[CI] Fix 3.13t wheels

ghstack-source-id: c57cd1f
Pull Request resolved: #1294

Author: Vincent Moens

.github/scripts/version_script.sh

@@ -1,3 +1,8 @@
 #!/bin/bash
 
 export TENSORDICT_BUILD_VERSION=0.8.0
+${CONDA_RUN} pip install --upgrade pip
+
+${CONDA_RUN} conda install conda-forge::rust -y
+# for orjson
+export UNSAFE_PYO3_BUILD_FREE_THREADED=1

pyproject.toml

@@ -3,12 +3,12 @@ requires = ["setuptools", "wheel", "torch"]
 
 [tool.usort]
 first_party_detection = false
-target-version = ["py38"]
+target-version = ["py39"]
 excludes = [
     "gallery",
     "tutorials",
 ]
 
 [tool.black]
 line-length = 88
-target-version = ["py38"]
+target-version = ["py39"]

test/test_nn.py

@@ -812,8 +812,9 @@ def test_dispatch_deactivate(self):
         with _set_dispatch_td_nn_modules(True):
             out = tdm(a=torch.zeros(1, 1))
             assert (out == td["b"]).all()
-        with _set_dispatch_td_nn_modules(False), pytest.raises(
-            TypeError, match="missing 1 required positional argument"
+        with (
+            _set_dispatch_td_nn_modules(False),
+            pytest.raises(TypeError, match="missing 1 required positional argument"),
         ):
             tdm(a=torch.zeros(1, 1))
 
@@ -2458,11 +2459,14 @@ def test_no_warning_single_key(self):
                 out_keys=[("dirich", "categ")],
                 return_log_prob=True,
             )
-            with pytest.warns(
-                DeprecationWarning, match="You are querying the log-probability key"
-            ), pytest.warns(
-                DeprecationWarning,
-                match="Composite log-prob aggregation wasn't defined explicitly",
+            with (
+                pytest.warns(
+                    DeprecationWarning, match="You are querying the log-probability key"
+                ),
+                pytest.warns(
+                    DeprecationWarning,
+                    match="Composite log-prob aggregation wasn't defined explicitly",
+                ),
             ):
                 td = TensorDict(
                     params=TensorDict(

test/test_tensorclass.py

@@ -1625,10 +1625,13 @@ class MyDataNested:
         X = torch.randn(3, 4, 5)
         z = ["a", "b", "c"]
         batch_size = [3, 4]
-        with set_list_to_stack(list_to_stack), (
-            pytest.raises(RuntimeError, match="batch dimension mismatch")
-            if list_to_stack
-            else contextlib.nullcontext()
+        with (
+            set_list_to_stack(list_to_stack),
+            (
+                pytest.raises(RuntimeError, match="batch dimension mismatch")
+                if list_to_stack
+                else contextlib.nullcontext()
+            ),
         ):
             data_nest = MyDataNested(X=X, z=z, batch_size=batch_size)
             data = MyDataNested(X=X, y=data_nest, z=z, batch_size=batch_size)
@@ -1662,10 +1665,13 @@ class MyDataNested:
         X = torch.ones(3, 4, 5)
         z = ["a", "b", "c"]
         batch_size = [3, 4]
-        with set_list_to_stack(list_to_stack), (
-            pytest.raises(RuntimeError, match="batch dimension mismatch")
-            if list_to_stack
-            else contextlib.nullcontext()
+        with (
+            set_list_to_stack(list_to_stack),
+            (
+                pytest.raises(RuntimeError, match="batch dimension mismatch")
+                if list_to_stack
+                else contextlib.nullcontext()
+            ),
         ):
             data_nest = MyDataNested(X=X, z=z, batch_size=batch_size)
             data = MyDataNested(X=X, y=data_nest, z=z, batch_size=batch_size)