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Add dpnp.linalg.solve() function (IntelPython#1598)
* Add dpnp.linalg.solve() function * Add cupy tests for dpnp.linalg.solve() * Register a LinAlgError in dpnp.linalg submodule * Implementation of dtype dispatching with _common_type for dpnp.linalg.solve * Add a common_helpers.hpp file * Add validation functions for array types and dimensions for linalg funcs * Skip test_solve_singular_empty --------- Co-authored-by: Anton <[email protected]>
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//***************************************************************************** | ||
// Copyright (c) 2023, 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. | ||
//***************************************************************************** | ||
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#pragma once | ||
#include <cstring> | ||
#include <stdexcept> | ||
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namespace dpnp | ||
{ | ||
namespace backend | ||
{ | ||
namespace ext | ||
{ | ||
namespace lapack | ||
{ | ||
namespace helper | ||
{ | ||
template <typename T> | ||
struct value_type_of | ||
{ | ||
using type = T; | ||
}; | ||
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template <typename T> | ||
struct value_type_of<std::complex<T>> | ||
{ | ||
using type = T; | ||
}; | ||
} // namespace helper | ||
} // namespace lapack | ||
} // namespace ext | ||
} // namespace backend | ||
} // namespace dpnp |
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//***************************************************************************** | ||
// Copyright (c) 2023, 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. | ||
//***************************************************************************** | ||
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#include <pybind11/pybind11.h> | ||
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// dpctl tensor headers | ||
#include "utils/memory_overlap.hpp" | ||
#include "utils/type_utils.hpp" | ||
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#include "common_helpers.hpp" | ||
#include "gesv.hpp" | ||
#include "linalg_exceptions.hpp" | ||
#include "types_matrix.hpp" | ||
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#include "dpnp_utils.hpp" | ||
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namespace dpnp | ||
{ | ||
namespace backend | ||
{ | ||
namespace ext | ||
{ | ||
namespace lapack | ||
{ | ||
namespace mkl_lapack = oneapi::mkl::lapack; | ||
namespace py = pybind11; | ||
namespace type_utils = dpctl::tensor::type_utils; | ||
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typedef sycl::event (*gesv_impl_fn_ptr_t)(sycl::queue, | ||
const std::int64_t, | ||
const std::int64_t, | ||
char *, | ||
std::int64_t, | ||
char *, | ||
std::int64_t, | ||
std::vector<sycl::event> &, | ||
const std::vector<sycl::event> &); | ||
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static gesv_impl_fn_ptr_t gesv_dispatch_vector[dpctl_td_ns::num_types]; | ||
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template <typename T> | ||
static sycl::event gesv_impl(sycl::queue exec_q, | ||
const std::int64_t n, | ||
const std::int64_t nrhs, | ||
char *in_a, | ||
std::int64_t lda, | ||
char *in_b, | ||
std::int64_t ldb, | ||
std::vector<sycl::event> &host_task_events, | ||
const std::vector<sycl::event> &depends) | ||
{ | ||
type_utils::validate_type_for_device<T>(exec_q); | ||
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T *a = reinterpret_cast<T *>(in_a); | ||
T *b = reinterpret_cast<T *>(in_b); | ||
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const std::int64_t scratchpad_size = | ||
mkl_lapack::gesv_scratchpad_size<T>(exec_q, n, nrhs, lda, ldb); | ||
T *scratchpad = nullptr; | ||
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std::int64_t *ipiv = nullptr; | ||
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std::stringstream error_msg; | ||
std::int64_t info = 0; | ||
bool sycl_exception_caught = false; | ||
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sycl::event gesv_event; | ||
