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48 lines
1.5 KiB
C++
48 lines
1.5 KiB
C++
/* Copyright 2023 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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#if GOOGLE_CUDA
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#define EIGEN_USE_GPU
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#include "tensorflow/core/util/gpu_kernel_helper.h"
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typedef Eigen::GpuDevice GPUDevice;
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namespace tensorflow {
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namespace {
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__global__ void sleep_kernel(int seconds) {
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#if __CUDA_ARCH__ >= 700 // __nanosleep requires compute capability 7.0
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int64_t nanoseconds = int64_t{seconds} * 1'000'000'000;
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// Passing too high a number to __nanosleep makes it sleep for much less time
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// than the passed-in number. So only pass 1,000,000 and keep calling
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// __nanosleep in a loop.
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for (int64_t i = 0; i < nanoseconds; i += 1'000'000) {
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__nanosleep(1'000'000);
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}
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#endif
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}
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} // namespace
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void GpuSleep(OpKernelContext* ctx, int seconds) {
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auto* cu_stream = ctx->eigen_device<GPUDevice>().stream();
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CHECK(cu_stream); // Crash OK
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TF_CHECK_OK(GpuLaunchKernel(sleep_kernel, 1, 1, 0, cu_stream, seconds));
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}
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} // namespace tensorflow
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#endif // GOOGLE_CUDA
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