Update dpnp.linalg.inv() function

dpnp/backend/extensions/lapack/CMakeLists.txt

@@ -30,6 +30,7 @@ set(_module_src
     ${CMAKE_CURRENT_SOURCE_DIR}/gesv.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/getrf.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/getrf_batch.cpp
+    ${CMAKE_CURRENT_SOURCE_DIR}/getri_batch.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/heevd.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/potrf.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/potrf_batch.cpp

dpnp/backend/extensions/lapack/getrf_batch.cpp

@@ -116,6 +116,15 @@ static sycl::event getrf_batch_impl(sycl::queue exec_q,
         // Get the indices of the first zero diagonal elements of these matrices
         auto error_info = be.exceptions();
 
+        auto error_matrices_ids_size = error_matrices_ids.size();
+        auto dev_info_size = static_cast<std::size_t>(py::len(dev_info));
+        if (error_matrices_ids_size != dev_info_size) {
+            throw py::value_error("The size of `dev_info` must be equal to" +
+                                  std::to_string(error_matrices_ids_size) +
+                                  ", but currently it is " +
+                                  std::to_string(dev_info_size) + ".");
+        }
+
         for (size_t i = 0; i < error_matrices_ids.size(); ++i) {
             // Assign the index of the first zero diagonal element in each
             // error matrix to the corresponding index in 'dev_info'
@@ -190,6 +199,14 @@ std::pair<sycl::event, sycl::event>
                               ", but a 2-dimensional array is expected.");
     }
 
+    const int dev_info_size = py::len(dev_info);
+    if (dev_info_size != batch_size) {
+        throw py::value_error("The size of 'dev_info' (" +
+                              std::to_string(dev_info_size) +
+                              ") does not match the expected batch size (" +
+                              std::to_string(batch_size) + ").");
+    }
+
     // check compatibility of execution queue and allocation queue
     if (!dpctl::utils::queues_are_compatible(exec_q, {a_array, ipiv_array})) {
         throw py::value_error(

dpnp/backend/extensions/lapack/getri.hpp

@@ -0,0 +1,56 @@
+//*****************************************************************************
+// Copyright (c) 2024, Intel Corporation
+// All rights reserved.
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+// - Redistributions of source code must retain the above copyright notice,
+//   this list of conditions and the following disclaimer.
+// - Redistributions in binary form must reproduce the above copyright notice,
+//   this list of conditions and the following disclaimer in the documentation
+//   and/or other materials provided with the distribution.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
+// THE POSSIBILITY OF SUCH DAMAGE.
+//*****************************************************************************
+
+#pragma once
+
+#include <CL/sycl.hpp>
+#include <oneapi/mkl.hpp>
+
+#include <dpctl4pybind11.hpp>
+
+namespace dpnp
+{
+namespace backend
+{
+namespace ext
+{
+namespace lapack
+{
+extern std::pair<sycl::event, sycl::event>
+    getri_batch(sycl::queue exec_q,
+                dpctl::tensor::usm_ndarray a_array,
+                dpctl::tensor::usm_ndarray ipiv_array,
+                py::list dev_info,
+                std::int64_t n,
+                std::int64_t stride_a,
+                std::int64_t stride_ipiv,
+                std::int64_t batch_size,
+                const std::vector<sycl::event> &depends = {});
+
+extern void init_getri_batch_dispatch_vector(void);
+} // namespace lapack
+} // namespace ext
+} // namespace backend
+} // namespace dpnp