try { | ||
scratchpad = sycl::malloc_device<T>(scratchpad_size, exec_q); | ||
ipiv = sycl::malloc_device<std::int64_t>(n, exec_q); | ||
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gesv_event = mkl_lapack::gesv( | ||
exec_q, | ||
n, // The order of the matrix A (0 ≤ n). | ||
nrhs, // The number of right-hand sides B (0 ≤ nrhs). | ||
a, // Pointer to the square coefficient matrix A (n x n). | ||
lda, // The leading dimension of a, must be at least max(1, n). | ||
ipiv, // The pivot indices that define the permutation matrix P; | ||
// row i of the matrix was interchanged with row ipiv(i), | ||
// must be at least max(1, n). | ||
b, // Pointer to the right hand side matrix B (n x nrhs). | ||
ldb, // The leading dimension of b, must be at least max(1, n). | ||
scratchpad, // Pointer to scratchpad memory to be used by MKL | ||
// routine for storing intermediate results. | ||
scratchpad_size, depends); | ||
} catch (mkl_lapack::exception const &e) { | ||
info = e.info(); | ||
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if (info < 0) { | ||
error_msg << "Parameter number " << -info | ||
<< " had an illegal value."; | ||
} | ||
else if (info > 0) { | ||
T host_U; | ||
exec_q.memcpy(&host_U, &a[(info - 1) * lda + info - 1], sizeof(T)) | ||
.wait(); | ||
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using ThresholdType = typename helper::value_type_of<T>::type; | ||
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const auto threshold = | ||
std::numeric_limits<ThresholdType>::epsilon() * 100; | ||
if (std::abs(host_U) < threshold) { | ||
sycl::free(scratchpad, exec_q); | ||
throw LinAlgError("The input coefficient matrix is singular."); | ||
} | ||
else { | ||
error_msg << "Unexpected MKL exception caught during gesv() " | ||
"call:\nreason: " | ||
<< e.what() << "\ninfo: " << e.info(); | ||
} | ||
} | ||
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 gesv() " | ||
"call:\nreason: " | ||
<< e.what() << "\ninfo: " << e.info(); | ||
} | ||
} catch (sycl::exception const &e) { | ||
error_msg << "Unexpected SYCL exception caught during gesv() call:\n" | ||
<< e.what(); | ||
sycl_exception_caught = true; | ||
} | ||
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if (info != 0 || sycl_exception_caught) // an unexpected error occurs | ||
{ | ||
if (scratchpad != nullptr) { | ||
sycl::free(scratchpad, exec_q); | ||
} | ||
if (ipiv != nullptr) { | ||
sycl::free(ipiv, exec_q); | ||
} | ||
throw std::runtime_error(error_msg.str()); | ||
} | ||
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sycl::event clean_up_event = exec_q.submit([&](sycl::handler &cgh) { | ||
cgh.depends_on(gesv_event); | ||
auto ctx = exec_q.get_context(); | ||
cgh.host_task([ctx, scratchpad, ipiv]() { | ||
sycl::free(scratchpad, ctx); | ||
sycl::free(ipiv, ctx); | ||
}); | ||
}); | ||
host_task_events.push_back(clean_up_event); | ||
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return gesv_event; | ||
} | ||
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std::pair<sycl::event, sycl::event> | ||
gesv(sycl::queue exec_q, | ||
dpctl::tensor::usm_ndarray coeff_matrix, | ||
dpctl::tensor::usm_ndarray dependent_vals, | ||
const std::vector<sycl::event> &depends) | ||
{ | ||
const int coeff_matrix_nd = coeff_matrix.get_ndim(); | ||
const int dependent_vals_nd = dependent_vals.get_ndim(); | ||
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if (coeff_matrix_nd != 2) { | ||
throw py::value_error("The coefficient matrix has ndim=" + | ||
std::to_string(coeff_matrix_nd) + | ||
", but a 2-dimensional array is expected."); | ||
} | ||
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if (dependent_vals_nd > 2) { | ||
throw py::value_error( | ||
"The dependent values array has ndim=" + | ||
std::to_string(dependent_vals_nd) + | ||
", but a 1-dimensional or a 2-dimensional array is expected."); | ||
} | ||
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const py::ssize_t *coeff_matrix_shape = coeff_matrix.get_shape_raw(); | ||
const py::ssize_t *dependent_vals_shape = dependent_vals.get_shape_raw(); | ||
