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Impementation of dpctl.tensor.less function #1235

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2 changes: 2 additions & 0 deletions dpctl/tensor/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -105,6 +105,7 @@
isfinite,
isinf,
isnan,
less,
log,
log1p,
multiply,
Expand Down Expand Up @@ -202,6 +203,7 @@
"isinf",
"isnan",
"isfinite",
"less",
"log",
"log1p",
"proj",
Expand Down
28 changes: 27 additions & 1 deletion dpctl/tensor/_elementwise_funcs.py
Original file line number Diff line number Diff line change
Expand Up @@ -405,7 +405,33 @@
)

# B13: ==== LESS (x1, x2)
# FIXME: implement B13
_less_docstring_ = """
less(x1, x2, out=None, order='K')

Computes the less-than test results for each element `x1_i` of
the input array `x1` the respective element `x2_i` of the input array `x2`.

Args:
x1 (usm_ndarray):
First input array, expected to have numeric data type.
x2 (usm_ndarray):
Second input array, also expected to have numeric data type.
out ({None, usm_ndarray}, optional):
Output array to populate.
Array have the correct shape and the expected data type.
order ("C","F","A","K", optional):
Memory layout of the newly output array, if parameter `out` is `None`.
Default: "K".
Returns:
usm_narray:
An array containing the result of element-wise less-than comparison.
The data type of the returned array is determined by the
Type Promotion Rules.
"""

less = BinaryElementwiseFunc(
"less", ti._less_result_type, ti._less, _less_docstring_
)

# B14: ==== LESS_EQUAL (x1, x2)
# FIXME: implement B14
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,316 @@
//=== less.hpp - Binary function LESS ------ *-C++-*--/===//
//
// Data Parallel Control (dpctl)
//
// Copyright 2020-2023 Intel Corporation
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain in1 copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
//===---------------------------------------------------------------------===//
///
/// \file
/// This file defines kernels for elementwise evaluation of comparison of
/// tensor elements.
//===---------------------------------------------------------------------===//

#pragma once
#include <CL/sycl.hpp>
#include <cstddef>
#include <cstdint>
#include <type_traits>

#include "utils/offset_utils.hpp"
#include "utils/type_dispatch.hpp"
#include "utils/type_utils.hpp"

#include "kernels/elementwise_functions/common.hpp"
#include <pybind11/pybind11.h>

namespace dpctl
{
namespace tensor
{
namespace kernels
{
namespace less
{

namespace py = pybind11;
namespace td_ns = dpctl::tensor::type_dispatch;
namespace tu_ns = dpctl::tensor::type_utils;

template <typename argT1, typename argT2, typename resT> struct LessFunctor
{
static_assert(std::is_same_v<resT, bool>);

using supports_sg_loadstore = std::negation<
std::disjunction<tu_ns::is_complex<argT1>, tu_ns::is_complex<argT2>>>;
using supports_vec = std::conjunction<
std::is_same<argT1, argT2>,
std::negation<std::disjunction<tu_ns::is_complex<argT1>,
tu_ns::is_complex<argT2>>>>;

resT operator()(const argT1 &in1, const argT2 &in2)
{
if constexpr (std::is_same_v<argT1, std::complex<float>> &&
std::is_same_v<argT2, float>)
{
float real1 = std::real(in1);
return (real1 == in2) ? (std::imag(in1) < 0.0f) : real1 < in2;
}
else if constexpr (std::is_same_v<argT1, float> &&
std::is_same_v<argT2, std::complex<float>>)
{
float real2 = std::real(in2);
return (in1 == real2) ? (0.0f < std::imag(in2)) : in1 < real2;
}
else if constexpr (tu_ns::is_complex<argT1>::value ||
tu_ns::is_complex<argT2>::value)
{
static_assert(std::is_same_v<argT1, argT2>);
using realT = typename argT1::value_type;
realT real1 = std::real(in1);
realT real2 = std::real(in2);