dpnp/backend/extensions/lapack/getri_batch.cpp

@@ -0,0 +1,293 @@
+//*****************************************************************************
+// Copyright (c) 2024, Intel Corporation
+// All rights reserved.
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+// - Redistributions of source code must retain the above copyright notice,
+//   this list of conditions and the following disclaimer.
+// - Redistributions in binary form must reproduce the above copyright notice,
+//   this list of conditions and the following disclaimer in the documentation
+//   and/or other materials provided with the distribution.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
+// THE POSSIBILITY OF SUCH DAMAGE.
+//*****************************************************************************
+
+#include <pybind11/pybind11.h>
+
+// dpctl tensor headers
+#include "utils/memory_overlap.hpp"
+#include "utils/type_utils.hpp"
+
+#include "getri.hpp"
+#include "types_matrix.hpp"
+
+#include "dpnp_utils.hpp"
+
+namespace dpnp
+{
+namespace backend
+{
+namespace ext
+{
+namespace lapack
+{
+namespace mkl_lapack = oneapi::mkl::lapack;
+namespace py = pybind11;
+namespace type_utils = dpctl::tensor::type_utils;
+
+typedef sycl::event (*getri_batch_impl_fn_ptr_t)(
+    sycl::queue,
+    std::int64_t,
+    char *,
+    std::int64_t,
+    std::int64_t,
+    std::int64_t *,
+    std::int64_t,
+    std::int64_t,
+    py::list,
+    std::vector<sycl::event> &,
+    const std::vector<sycl::event> &);
+
+static getri_batch_impl_fn_ptr_t
+    getri_batch_dispatch_vector[dpctl_td_ns::num_types];
+
+template <typename T>
+static sycl::event getri_batch_impl(sycl::queue exec_q,
+                                    std::int64_t n,
+                                    char *in_a,
+                                    std::int64_t lda,
+                                    std::int64_t stride_a,
+                                    std::int64_t *ipiv,
+                                    std::int64_t stride_ipiv,
+                                    std::int64_t batch_size,
+                                    py::list dev_info,
+                                    std::vector<sycl::event> &host_task_events,
+                                    const std::vector<sycl::event> &depends)
+{
+    type_utils::validate_type_for_device<T>(exec_q);
+
+    T *a = reinterpret_cast<T *>(in_a);
+
+    const std::int64_t scratchpad_size =
+        mkl_lapack::getri_batch_scratchpad_size<T>(exec_q, n, lda, stride_a,
+                                                   stride_ipiv, batch_size);
+    T *scratchpad = nullptr;
+
+    std::stringstream error_msg;
+    std::int64_t info = 0;
+    bool is_exception_caught = false;
+
+    sycl::event getri_batch_event;
+    try {
+        scratchpad = sycl::malloc_device<T>(scratchpad_size, exec_q);
+
+        getri_batch_event = mkl_lapack::getri_batch(
+            exec_q,
+            n, // The order of each square matrix in the batch; (0 ≤ n).
+               // It must be a non-negative integer.
+            a, // Pointer to the batch of square matrices, each of size (n x n).
+            lda,      // The leading dimension of each matrix in the batch.
+            stride_a, // Stride between consecutive matrices in the batch.
+            ipiv, // Pointer to the array of pivot indices for each matrix in
+                  // the batch.
+            stride_ipiv, // Stride between pivot indices: Spacing between pivot
+                         // arrays in 'ipiv'.
+            batch_size,  // Total number of matrices in the batch.
+            scratchpad,  // Pointer to scratchpad memory to be used by MKL
+                         // routine for storing intermediate results.
+            scratchpad_size, depends);
+    } catch (mkl_lapack::batch_error const &be) {
+        // Get the indices of matrices within the batch that encountered an
+        // error
+        auto error_matrices_ids = be.ids();
+        // Get the indices of the first zero diagonal elements of these matrices
+        auto error_info = be.exceptions();
+
+        auto error_matrices_ids_size = error_matrices_ids.size();
+        auto dev_info_size = static_cast<std::size_t>(py::len(dev_info));
+        if (error_matrices_ids_size != dev_info_size) {
+            throw py::value_error("The size of `dev_info` must be equal to" +
+                                  std::to_string(error_matrices_ids_size) +
+                                  ", but currently it is " +
+                                  std::to_string(dev_info_size) + ".");
+        }
+
+        for (size_t i = 0; i < error_matrices_ids.size(); ++i) {
+            // Assign the index of the first zero diagonal element in each
+            // error matrix to the corresponding index in 'dev_info'
+            dev_info[error_matrices_ids[i]] = error_info[i];
+        }
+    } catch (mkl_lapack::exception const &e) {
+        is_exception_caught = true;
+        info = e.info();
+
+        if (info < 0) {
+            error_msg << "Parameter number " << -info
+                      << " had an illegal value.";
+        }
+        else if (info == scratchpad_size && e.detail() != 0) {
+            error_msg
+                << "Insufficient scratchpad size. Required size is at least "
+                << e.detail();
+        }
+        else {