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if (coeff_matrix_shape[0] != coeff_matrix_shape[1]) { | ||
throw py::value_error("The coefficient matrix must be square," | ||
" but got a shape of (" + | ||
std::to_string(coeff_matrix_shape[0]) + ", " + | ||
std::to_string(coeff_matrix_shape[1]) + ")."); | ||
} | ||
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// check compatibility of execution queue and allocation queue | ||
if (!dpctl::utils::queues_are_compatible(exec_q, | ||
{coeff_matrix, dependent_vals})) | ||
{ | ||
throw py::value_error( | ||
"Execution queue is not compatible with allocation queues"); | ||
} | ||
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auto const &overlap = dpctl::tensor::overlap::MemoryOverlap(); | ||
if (overlap(coeff_matrix, dependent_vals)) { | ||
throw py::value_error( | ||
"The arrays of coefficients and dependent variables " | ||
"are overlapping segments of memory"); | ||
} | ||
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bool is_coeff_matrix_f_contig = coeff_matrix.is_f_contiguous(); | ||
if (!is_coeff_matrix_f_contig) { | ||
throw py::value_error("The coefficient matrix " | ||
"must be F-contiguous"); | ||
} | ||
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bool is_dependent_vals_f_contig = dependent_vals.is_f_contiguous(); | ||
if (!is_dependent_vals_f_contig) { | ||
throw py::value_error("The array of dependent variables " | ||
"must be F-contiguous"); | ||
} | ||
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auto array_types = dpctl_td_ns::usm_ndarray_types(); | ||
int coeff_matrix_type_id = | ||
array_types.typenum_to_lookup_id(coeff_matrix.get_typenum()); | ||
int dependent_vals_type_id = | ||
array_types.typenum_to_lookup_id(dependent_vals.get_typenum()); | ||
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if (coeff_matrix_type_id != dependent_vals_type_id) { | ||
throw py::value_error("The types of the coefficient matrix and " | ||
"dependent variables are mismatched"); | ||
} | ||
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gesv_impl_fn_ptr_t gesv_fn = gesv_dispatch_vector[coeff_matrix_type_id]; | ||
if (gesv_fn == nullptr) { | ||
throw py::value_error( | ||
"No gesv implementation defined for the provided type " | ||
"of the coefficient matrix."); | ||
} | ||
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char *coeff_matrix_data = coeff_matrix.get_data(); | ||
char *dependent_vals_data = dependent_vals.get_data(); | ||
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const std::int64_t n = coeff_matrix_shape[0]; | ||
const std::int64_t m = dependent_vals_shape[0]; | ||
const std::int64_t nrhs = | ||
(dependent_vals_nd > 1) ? dependent_vals_shape[1] : 1; | ||
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const std::int64_t lda = std::max<size_t>(1UL, n); | ||
const std::int64_t ldb = std::max<size_t>(1UL, m); | ||
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std::vector<sycl::event> host_task_events; | ||
sycl::event gesv_ev = | ||
gesv_fn(exec_q, n, nrhs, coeff_matrix_data, lda, dependent_vals_data, | ||
ldb, host_task_events, depends); | ||
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sycl::event args_ev = dpctl::utils::keep_args_alive( | ||
exec_q, {coeff_matrix, dependent_vals}, host_task_events); | ||
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return std::make_pair(args_ev, gesv_ev); | ||
} | ||
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template <typename fnT, typename T> | ||
struct GesvContigFactory | ||
{ | ||
fnT get() | ||
{ | ||
if constexpr (types::GesvTypePairSupportFactory<T>::is_defined) { | ||
return gesv_impl<T>; | ||
} | ||
else { | ||
return nullptr; | ||
} | ||
} | ||
}; | ||
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void init_gesv_dispatch_vector(void) | ||
{ | ||
dpctl_td_ns::DispatchVectorBuilder<gesv_impl_fn_ptr_t, GesvContigFactory, | ||
dpctl_td_ns::num_types> | ||
contig; | ||
contig.populate_dispatch_vector(gesv_dispatch_vector); | ||
} | ||
} // namespace lapack | ||
} // namespace ext | ||
} // namespace backend | ||
} // namespace dpnp |
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