Update cupy tests for dpnp.linalg.solve() (#2074)

* Update cupy tests for dpnp.linalg.solve()

* Update CHANGELOG.md

CHANGELOG.md

@@ -107,6 +107,7 @@ In addition, this release completes implementation of `dpnp.fft` module and adds
 * Improved implementation of `dpnp.kron` to avoid unnecessary copy for non-contiguous arrays [#2059](https://github.com/IntelPython/dpnp/pull/2059)
 * Updated the test suit for `dpnp.fft` module [#2071](https://github.com/IntelPython/dpnp/pull/2071)
 * Reworked `dpnp.clip` implementation to align with Python Array API 2023.12 specification [#2048](https://github.com/IntelPython/dpnp/pull/2048)
+* Skipped outdated tests for `dpnp.linalg.solve` due to compatibility issues with NumPy 2.0 [#2074](https://github.com/IntelPython/dpnp/pull/2074)
 
 ### Fixed
 

tests/third_party/cupy/linalg_tests/test_solve.py

@@ -50,14 +50,20 @@ def check_x(self, a_shape, b_shape, xp, dtype):
     def test_solve(self):
         self.check_x((4, 4), (4,))
         self.check_x((5, 5), (5, 2))
-        self.check_x((2, 4, 4), (2, 4))
         self.check_x((2, 5, 5), (2, 5, 2))
-        self.check_x((2, 3, 2, 2), (2, 3, 2))
         self.check_x((2, 3, 3, 3), (2, 3, 3, 2))
         self.check_x((0, 0), (0,))
         self.check_x((0, 0), (0, 2))
-        self.check_x((0, 2, 2), (0, 2))
         self.check_x((0, 2, 2), (0, 2, 3))
+        # In numpy 2.0 the broadcast ambiguity has been removed and now
+        # b is treaded as a single vector if and only if it is 1-dimensional;
+        # for other cases this signature must be followed
+        # (..., m, m), (..., m, n) -> (..., m, n)
+        # https://github.com/numpy/numpy/pull/25914
+        if numpy.lib.NumpyVersion(numpy.__version__) < "2.0.0":
+            self.check_x((2, 4, 4), (2, 4))
+            self.check_x((2, 3, 2, 2), (2, 3, 2))
+            self.check_x((0, 2, 2), (0, 2))
 
     def check_shape(self, a_shape, b_shape, error_types):
         for xp, error_type in error_types.items():
@@ -90,7 +96,9 @@ def test_invalid_shape(self):
         self.check_shape((3, 3), (2,), value_errors)
         self.check_shape((3, 3), (2, 2), value_errors)
         self.check_shape((3, 3, 4), (3,), linalg_errors)
-        self.check_shape((2, 3, 3), (3,), value_errors)
+        # Since numpy >= 2.0, this case does not raise an error
+        if numpy.lib.NumpyVersion(numpy.__version__) < "2.0.0":
+            self.check_shape((2, 3, 3), (3,), value_errors)
         self.check_shape((3, 3), (0,), value_errors)
         self.check_shape((0, 3, 4), (3,), linalg_errors)