+            error_msg << "Unexpected MKL exception caught during getri_batch() "
+                         "call:\nreason: "
+                      << e.what() << "\ninfo: " << e.info();
+        }
+    } catch (sycl::exception const &e) {
+        is_exception_caught = true;
+        error_msg
+            << "Unexpected SYCL exception caught during getri_batch() call:\n"
+            << e.what();
+    }
+
+    if (is_exception_caught) // an unexpected error occurs
+    {
+        if (scratchpad != nullptr) {
+            sycl::free(scratchpad, exec_q);
+        }
+
+        throw std::runtime_error(error_msg.str());
+    }
+
+    sycl::event clean_up_event = exec_q.submit([&](sycl::handler &cgh) {
+        cgh.depends_on(getri_batch_event);
+        auto ctx = exec_q.get_context();
+        cgh.host_task([ctx, scratchpad]() { sycl::free(scratchpad, ctx); });
+    });
+    host_task_events.push_back(clean_up_event);
+    return getri_batch_event;
+}
+
+std::pair<sycl::event, sycl::event>
+    getri_batch(sycl::queue exec_q,
+                dpctl::tensor::usm_ndarray a_array,
+                dpctl::tensor::usm_ndarray ipiv_array,
+                py::list dev_info,
+                std::int64_t n,
+                std::int64_t stride_a,
+                std::int64_t stride_ipiv,
+                std::int64_t batch_size,
+                const std::vector<sycl::event> &depends)
+{
+    const int a_array_nd = a_array.get_ndim();
+    const int ipiv_array_nd = ipiv_array.get_ndim();
+
+    if (a_array_nd < 3) {
+        throw py::value_error(
+            "The input array has ndim=" + std::to_string(a_array_nd) +
+            ", but an array with ndim >= 3 is expected.");
+    }
+
+    if (ipiv_array_nd != 2) {
+        throw py::value_error("The array of pivot indices has ndim=" +
+                              std::to_string(ipiv_array_nd) +
+                              ", but a 2-dimensional array is expected.");
+    }
+
+    const int dev_info_size = py::len(dev_info);
+    if (dev_info_size != batch_size) {
+        throw py::value_error("The size of 'dev_info' (" +
+                              std::to_string(dev_info_size) +
+                              ") does not match the expected batch size (" +
+                              std::to_string(batch_size) + ").");
+    }
+
+    // check compatibility of execution queue and allocation queue
+    if (!dpctl::utils::queues_are_compatible(exec_q, {a_array, ipiv_array})) {
+        throw py::value_error(
+            "Execution queue is not compatible with allocation queues");
+    }
+
+    auto const &overlap = dpctl::tensor::overlap::MemoryOverlap();
+    if (overlap(a_array, ipiv_array)) {
+        throw py::value_error("The input array and the array of pivot indices "
+                              "are overlapping segments of memory");
+    }
+
+    bool is_a_array_c_contig = a_array.is_c_contiguous();
+    bool is_ipiv_array_c_contig = ipiv_array.is_c_contiguous();
+    if (!is_a_array_c_contig) {
+        throw py::value_error("The input array "
+                              "must be C-contiguous");
+    }
+    if (!is_ipiv_array_c_contig) {
+        throw py::value_error("The array of pivot indices "
+                              "must be C-contiguous");
+    }
+
+    auto array_types = dpctl_td_ns::usm_ndarray_types();
+    int a_array_type_id =
+        array_types.typenum_to_lookup_id(a_array.get_typenum());
+
+    getri_batch_impl_fn_ptr_t getri_batch_fn =
+        getri_batch_dispatch_vector[a_array_type_id];
+    if (getri_batch_fn == nullptr) {
+        throw py::value_error(
+            "No getri_batch implementation defined for the provided type "
+            "of the input matrix.");
+    }
+
+    auto ipiv_types = dpctl_td_ns::usm_ndarray_types();
+    int ipiv_array_type_id =
+        ipiv_types.typenum_to_lookup_id(ipiv_array.get_typenum());
+
+    if (ipiv_array_type_id != static_cast<int>(dpctl_td_ns::typenum_t::INT64)) {
+        throw py::value_error("The type of 'ipiv_array' must be int64.");
+    }
+
+    char *a_array_data = a_array.get_data();
+    const std::int64_t lda = std::max<size_t>(1UL, n);
+
+    char *ipiv_array_data = ipiv_array.get_data();
+    std::int64_t *d_ipiv = reinterpret_cast<std::int64_t *>(ipiv_array_data);
+
+    std::vector<sycl::event> host_task_events;
+    sycl::event getri_batch_ev = getri_batch_fn(
+        exec_q, n, a_array_data, lda, stride_a, d_ipiv, stride_ipiv, batch_size,
+        dev_info, host_task_events, depends);
+
+    sycl::event args_ev = dpctl::utils::keep_args_alive(
+        exec_q, {a_array, ipiv_array}, host_task_events);
+
+    return std::make_pair(args_ev, getri_batch_ev);
+}
+
+template <typename fnT, typename T>
+struct GetriBatchContigFactory
+{
+    fnT get()
+    {
+        if constexpr (types::GetriBatchTypePairSupportFactory<T>::is_defined) {
+            return getri_batch_impl<T>;
+        }
+        else {
+            return nullptr;
+        }
+    }
+};
+
+void init_getri_batch_dispatch_vector(void)
+{
+    dpctl_td_ns::DispatchVectorBuilder<getri_batch_impl_fn_ptr_t,
+                                       GetriBatchContigFactory,
+                                       dpctl_td_ns::num_types>
+        contig;
+    contig.populate_dispatch_vector(getri_batch_dispatch_vector);
+}
+} // namespace lapack
+} // namespace ext
+} // namespace backend
+} // namespace dpnp