Merge dd7a5c9 into 5314bab

.github/workflows/build_documentation.yml

@@ -33,10 +33,10 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Set up python 3.7
+      - name: Set up python 3.8
         uses: actions/setup-python@v4
         with:
-          python-version: 3.7
+          python-version: 3.8
           cache: pip
           cache-dependency-path: pyproject.toml
 

.github/workflows/build_release_package.yml

@@ -17,10 +17,10 @@ jobs:
       - name: Checkout
         uses: actions/checkout@v2
 
-      - name: Set up python 3.7
+      - name: Set up python 3.8
         uses: actions/setup-python@v4
         with:
-          python-version: 3.7
+          python-version: 3.8
           cache: pip
           cache-dependency-path: pyproject.toml
 

.github/workflows/run_tests.yml

@@ -12,7 +12,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.7"
           - "3.8"
           - "3.9"
           - "3.10"

pyproject.toml

@@ -16,7 +16,7 @@ authors = [
 ]
 readme = "README.md"
 license = {text = "BSD 3-Clause License"}
-requires-python = ">=3.7"
+requires-python = ">=3.8"
 keywords = [
   "manifolds",
   "optimization",

src/pymanopt/autodiff/backends/_jax.py

@@ -9,7 +9,7 @@
     jax = None
 else:
     import jax.numpy as jnp
-    from jax.config import config
+    from jax import config
 
     config.update("jax_enable_x64", True)
 

src/pymanopt/autodiff/backends/_pytorch.py

@@ -85,7 +85,7 @@ def hessian_vector_product(*args):
             for gradient, vector in zip(gradients, vectors):
                 dot_product += torch.tensordot(
                     gradient.conj(), vector, dims=gradient.ndim
-                )
+                ).real
             dot_product.backward()
             return self._sanitize_gradients(arguments)