Merge 5b5a2a5 into 8584a2f

Author: vlad-perevezentsev

dpnp/backend/extensions/lapack/getrs.cpp

@@ -166,6 +166,7 @@ std::pair<sycl::event, sycl::event>
           const dpctl::tensor::usm_ndarray &a_array,
           const dpctl::tensor::usm_ndarray &ipiv_array,
           const dpctl::tensor::usm_ndarray &b_array,
+          const int trans_code,
           const std::vector<sycl::event> &depends)
 {
     const int a_array_nd = a_array.get_ndim();
@@ -264,11 +265,20 @@ std::pair<sycl::event, sycl::event>
     const std::int64_t lda = std::max<size_t>(1UL, n);
     const std::int64_t ldb = std::max<size_t>(1UL, n);
 
-    // Use transpose::T if the LU-factorized array is passed as C-contiguous.
-    // For F-contiguous we use transpose::N.
-    oneapi::mkl::transpose trans = is_a_array_c_contig
-                                       ? oneapi::mkl::transpose::T
-                                       : oneapi::mkl::transpose::N;
+    oneapi::mkl::transpose trans;
+    switch (trans_code) {
+    case 0:
+        trans = oneapi::mkl::transpose::N;
+        break;
+    case 1:
+        trans = oneapi::mkl::transpose::T;
+        break;
+    case 2:
+        trans = oneapi::mkl::transpose::C;
+        break;
+    default:
+        throw py::value_error("`trans_code` must be 0 (N), 1 (T), or 2 (C)");
+    }
 
     char *a_array_data = a_array.get_data();
     char *b_array_data = b_array.get_data();

dpnp/backend/extensions/lapack/getrs.hpp

@@ -37,6 +37,7 @@ extern std::pair<sycl::event, sycl::event>
           const dpctl::tensor::usm_ndarray &a_array,
           const dpctl::tensor::usm_ndarray &ipiv_array,
           const dpctl::tensor::usm_ndarray &b_array,
+          const int trans_code,
           const std::vector<sycl::event> &depends = {});
 
 extern void init_getrs_dispatch_vector(void);

dpnp/backend/extensions/lapack/lapack_py.cpp

@@ -160,7 +160,8 @@ PYBIND11_MODULE(_lapack_impl, m)
           "the solves of linear equations with an LU-factored "
           "square coefficient matrix, with multiple right-hand sides",
           py::arg("sycl_queue"), py::arg("a_array"), py::arg("ipiv_array"),
-          py::arg("b_array"), py::arg("depends") = py::list());
+          py::arg("b_array"), py::arg("trans_code"),
+          py::arg("depends") = py::list());
 
     m.def("_orgqr_batch", &lapack_ext::orgqr_batch,
           "Call `_orgqr_batch` from OneMKL LAPACK library to return "

dpnp/linalg/dpnp_utils_linalg.py

@@ -2632,6 +2632,12 @@ def dpnp_solve(a, b):
     _manager = dpu.SequentialOrderManager[exec_q]
     dev_evs = _manager.submitted_events
 
+    # TODO: remove after PR #2558 is merged
+    # Temporarily set trans_code=1 (transpose) because the LU-factorized
+    # array is C-contiguous.
+    # For F-contiguous arrays use 0 (non-transpose)
+    trans_code = 1
+
     # use DPCTL tensor function to fill the сopy of the input array
     # from the input array
     ht_ev, a_copy_ev = ti._copy_usm_ndarray_into_usm_ndarray(
@@ -2688,6 +2694,7 @@ def dpnp_solve(a, b):
         a_h.get_array(),
         ipiv_h.get_array(),
         b_h.get_array(),
+        trans_code,
         depends=[b_copy_ev, getrf_ev],
     )
     _manager.add_event_pair(ht_ev, getrs_ev)