mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +01:00
5306713a36
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/34468 This PR prepares `at::Generator` for pybind11's `type_caster<at::Generator>` which is required to implement custom RNG in python. The following changes are done: 1. `at::Generator` was moved to `c10::GeneratorImpl` (similar to `c10::TensorImpl`) 2. `at::Generator` was recreated as a holder of `std::shared_ptr<c10::GeneratorImpl>` (similar to `at::Tensor` that holds `c10::intrusive_ptr<c10::TensorImpl>`) 3. Most of `at::Generator*` usages were replaced with `at::Generator` TBD: replacing `Generator generator = nullptr` with `{}` requires JIT changes(adding Generator to IValue?) Differential Revision: D20549420 Pulled By: pbelevich fbshipit-source-id: 4c92a40eab8f033b359bb6c93f4cd84b07ee8d4e
85 lines
2.4 KiB
C++
85 lines
2.4 KiB
C++
#include <c10/core/GeneratorImpl.h>
|
|
#include <chrono>
|
|
#include <random>
|
|
|
|
#ifndef _WIN32
|
|
#include <fcntl.h>
|
|
#include <unistd.h>
|
|
#endif
|
|
|
|
namespace c10 {
|
|
|
|
/**
|
|
* GeneratorImpl class implementation
|
|
*/
|
|
GeneratorImpl::GeneratorImpl(Device device_in, DispatchKeySet key_set)
|
|
: device_{device_in}, key_set_(key_set) {}
|
|
|
|
/**
|
|
* Clone this generator. Note that clone() is the only
|
|
* method for copying for Generators in ATen.
|
|
*/
|
|
std::shared_ptr<GeneratorImpl> GeneratorImpl::clone() const {
|
|
return std::shared_ptr<GeneratorImpl>(static_cast<GeneratorImpl*>(this->clone_impl()));
|
|
}
|
|
|
|
/**
|
|
* Gets the device of a generator.
|
|
*/
|
|
Device GeneratorImpl::device() const {
|
|
return device_;
|
|
}
|
|
|
|
namespace detail {
|
|
|
|
/**
|
|
* Gets a random number for /dev/urandom
|
|
* Note this is a legacy method (from THRandom.cpp)
|
|
* FIXME: use std::random_device with entropy information
|
|
*/
|
|
#ifndef _WIN32
|
|
static uint64_t readURandomLong()
|
|
{
|
|
int randDev = open("/dev/urandom", O_RDONLY);
|
|
uint64_t randValue;
|
|
TORCH_CHECK(randDev >= 0, "Unable to open /dev/urandom");
|
|
ssize_t readBytes = read(randDev, &randValue, sizeof(randValue));
|
|
TORCH_CHECK(readBytes >= (ssize_t) sizeof(randValue), "Unable to read from /dev/urandom");
|
|
close(randDev);
|
|
return randValue;
|
|
}
|
|
#endif // _WIN32
|
|
|
|
/**
|
|
* Gets a non deterministic random number number from either the
|
|
* /dev/urandom or the current time. For CUDA, gets random from
|
|
* std::random_device and adds a transformation on it.
|
|
*
|
|
* FIXME: The behavior in this function is from legacy code (THRandom_seed/THCRandom_seed)
|
|
* and is probably not the right thing to do, even though our tests pass.
|
|
* Figure out if tests get perturbed
|
|
* - when the same algorithm is used for all backends. Note that the current behavior is
|
|
* different for CPU, CUDA and Windows CPU.
|
|
* - when using C++11 std objects, such as std::random_device
|
|
* - when constructing a 64 bit seed properly, rather than static casting
|
|
* a 32 bit number to 64 bit.
|
|
*/
|
|
uint64_t getNonDeterministicRandom(bool is_cuda) {
|
|
uint64_t s;
|
|
if (!is_cuda) {
|
|
#ifdef _WIN32
|
|
s = (uint64_t)std::chrono::high_resolution_clock::now().time_since_epoch().count();
|
|
#else
|
|
s = readURandomLong();
|
|
#endif
|
|
} else {
|
|
std::random_device rd;
|
|
// limit to 53 bits to ensure unique representation in double
|
|
s = ((((uint64_t)rd()) << 32) + rd()) & 0x1FFFFFFFFFFFFF;
|
|
}
|
|
return s;
|
|
}
|
|
|
|
} // namespace detail
|
|
} // namespace c10
|