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oleksandr-pavlykoleksandr-pavlyk
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Factored out device-capabilities into dedicated file
1 parent f498829 commit 51fd051

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4 files changed

+205
-83
lines changed

4 files changed

+205
-83
lines changed

‎dpctl/tensor/CMakeLists.txt

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@@ -26,6 +26,7 @@ pybind11_add_module(${python_module_name} MODULE
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${CMAKE_CURRENT_SOURCE_DIR}/libtensor/source/eye_ctor.cpp
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${CMAKE_CURRENT_SOURCE_DIR}/libtensor/source/full_ctor.cpp
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${CMAKE_CURRENT_SOURCE_DIR}/libtensor/source/triul_ctor.cpp
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${CMAKE_CURRENT_SOURCE_DIR}/libtensor/source/device_support_queries.cpp
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)
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target_link_options(${python_module_name} PRIVATE -fsycl-device-code-split=per_kernel)
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target_include_directories(${python_module_name}

‎dpctl/tensor/libtensor/source/device_support_queries.cpp

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@@ -0,0 +1,118 @@
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//===-- ------------ Implementation of _tensor_impl module ----*-C++-*-/===//
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//
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// Data Parallel Control (dpctl)
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//
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// Copyright 2020-2022 Intel Corporation
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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//===--------------------------------------------------------------------===//
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///
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/// \file
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/// This file defines functions of dpctl.tensor._tensor_impl extensions
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//===--------------------------------------------------------------------===//
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#include <string>
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#include "dpctl4pybind11.hpp"
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#include <CL/sycl.hpp>
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#include <pybind11/pybind11.h>
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#include <pybind11/stl.h>
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namespace dpctl
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{
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namespace tensor
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{
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namespace py_internal
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{
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namespace
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{
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std::string _default_device_fp_type(sycl::device d)
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{
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if (d.has(sycl::aspect::fp64)) {
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return "f8";
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}
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else {
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return "f4";
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}
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}
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std::string _default_device_int_type(sycl::device)
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{
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return "i8";
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}
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std::string _default_device_complex_type(sycl::device d)
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{
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if (d.has(sycl::aspect::fp64)) {
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return "c16";
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}
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else {
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return "c8";
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}
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}
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std::string _default_device_bool_type(sycl::device)
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{
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return "b1";
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}
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sycl::device _extract_device(py::object arg)
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{
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auto &api = dpctl::detail::dpctl_capi::get();
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PyObject *source = arg.ptr();
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if (api.PySyclQueue_Check_(source)) {
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sycl::queue q = py::cast<sycl::queue>(arg);
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return q.get_device();
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}
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else if (api.PySyclDevice_Check_(source)) {
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return py::cast<sycl::device>(arg);
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}
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else {
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throw py::type_error(
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"Expected type `dpctl.SyclQueue` or `dpctl.SyclDevice`.");
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}
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}
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} // namespace
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std::string default_device_fp_type(py::object arg)
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{
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sycl::device d = _extract_device(arg);
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return _default_device_fp_type(d);
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}
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std::string default_device_int_type(py::object arg)
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{
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sycl::device d = _extract_device(arg);
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return _default_device_int_type(d);
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}
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std::string default_device_bool_type(py::object arg)
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{
106+
sycl::device d = _extract_device(arg);
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return _default_device_bool_type(d);
108+
}
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std::string default_device_complex_type(py::object arg)
111+
{
112+
sycl::device d = _extract_device(arg);
113+
return _default_device_complex_type(d);
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}
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} // namespace py_internal
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} // namespace tensor
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} // namespace dpctl

‎dpctl/tensor/libtensor/source/device_support_queries.hpp

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@@ -0,0 +1,47 @@
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//===-- ------------ Implementation of _tensor_impl module ----*-C++-*-/===//
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//
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// Data Parallel Control (dpctl)
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//
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// Copyright 2020-2022 Intel Corporation
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//
7+
// Licensed under the Apache License, Version 2.0 (the "License");
8+
// you may not use this file except in compliance with the License.
9+
// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
14+
// distributed under the License is distributed on an "AS IS" BASIS,
15+
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
16+
// See the License for the specific language governing permissions and
17+
// limitations under the License.
18+
//
19+
//===--------------------------------------------------------------------===//
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///
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/// \file
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/// This file defines functions of dpctl.tensor._tensor_impl extensions
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//===--------------------------------------------------------------------===//
24+
25+
#pragma once
26+
#include <string>
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28+
#include "dpctl4pybind11.hpp"
29+
#include <CL/sycl.hpp>
30+
#include <pybind11/pybind11.h>
31+
#include <pybind11/stl.h>
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33+
namespace dpctl
34+
{
35+
namespace tensor
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{
37+
namespace py_internal
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{
39+
40+
extern std::string default_device_fp_type(py::object);
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extern std::string default_device_int_type(py::object);
42+
extern std::string default_device_bool_type(py::object);
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extern std::string default_device_complex_type(py::object);
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} // namespace py_internal
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} // namespace tensor
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} // namespace dpctl

‎dpctl/tensor/libtensor/source/tensor_py.cpp

Lines changed: 39 additions & 83 deletions
Original file line numberDiff line numberDiff line change
@@ -26,7 +26,6 @@
2626
#include <algorithm>
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#include <complex>
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#include <cstdint>
29-
#include <pybind11/complex.h>
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#include <pybind11/pybind11.h>
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#include <pybind11/stl.h>
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#include <thread>
@@ -37,6 +36,7 @@
3736
#include "copy_and_cast_usm_to_usm.hpp"
3837
#include "copy_for_reshape.hpp"
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#include "copy_numpy_ndarray_into_usm_ndarray.hpp"
39+
#include "device_support_queries.hpp"
4040
#include "eye_ctor.hpp"
4141
#include "full_ctor.hpp"
4242
#include "linear_sequences.hpp"
@@ -102,36 +102,6 @@ void init_dispatch_vectors(void)
102102
return;
103103
}
104104

