dot/matmul fixes in python/cython (#922)

* dot/matmul fixes in python/sython

* skip SVD tests with complex128 type

Author: Alexander-Makaryev

dpnp/dpnp_algo/dpnp_algo_linearalgebra.pyx

@@ -244,18 +244,7 @@ cpdef utils.dpnp_descriptor dpnp_matmul(utils.dpnp_descriptor in_array1, utils.d
         """
         size_n = 1
 
-    if ndim_max > 2:
-        """
-        shape1(5, 3, 2) * shape2(5, 2, 4) -> result(5, 3, 4)
-        test: pytest tests/test_matmul.py::test_matmul[shape_pair10-types0] -v -s
-        """
-        shape_result = shape1[:-1] + [shape2.back()]
-    else:
-        """
-        shape1(5,2) * shape2(2,3) -> result(5,3)
-        test: pytest tests/test_matmul.py::test_matmul[shape_pair0-types0] -v -s
-        """
-        shape_result = shape1[:-1] + shape2[1:]
+    shape_result = shape1[:-1] + shape2[-1:]
 
     # convert string type names (array.dtype) to C enum DPNPFuncType
     cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(in_array1.dtype)

dpnp/dpnp_iface_linearalgebra.py

@@ -97,11 +97,18 @@ def dot(x1, x2, **kwargs):
         dim1 = x1_desc.ndim
         dim2 = x2_desc.ndim
 
-        if not (dim1 >= 2 and dim2 == 1) and not (dim1 >= 2 and dim2 >= 2) and (x1_desc.dtype == x2_desc.dtype):
+        # for now we work only with these cases
+        if (
+            (dim1 == 1 and dim2 == 1 # vectors
+             or dim1 == 2 and dim2 == 2 # matrices
+             # or dim1 == 0 or dim2 == 0 # there is an issue with scalars (dpnp_multiply)
+            ) and (x1_desc.dtype == x2_desc.dtype)):
             result_obj = dpnp_dot(x1_desc, x2_desc).get_pyobj()
-            result = dpnp.convert_single_elem_array_to_scalar(result_obj)
-
-            return result
+            if (dim1 == 2 and dim2 == 2):
+                return result_obj
+            else:
+                result = dpnp.convert_single_elem_array_to_scalar(result_obj)
+                return result
 
     return call_origin(numpy.dot, x1, x2, **kwargs)
 
@@ -246,7 +253,7 @@ def matmul(x1, x2, out=None, **kwargs):
     x1_desc = dpnp.get_dpnp_descriptor(x1)
     x2_desc = dpnp.get_dpnp_descriptor(x2)
     if x1_desc and x2_desc and not kwargs:
-        if x1_desc.size != x2_desc.size:
+        if x1_desc.ndim != 2 or x2_desc.ndim != 2:
             pass
         elif not x1_desc.ndim:
             pass

tests/skipped_tests.tbl

@@ -13,6 +13,10 @@ tests/test_linalg.py::test_cond[None-[[1, 0, -1], [0, 1, 0], [1, 0, 1]]]
 tests/test_linalg.py::test_cond[None-[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]
 tests/test_linalg.py::test_cond[-numpy.inf-[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]
 tests/test_linalg.py::test_cond[numpy.inf-[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]
+tests/test_linalg.py::test_svd[(2,2)-complex128]
+tests/test_linalg.py::test_svd[(3,4)-complex128]
+tests/test_linalg.py::test_svd[(5,3)-complex128]
+tests/test_linalg.py::test_svd[(16,16)-complex128]
 tests/test_random.py::TestPermutationsTestShuffle::test_shuffle1[lambda x: (dpnp.asarray([(i, i) for i in x], [("a", int), ("b", int)]).view(dpnp.recarray))]
 tests/test_random.py::TestPermutationsTestShuffle::test_shuffle1[lambda x: dpnp.asarray([(i, i) for i in x], [("a", object), ("b", dpnp.int32)])]]
 tests/test_random.py::TestPermutationsTestShuffle::test_shuffle1[lambda x: dpnp.asarray(x).astype(dpnp.int8)]

tests/skipped_tests_gpu.tbl

@@ -38,6 +38,10 @@ tests/test_linalg.py::test_svd[(5,3)-float32]
 tests/test_linalg.py::test_svd[(5,3)-float64]
 tests/test_linalg.py::test_svd[(5,3)-int32]
 tests/test_linalg.py::test_svd[(5,3)-int64]
+tests/test_linalg.py::test_svd[(2,2)-complex128]
+tests/test_linalg.py::test_svd[(3,4)-complex128]
+tests/test_linalg.py::test_svd[(5,3)-complex128]
+tests/test_linalg.py::test_svd[(16,16)-complex128]
 tests/test_random.py::TestPermutationsTestShuffle::test_shuffle1[lambda x: (dpnp.asarray([(i, i) for i in x], [("a", int), ("b", int)]).view(dpnp.recarray))]
 tests/test_random.py::TestPermutationsTestShuffle::test_shuffle1[lambda x: dpnp.asarray([(i, i) for i in x], [("a", object), ("b", dpnp.int32)])]]
 tests/test_random.py::TestPermutationsTestShuffle::test_shuffle1[lambda x: dpnp.asarray(x).astype(dpnp.int8)]