Update test_mixins.py

Author: npolina4

tests/test_mixins.py

@@ -1,78 +1,44 @@
 import unittest
 
-import numpy
-
-import dpnp as inp
-
-from .helper import get_float_dtypes
+from tests.third_party.cupy import testing
 
 
 class TestMatMul(unittest.TestCase):
-    def test_matmul(self):
-        array_data = [1.0, 2.0, 3.0, 4.0]
-        size = 2
-
-        for dtype in get_float_dtypes():
-            # DPNP
-            array1 = inp.reshape(
-                inp.array(array_data, dtype=dtype), (size, size)
-            )
-            array2 = inp.reshape(
-                inp.array(array_data, dtype=dtype), (size, size)
-            )
-            result = inp.matmul(array1, array2)
-            # print(result)
-
-            # original
-            array_1 = numpy.array(array_data, dtype=dtype).reshape((size, size))
-            array_2 = numpy.array(array_data, dtype=dtype).reshape((size, size))
-            expected = numpy.matmul(array_1, array_2)
-            # print(expected)
-
-            # passed
-            numpy.testing.assert_array_equal(expected, result)
-            # still failed
-            # self.assertEqual(expected, result)
-
-    def test_matmul2(self):
-        array_data1 = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0]
-        array_data2 = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]
+    @testing.for_float_dtypes()
+    @testing.numpy_cupy_allclose()
+    def test_matmul(self, xp, dtype):
+        data = [1.0, 2.0, 3.0, 4.0]
+        shape = (2, 2)
 
-        for dtype in get_float_dtypes():
-            # DPNP
-            array1 = inp.reshape(inp.array(array_data1, dtype=dtype), (3, 2))
-            array2 = inp.reshape(inp.array(array_data2, dtype=dtype), (2, 4))
-            result = inp.matmul(array1, array2)
-            # print(result)
+        a = xp.array(data, dtype=dtype).reshape(shape)
+        b = xp.array(data, dtype=dtype).reshape(shape)
 
-            # original
-            array_1 = numpy.array(array_data1, dtype=dtype).reshape((3, 2))
-            array_2 = numpy.array(array_data2, dtype=dtype).reshape((2, 4))
-            expected = numpy.matmul(array_1, array_2)
-            # print(expected)
+        return xp.matmul(a, b)
 
-            numpy.testing.assert_array_equal(expected, result)
+    @testing.for_float_dtypes()
+    @testing.numpy_cupy_allclose()
+    def test_matmul2(self, xp, dtype):
+        data1 = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0]
+        data2 = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]
 
-    def test_matmul3(self):
-        array_data1 = numpy.full((513, 513), 5)
-        array_data2 = numpy.full((513, 513), 2)
+        a = xp.array(data1, dtype=dtype).reshape(3, 2)
+        b = xp.array(data2, dtype=dtype).reshape(2, 4)
 
-        for dtype in get_float_dtypes():
-            out = numpy.empty((513, 513), dtype=dtype)
+        return xp.matmul(a, b)
 
-            # DPNP
-            array1 = inp.array(array_data1, dtype=dtype)
-            array2 = inp.array(array_data2, dtype=dtype)
-            out1 = inp.array(out, dtype=dtype)
-            result = inp.matmul(array1, array2, out=out1)
+    @testing.for_float_dtypes()
+    @testing.numpy_cupy_allclose()
+    def test_matmul3(self, xp, dtype):
+        data1 = xp.full((513, 513), 5)
+        data2 = xp.full((513, 513), 2)
+        out = xp.empty((513, 513), dtype=dtype)
 
-            # original
-            array_1 = numpy.array(array_data1, dtype=dtype)
-            array_2 = numpy.array(array_data2, dtype=dtype)
-            expected = numpy.matmul(array_1, array_2, out=out)
+        a = xp.array(data1, dtype=dtype)
+        b = xp.array(data2, dtype=dtype)
 
-            numpy.testing.assert_array_equal(expected, result)
+        xp.matmul(a, b, out=out)
 
+        return out
 
 if __name__ == "__main__":
     unittest.main()