return (real1 == real2) ? (std::imag(in1) < std::imag(in2))
: real1 < real2;
}
else {
return (in1 < in2);
}
}

template <int vec_sz>
sycl::vec<resT, vec_sz> operator()(const sycl::vec<argT1, vec_sz> &in1,
const sycl::vec<argT2, vec_sz> &in2)
{

auto tmp = (in1 < in2);

if constexpr (std::is_same_v<resT,
typename decltype(tmp)::element_type>) {
return tmp;
}
else {
using dpctl::tensor::type_utils::vec_cast;

return vec_cast<resT, typename decltype(tmp)::element_type, vec_sz>(
tmp);
}
}
};

template <typename argT1,
typename argT2,
typename resT,
unsigned int vec_sz = 4,
unsigned int n_vecs = 2>
using LessContigFunctor =
elementwise_common::BinaryContigFunctor<argT1,
argT2,
resT,
LessFunctor<argT1, argT2, resT>,
vec_sz,
n_vecs>;

template <typename argT1, typename argT2, typename resT, typename IndexerT>
using LessStridedFunctor =
elementwise_common::BinaryStridedFunctor<argT1,
argT2,
resT,
IndexerT,
LessFunctor<argT1, argT2, resT>>;

template <typename T1, typename T2> struct LessOutputType
{
using value_type = typename std::disjunction< // disjunction is C++17
// feature, supported by DPC++
td_ns::BinaryTypeMapResultEntry<T1, bool, T2, bool, bool>,
td_ns::
BinaryTypeMapResultEntry<T1, std::uint8_t, T2, std::uint8_t, bool>,
td_ns::BinaryTypeMapResultEntry<T1, std::int8_t, T2, std::int8_t, bool>,
td_ns::BinaryTypeMapResultEntry<T1,
std::uint16_t,
T2,
std::uint16_t,
bool>,
td_ns::
BinaryTypeMapResultEntry<T1, std::int16_t, T2, std::int16_t, bool>,
td_ns::BinaryTypeMapResultEntry<T1,
std::uint32_t,
T2,
std::uint32_t,
bool>,
td_ns::
BinaryTypeMapResultEntry<T1, std::int32_t, T2, std::int32_t, bool>,
td_ns::BinaryTypeMapResultEntry<T1,
std::uint64_t,
T2,
std::uint64_t,
bool>,
td_ns::
BinaryTypeMapResultEntry<T1, std::int64_t, T2, std::int64_t, bool>,
td_ns::BinaryTypeMapResultEntry<T1, sycl::half, T2, sycl::half, bool>,
td_ns::BinaryTypeMapResultEntry<T1, float, T2, float, bool>,
td_ns::BinaryTypeMapResultEntry<T1, double, T2, double, bool>,
td_ns::BinaryTypeMapResultEntry<T1,
std::complex<float>,
T2,
std::complex<float>,
bool>,
td_ns::BinaryTypeMapResultEntry<T1,
std::complex<double>,
T2,
std::complex<double>,
bool>,
td_ns::
BinaryTypeMapResultEntry<T1, float, T2, std::complex<float>, bool>,
td_ns::
BinaryTypeMapResultEntry<T1, std::complex<float>, T2, float, bool>,
td_ns::DefaultResultEntry<void>>::result_type;
};

template <typename argT1,
typename argT2,
typename resT,
unsigned int vec_sz,
unsigned int n_vecs>
class less_contig_kernel;

template <typename argTy1, typename argTy2>
sycl::event less_contig_impl(sycl::queue exec_q,
size_t nelems,
const char *arg1_p,
py::ssize_t arg1_offset,
const char *arg2_p,
py::ssize_t arg2_offset,
char *res_p,
py::ssize_t res_offset,
const std::vector<sycl::event> &depends = {})
{
sycl::event comp_ev = exec_q.submit([&](sycl::handler &cgh) {
cgh.depends_on(depends);

