Reduce number of slow tests and balance parts (#1569)

.github/workflows/test.yml

@@ -84,14 +84,12 @@ jobs:
         install-torch: [0]
         install-xarray: [0]
         part:
-          - "tests --ignore=tests/tensor --ignore=tests/scan --ignore=tests/sparse --ignore=tests/xtensor"
+          - "tests --ignore=tests/tensor --ignore=tests/scan --ignore=tests/xtensor"
           - "tests/scan"
-          - "tests/sparse"
-          - "tests/tensor --ignore=tests/tensor/conv --ignore=tests/tensor/rewriting --ignore=tests/tensor/test_math.py --ignore=tests/tensor/test_basic.py --ignore=tests/tensor/test_inplace.py --ignore=tests/tensor/test_blas.py --ignore=tests/tensor/test_elemwise.py --ignore=tests/tensor/test_math_scipy.py"
-          - "tests/tensor/conv"
+          - "tests/tensor --ignore=tests/tensor/rewriting --ignore=tests/tensor/test_math.py --ignore=tests/tensor/test_basic.py --ignore=tests/tensor/test_inplace.py --ignore=tests/tensor/conv --ignore=tests/tensor/test_blas.py --ignore=tests/tensor/test_elemwise.py --ignore=tests/tensor/test_math_scipy.py"
           - "tests/tensor/rewriting"
           - "tests/tensor/test_math.py"
-          - "tests/tensor/test_basic.py tests/tensor/test_inplace.py"
+          - "tests/tensor/test_basic.py tests/tensor/test_inplace.py tests/tensor/conv"
           - "tests/tensor/test_blas.py tests/tensor/test_elemwise.py tests/tensor/test_math_scipy.py"
         exclude:
           - python-version: "3.10"
@@ -123,14 +121,21 @@ jobs:
             numpy-version: "~=2.1.0"
             fast-compile: 0
             float32: 0
-            part: "tests/link/numba"
+            part: "tests/link/numba --ignore=tests/link/numba/test_slinalg.py"
           - install-numba: 1
             os: "ubuntu-latest"
             python-version: "3.13"
             numpy-version: "~=2.1.0"
             fast-compile: 0
             float32: 0
-            part: "tests/link/numba"
+            part: "tests/link/numba --ignore=tests/link/numba/test_slinalg.py"
+          - install-numba: 1
+            os: "ubuntu-latest"
+            python-version: "3.13"
+            numpy-version: "~=2.1.0"
+            fast-compile: 0
+            float32: 0
+            part: "tests/link/numba/test_slinalg.py"
           - install-jax: 1
             os: "ubuntu-latest"
             python-version: "3.10"
@@ -343,4 +348,3 @@ jobs:
           directory: ./coverage/
           fail_ci_if_error: true
           token: ${{ secrets.CODECOV_TOKEN }}
-

tests/link/numba/test_pad.py

@@ -11,6 +11,9 @@ floatX = config.floatX
 RTOL = ATOL = 1e-6 if floatX.endswith("64") else 1e-3
 
 
+@pytest.mark.skip(
+    "Numba compilation is too slow and this is just a test for dispatch of OpFromGraph"
+)
 @pytest.mark.parametrize(
     "mode, kwargs",
     [

tests/tensor/test_basic.py

@@ -191,15 +191,7 @@ TestSecondBroadcast = makeTester(
     name="SecondBroadcastTester",
     op=second,
     expected=_numpy_second,
-    good=dict(
-        itertools.chain(
-            multi_dtype_checks((4, 5), (5,)),
-            multi_dtype_checks((2, 3, 2), (3, 2)),
-            multi_dtype_checks((2, 3, 2), (2,)),
-        )
-    ),
-    # I can't think of any way to make this fail at build time
-    # Just some simple smoke tests
+    good=dict(multi_dtype_checks((4, 2, 3, 2), (3, 2))),
     bad_runtime=dict(
         fail1=(random(5, 4), random(5)),
         fail2=(random(3, 2, 3), random(6, 9)),
@@ -207,26 +199,15 @@ TestSecondBroadcast = makeTester(
     ),
 )
 
-# We exclude local_fill_to_alloc because it optimizes the "second" node
-# away from the graph.
+# We exclude local_fill_to_alloc because it optimizes the "second" node away from the graph.
 TestSecondSameRank = makeTester(
     name="SecondSameRankTester",
     op=second,
     expected=_numpy_second,
-    good=dict(
-        itertools.chain(
-            multi_dtype_checks((4, 5), (4, 5)),
-            multi_dtype_checks((1, 2), (3, 2)),
-            multi_dtype_checks((3, 2), (1, 2)),
-        )
-    ),
-    # These sizes are not broadcastable to one another
-    # and SHOULD raise an error, but currently don't.
+    good=dict(multi_dtype_checks((4, 5), (4, 1))),
     bad_runtime=dict(
-        itertools.chain(
-            multi_dtype_checks((4, 5), (5, 4)),
-            multi_dtype_checks((1, 5), (5, 4)),
-        )
+        fail1=(random(4, 5), random(5, 4)),
+        fail2=(integers(1, 5), integers(5, 4)),
     ),
     mode=get_default_mode().excluding("local_fill_to_alloc", "local_useless_fill"),
 )