modifying dpnp.linalg.det function

Author: vtavana

dpnp/linalg/dpnp_algo_linalg.pyx

@@ -142,15 +142,9 @@ cpdef object dpnp_cond(object input, object p):
 cpdef utils.dpnp_descriptor dpnp_det(utils.dpnp_descriptor input):
     cdef shape_type_c input_shape = input.shape
     cdef size_t n = input.shape[-1]
-    cdef size_t size_out = 1
+    cdef shape_type_c result_shape = (1,)
     if input.ndim != 2:
-        output_shape = tuple((list(input.shape))[:-2])
-        for i in range(len(output_shape)):
-            size_out *= output_shape[i]
-
-    cdef shape_type_c result_shape = (size_out,)
-    if size_out > 1:
-        result_shape = output_shape
+        result_shape = tuple((list(input.shape))[:-2])
 
     cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(input.dtype)
 

dpnp/linalg/dpnp_iface_linalg.py

@@ -159,7 +159,9 @@ def det(input):
 
     x1_desc = dpnp.get_dpnp_descriptor(input, copy_when_nondefault_queue=False)
     if x1_desc:
-        if x1_desc.shape[-1] == x1_desc.shape[-2]:
+        if x1_desc.ndim < 2:
+            pass
+        elif x1_desc.shape[-1] == x1_desc.shape[-2]:
             result_obj = dpnp_det(x1_desc).get_pyobj()
             result = dpnp.convert_single_elem_array_to_scalar(result_obj)
 

tests/test_linalg.py

@@ -128,6 +128,20 @@ def test_det(array):
     assert_allclose(expected, result)
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
+def test_det_empty():
+    a = numpy.empty((0,0,2,2), dtype=numpy.float32)
+    ia = inp.array(a)
+
+    np_det = numpy.linalg.det(a)
+    dpnp_det = inp.linalg.det(ia)
+
+    assert dpnp_det.dtype == np_det.dtype
+    assert dpnp_det.shape == np_det.shape
+
+    assert_allclose(np_det,dpnp_det)
+
+    
 @pytest.mark.parametrize("type", get_all_dtypes(no_bool=True, no_complex=True))
 @pytest.mark.parametrize("size", [2, 4, 8, 16, 300])
 def test_eig_arange(type, size):
@@ -388,7 +402,7 @@ def test_qr(type, shape, mode):
     # check decomposition
     assert_allclose(
         ia,
-        numpy.dot(inp.asnumpy(dpnp_q), inp.asnumpy(dpnp_r)),
+        inp.dot(dpnp_q, dpnp_r),
         rtol=tol,
         atol=tol,
     )
@@ -409,6 +423,35 @@ def test_qr(type, shape, mode):
     assert_allclose(dpnp_r, np_r, rtol=tol, atol=tol)
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
+def test_qr_not_2D():
+    a = numpy.arange(12, dtype=numpy.float32).reshape((3,2,2))
+    ia = inp.array(a)
+
+    np_q, np_r = numpy.linalg.qr(a)
+    dpnp_q, dpnp_r = inp.linalg.qr(ia)
+
+    assert dpnp_q.dtype == np_q.dtype
+    assert dpnp_r.dtype == np_r.dtype
+    assert dpnp_q.shape == np_q.shape
+    assert dpnp_r.shape == np_r.shape
+
+    assert_allclose(ia,inp.matmul(dpnp_q, dpnp_r))
+
+    a = numpy.empty((0,3,2), dtype=numpy.float32)
+    ia = inp.array(a)
+
+    np_q, np_r = numpy.linalg.qr(a)
+    dpnp_q, dpnp_r = inp.linalg.qr(ia)
+
+    assert dpnp_q.dtype == np_q.dtype
+    assert dpnp_r.dtype == np_r.dtype
+    assert dpnp_q.shape == np_q.shape
+    assert dpnp_r.shape == np_r.shape
+
+    assert_allclose(ia,inp.matmul(dpnp_q, dpnp_r))
+
+
 @pytest.mark.parametrize("type", get_all_dtypes(no_bool=True, no_complex=True))
 @pytest.mark.parametrize(
     "shape",