can do this by running: \n"
+        "pip install 'poli-baselines[pr] @ git+https://github.com/MachineLearningLifeScience/poli-baselines.git'"
+    ) from e
 
 
 class ProbabilisticReparametrizationSolver(AbstractSolver):