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// ----------------------------------------------------------------------------
// - Open3D: www.open3d.org -
// ----------------------------------------------------------------------------
// The MIT License (MIT)
//
// Copyright (c) 2018-2021 www.open3d.org
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
// IN THE SOFTWARE.
// ----------------------------------------------------------------------------
#include "benchmarks/benchmark_utilities/Rand.h"
#include <random>
#include <type_traits>
#include <vector>
#include "open3d/core/Dispatch.h"
#include "open3d/core/Indexer.h"
#include "open3d/core/ParallelFor.h"
#include "open3d/utility/Parallel.h"
namespace open3d {
namespace benchmarks {
core::Tensor Rand(const core::SizeVector& shape,
size_t seed,
const std::pair<core::Scalar, core::Scalar>& range,
core::Dtype dtype,
const core::Device& device) {
// Initialize on CPU, then copy to device
core::Tensor random =
core::Tensor::Empty(shape, dtype, core::Device("CPU:0"));
core::TensorIterator random_it(random);
DISPATCH_DTYPE_TO_TEMPLATE_WITH_BOOL(dtype, [&]() {
scalar_t low = range.first.To<scalar_t>();
scalar_t high = range.second.To<scalar_t>();
using uniform_distribution = std::conditional_t<
std::is_same<scalar_t, bool>::value,
std::uniform_int_distribution<uint16_t>,
std::conditional_t<
std::is_same<scalar_t, uint8_t>::value,
std::uniform_int_distribution<uint16_t>,
std::conditional_t<
std::is_same<scalar_t, int8_t>::value,
std::uniform_int_distribution<int16_t>,
std::conditional_t<
std::is_integral<scalar_t>::value,
std::uniform_int_distribution<scalar_t>,
std::conditional_t<
std::is_floating_point<
scalar_t>::value,
std::uniform_real_distribution<
scalar_t>,
void>>>>>;
int num_threads = utility::EstimateMaxThreads();
std::vector<std::default_random_engine> rng;
for (int64_t i = 0; i < num_threads; ++i) {
rng.emplace_back(seed + i);
}
uniform_distribution dist(low, high);
core::ParallelFor(core::Device("CPU:0"), num_threads, [&](int64_t i) {
int64_t start = random.NumElements() * i / num_threads;
int64_t end = std::min<int64_t>(
random.NumElements() * (i + 1) / num_threads,
random.NumElements());
for (int64_t idx = start; idx < end; ++idx) {
*static_cast<scalar_t*>(random_it.GetPtr(idx)) = dist(rng[i]);
}
});
});
return random.To(device);
}
} // namespace benchmarks
} // namespace open3d
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