Restoring everything to main.

I created an [issue](spcl#1921), I think it is now time to run the CI until I pass, whcih is not a very good stragety.
However, I wonder why it happens soley to me.

.github/workflows/general-ci.yml

@@ -55,7 +55,7 @@ jobs:
         else
             export DACE_optimizer_automatic_simplification=${{ matrix.simplify }}
         fi
-        pytest -n auto --cov-report=xml --cov=dace --tb=short -m "not gpu and not verilator and not tensorflow and not mkl and not sve and not papi and not mlir and not lapack and not fpga and not mpi and not rtl_hardware and not scalapack and not datainstrument and not long" tests/numpy
+        pytest -n auto --cov-report=xml --cov=dace --tb=short -m "not gpu and not verilator and not tensorflow and not mkl and not sve and not papi and not mlir and not lapack and not fpga and not mpi and not rtl_hardware and not scalapack and not datainstrument and not long"
         ./codecov
 
     - name: Test OpenBLAS LAPACK

tests/numpy/array_creation_test.py

@@ -220,32 +220,14 @@ def test_strides_1():
 def program_strides_2():
     A = dace.ndarray((2, 2), dtype=dace.int32, strides=(1, 2))
     for i, j in dace.map[0:2, 0:2]:
-        A[i, j] = j + i # * 2 + j
+        A[i, j] = i * 2 + j
     return A
 
 
 def test_strides_2():
-    # Current state:
-    #   - If it is serial it does not fail.
-    #   - If we write to the output again, i.e. by adding `A[0, 0] += 1` it still fails.
-    #   - If we remove the `__restrict` from the output it still fails.
-    #   - Changing to `A[i, j] = 0` does remove the bug and makes it correct.
-    #   - Changing to `A[i, j] = i` does remove the bug and makes it correct.
-    #   - Changing to `A[i, j] = j` does remove the bug and makes it correct.
-    #   - Changing to `A[i, j] = i + j` triggers the bug.
-    sdfg = program_strides_2.to_sdfg()
-
-    csdfg = sdfg.compile()
-    A = csdfg()
-    Res1 = A.copy()
-    A = csdfg()
-    Res2 = A.copy()
-
+    A = program_strides_2()
     assert A.strides == (4, 8)
-    assert np.allclose(Res2, [[0, 1], [1, 2]])
-    assert np.allclose(Res1, [[0, 1], [1, 2]])
-    #assert np.allclose(Res2, [[0, 1], [2, 3]])
-    #assert np.allclose(Res1, [[0, 1], [2, 3]])
+    assert np.allclose(A, [[0, 1], [2, 3]])
 
 
 @dace.program