Make cagrad and nashmtl raise an error if their solver is not installed.

Author: ValerianRey

src/torchjd/aggregation/cagrad.py

@@ -1,3 +1,5 @@
+import importlib.util
+
 import cvxpy as cp
 import numpy as np
 import torch
@@ -6,6 +8,13 @@
 from ._gramian_utils import compute_gramian, normalize
 from .bases import _WeightedAggregator, _Weighting
 
+# Check that the ecos solver is installed
+if importlib.util.find_spec("ecos") is None:
+    raise ModuleNotFoundError(
+        "NashMTL requires the ecos solver, but it is not installed. Please run"
+        "`pip install torchjd[nash_mtl]`."
+    )
+
 
 class CAGrad(_WeightedAggregator):
     """

src/torchjd/aggregation/nash_mtl.py

@@ -24,12 +24,21 @@
 # SOFTWARE.
 
 
+import importlib.util
+
 import cvxpy as cp
 import numpy as np
 import torch
 from cvxpy import Expression
 from torch import Tensor
 
+# Check that the ecos solver is installed
+if importlib.util.find_spec("ecos") is None:
+    raise ModuleNotFoundError(
+        "NashMTL requires the ecos solver, but it is not installed. Please run"
+        "`pip install torchjd[nash_mtl]`."
+    )
+
 from .bases import _WeightedAggregator, _Weighting