update new tests

Author: vtavana

dpnp/tests/test_linalg.py

@@ -175,14 +175,15 @@ def test_cholesky(self, array, dtype):
     )
     @pytest.mark.parametrize("dtype", get_all_dtypes(no_bool=True))
     def test_cholesky_upper(self, array, dtype):
-        ia = dpnp.array(array, dtype=dtype)
+        a = numpy.array(array, dtype=dtype)
+        ia = dpnp.array(a)
         result = dpnp.linalg.cholesky(ia, upper=True)
 
-        if ia.ndim > 2:
+        if a.ndim > 2:
             n = ia.shape[-1]
-            ia_reshaped = ia.reshape(-1, n, n)
+            a_reshaped = a.reshape(-1, n, n)
             res_reshaped = result.reshape(-1, n, n)
-            batch_size = ia_reshaped.shape[0]
+            batch_size = a_reshaped.shape[0]
             for idx in range(batch_size):
                 # Reconstruct the matrix using the Cholesky decomposition result
                 if dpnp.issubdtype(dtype, dpnp.complexfloating):
@@ -192,15 +193,15 @@ def test_cholesky_upper(self, array, dtype):
                 else:
                     reconstructed = res_reshaped[idx].T @ res_reshaped[idx]
                 assert_dtype_allclose(
-                    reconstructed, ia_reshaped[idx], check_type=False
+                    reconstructed, a_reshaped[idx], check_type=False
                 )
         else:
             # Reconstruct the matrix using the Cholesky decomposition result
             if dpnp.issubdtype(dtype, dpnp.complexfloating):
                 reconstructed = result.T.conj() @ result
             else:
                 reconstructed = result.T @ result
-            assert_dtype_allclose(reconstructed, ia, check_type=False)
+            assert_dtype_allclose(reconstructed, a, check_type=False)
 
     # upper parameter support will be added in numpy 2.0 version
     @testing.with_requires("numpy>=2.0")

dpnp/tests/test_mathematical.py

@@ -2363,13 +2363,13 @@ def test_projection_infinity(self, dtype):
         a = dpnp.array(X, dtype=dtype)
         result = dpnp.proj(a)
         expected = dpnp.array(Y, dtype=dtype)
-        assert_dtype_allclose(result, expected)
+        assert_array_equal(result, expected)
 
         # out keyword
         dp_out = dpnp.empty(expected.shape, dtype=expected.dtype)
         result = dpnp.proj(a, out=dp_out)
         assert dp_out is result
-        assert_dtype_allclose(result, expected)
+        assert_array_equal(result, expected)
 
     @pytest.mark.parametrize("dtype", get_all_dtypes())
     def test_projection(self, dtype):
@@ -3660,4 +3660,4 @@ def test_elemenwise_outer_scalar():
     y = dpnp.asarray(s)
     expected = dpnp.add.outer(x, y)
     result = dpnp.add.outer(x, s)
-    assert_dtype_allclose(result, expected)
+    assert_array_equal(result, expected)