wehub-resource-sync
50 lines
1.7 KiB
C++
50 lines
1.7 KiB
C++
/* Copyright 2022 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include <pybind11/stl.h>
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#include <string>
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#include <vector>
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#include "absl/status/statusor.h"
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#include "pybind11/pybind11.h" // from @pybind11
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#include "pybind11/pytypes.h" // from @pybind11
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#include "pybind11/stl.h" // from @pybind11
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#include "pybind11_abseil/absl_casters.h" // from @pybind11_abseil
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#include "pybind11_abseil/status_casters.h" // from @pybind11_abseil
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#include "tensorflow/compiler/tf2xla/tf2xla_opset.h"
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using tensorflow::GetRegisteredXlaOpsForDevice;
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PYBIND11_MODULE(pywrap_xla_ops, m) {
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pybind11::google::ImportStatusModule();
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m.def(
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"get_gpu_kernel_names",
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[]() -> absl::StatusOr<std::vector<std::string>> {
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return GetRegisteredXlaOpsForDevice("XLA_GPU_JIT");
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},
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R"pbdoc(
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Returns list of names of gpu ops that can be compiled.
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)pbdoc");
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m.def(
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"get_cpu_kernel_names",
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[]() -> absl::StatusOr<std::vector<std::string>> {
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return GetRegisteredXlaOpsForDevice("XLA_CPU_JIT");
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},
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R"pbdoc(
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Returns list of names of cpu ops that can be compiled.
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)pbdoc");
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};
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