size_t lws = 64;
constexpr unsigned int vec_sz = 4;
constexpr unsigned int n_vecs = 2;
const size_t n_groups =
((nelems + lws * n_vecs * vec_sz - 1) / (lws * n_vecs * vec_sz));
const auto gws_range = sycl::range<1>(n_groups * lws);
const auto lws_range = sycl::range<1>(lws);

using resTy = typename LessOutputType<argTy1, argTy2>::value_type;

const argTy1 *arg1_tp =
reinterpret_cast<const argTy1 *>(arg1_p) + arg1_offset;
const argTy2 *arg2_tp =
reinterpret_cast<const argTy2 *>(arg2_p) + arg2_offset;
resTy *res_tp = reinterpret_cast<resTy *>(res_p) + res_offset;

cgh.parallel_for<
less_contig_kernel<argTy1, argTy2, resTy, vec_sz, n_vecs>>(
sycl::nd_range<1>(gws_range, lws_range),
LessContigFunctor<argTy1, argTy2, resTy, vec_sz, n_vecs>(
arg1_tp, arg2_tp, res_tp, nelems));
});
return comp_ev;
}

template <typename fnT, typename T1, typename T2> struct LessContigFactory
{
fnT get()
{
if constexpr (std::is_same_v<
typename LessOutputType<T1, T2>::value_type, void>) {
fnT fn = nullptr;
return fn;
}
else {
fnT fn = less_contig_impl<T1, T2>;
return fn;
}
}
};

template <typename fnT, typename T1, typename T2> struct LessTypeMapFactory
{
/*! @brief get typeid for output type of operator()>(x, y), always bool */
std::enable_if_t<std::is_same<fnT, int>::value, int> get()
{
using rT = typename LessOutputType<T1, T2>::value_type;
return td_ns::GetTypeid<rT>{}.get();
}
};

template <typename T1, typename T2, typename resT, typename IndexerT>
class less_strided_strided_kernel;

template <typename argTy1, typename argTy2>
sycl::event
less_strided_impl(sycl::queue exec_q,
size_t nelems,
int nd,
const py::ssize_t *shape_and_strides,
const char *arg1_p,
py::ssize_t arg1_offset,
const char *arg2_p,
py::ssize_t arg2_offset,
char *res_p,
py::ssize_t res_offset,
const std::vector<sycl::event> &depends,
const std::vector<sycl::event> &additional_depends)
{
sycl::event comp_ev = exec_q.submit([&](sycl::handler &cgh) {
cgh.depends_on(depends);
cgh.depends_on(additional_depends);

using resTy = typename LessOutputType<argTy1, argTy2>::value_type;

using IndexerT =
typename dpctl::tensor::offset_utils::ThreeOffsets_StridedIndexer;

IndexerT indexer{nd, arg1_offset, arg2_offset, res_offset,
shape_and_strides};

const argTy1 *arg1_tp = reinterpret_cast<const argTy1 *>(arg1_p);
const argTy2 *arg2_tp = reinterpret_cast<const argTy2 *>(arg2_p);
resTy *res_tp = reinterpret_cast<resTy *>(res_p);

cgh.parallel_for<
less_strided_strided_kernel<argTy1, argTy2, resTy, IndexerT>>(
{nelems}, LessStridedFunctor<argTy1, argTy2, resTy, IndexerT>(
arg1_tp, arg2_tp, res_tp, indexer));
});
return comp_ev;
}

template <typename fnT, typename T1, typename T2> struct LessStridedFactory
{
fnT get()
{
if constexpr (std::is_same_v<
typename LessOutputType<T1, T2>::value_type, void>) {
fnT fn = nullptr;
return fn;
}
else {
fnT fn = less_strided_impl<T1, T2>;
return fn;
}
}
};

} // namespace less
} // namespace kernels
} // namespace tensor
} // namespace dpctl
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