105-
std::string get_default_device_fp_type(sycl::device d)
106-
{
107-
if (d.has(sycl::aspect::fp64)) {
108-
return "f8";
109-
}
110-
else {
111-
return "f4";
112-
}
113-
}
114-
115-
std::string get_default_device_int_type(sycl::device)
116-
{
117-
return "i8";
118-
}
119-
120-
std::string get_default_device_complex_type(sycl::device d)
121-
{
122-
if (d.has(sycl::aspect::fp64)) {
123-
return "c16";
124-
}
125-
else {
126-
return "c8";
127-
}
128-
}
129-
130-
std::string get_default_device_bool_type(sycl::device)
131-
{
132-
return "b1";
133-
}
134-
135105
} // namespace
136106

137107
PYBIND11_MODULE(_tensor_impl, m)
@@ -209,57 +179,43 @@ PYBIND11_MODULE(_tensor_impl, m)
209179
py::arg("k"), py::arg("dst"), py::arg("sycl_queue"),
210180
py::arg("depends") = py::list());
211181

212-
m.def("default_device_fp_type", [](sycl::queue q) -> std::string {
213-
return get_default_device_fp_type(q.get_device());
214-
});
215-
m.def("default_device_fp_type_device", [](sycl::device dev) -> std::string {
216-
return get_default_device_fp_type(dev);
217-
});
218-
219-
m.def("default_device_int_type", [](sycl::queue q) -> std::string {
220-
return get_default_device_int_type(q.get_device());
221-
});
222-
m.def("default_device_int_type_device",
223-
[](sycl::device dev) -> std::string {
224-
return get_default_device_int_type(dev);
225-
});
226-
227-
m.def("default_device_bool_type", [](sycl::queue q) -> std::string {
228-
return get_default_device_bool_type(q.get_device());
229-
});
230-
m.def("default_device_bool_type_device",
231-
[](sycl::device dev) -> std::string {
232-
return get_default_device_bool_type(dev);
233-
});
234-
235-
m.def("default_device_complex_type", [](sycl::queue q) -> std::string {
236-
return get_default_device_complex_type(q.get_device());
237-
});
238-
m.def("default_device_complex_type_device",
239-
[](sycl::device dev) -> std::string {
240-
return get_default_device_complex_type(dev);
241-
});
242-
m.def(
243-
"_tril",
244-
[](dpctl::tensor::usm_ndarray src, dpctl::tensor::usm_ndarray dst,
245-
py::ssize_t k, sycl::queue exec_q,
246-
const std::vector<sycl::event> depends)
247-
-> std::pair<sycl::event, sycl::event> {
248-
return usm_ndarray_triul(exec_q, src, dst, 'l', k, depends);
249-
},
250-
"Tril helper function.", py::arg("src"), py::arg("dst"),
251-
py::arg("k") = 0, py::arg("sycl_queue"),
252-
py::arg("depends") = py::list());
182+
m.def("default_device_fp_type",
183+
dpctl::tensor::py_internal::default_device_fp_type,
184+
"Gives default floating point type supported by device.",
185+
py::arg("dev"));
186+
187+
m.def("default_device_int_type",
188+
dpctl::tensor::py_internal::default_device_int_type,
189+
"Gives default integer type supported by device.", py::arg("dev"));
190+
191+
m.def("default_device_bool_type",
192+
dpctl::tensor::py_internal::default_device_bool_type,
193+
"Gives default boolean type supported by device.", py::arg("dev"));
194+
195+
m.def("default_device_complex_type",
196+
dpctl::tensor::py_internal::default_device_complex_type,
197+
"Gives default complex floating point type support by device.",
198+
py::arg("dev"));
199+
200+
auto tril_fn = [](dpctl::tensor::usm_ndarray src,
201+
dpctl::tensor::usm_ndarray dst, py::ssize_t k,
202+
sycl::queue exec_q,
203+
const std::vector<sycl::event> depends)
204+
-> std::pair<sycl::event, sycl::event> {
205+
return usm_ndarray_triul(exec_q, src, dst, 'l', k, depends);
206+
};
207+
m.def("_tril", tril_fn, "Tril helper function.", py::arg("src"),
208+
py::arg("dst"), py::arg("k") = 0, py::arg("sycl_queue"),
209+
py::arg("depends") = py::list());
253210

254-
m.def(
255-
"_triu",
256-
[](dpctl::tensor::usm_ndarray src, dpctl::tensor::usm_ndarray dst,
257-
py::ssize_t k, sycl::queue exec_q,
258-
const std::vector<sycl::event> depends)
259-
-> std::pair<sycl::event, sycl::event> {
260-
return usm_ndarray_triul(exec_q, src, dst, 'u', k, depends);
261-
},
262-
"Triu helper function.", py::arg("src"), py::arg("dst"),
263-
py::arg("k") = 0, py::arg("sycl_queue"),
264-
py::arg("depends") = py::list());
211+
auto triu_fn = [](dpctl::tensor::usm_ndarray src,
212+
dpctl::tensor::usm_ndarray dst, py::ssize_t k,
213+
sycl::queue exec_q,
214+
const std::vector<sycl::event> depends)
215+
-> std::pair<sycl::event, sycl::event> {
216+
return usm_ndarray_triul(exec_q, src, dst, 'u', k, depends);
217+
};
218+
m.def("_triu", triu_fn, "Triu helper function.", py::arg("src"),
219+
py::arg("dst"), py::arg("k") = 0, py::arg("sycl_queue"),
220+
py::arg("depends") = py::list());
265221
}

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