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Register CUDAAllocatorConfig to AcceleratorAllocatorConfig (#165131)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/165131 Approved by: https://github.com/Skylion007 ghstack dependencies: #165129
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@ -297,7 +297,7 @@ size_t CUDAAllocatorConfig::parseAllocatorConfig(
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#endif // USE_ROCM
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}
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void CUDAAllocatorConfig::parseArgs(const std::optional<std::string>& env) {
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void CUDAAllocatorConfig::parseArgs(const std::string& env) {
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// If empty, set the default values
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m_max_split_size = std::numeric_limits<size_t>::max();
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m_roundup_power2_divisions.assign(kRoundUpPowerOfTwoIntervals, 0);
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@ -305,16 +305,13 @@ void CUDAAllocatorConfig::parseArgs(const std::optional<std::string>& env) {
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bool used_cudaMallocAsync = false;
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bool used_native_specific_option = false;
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if (!env.has_value()) {
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return;
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}
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{
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std::lock_guard<std::mutex> lock(m_last_allocator_settings_mutex);
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m_last_allocator_settings = env.value();
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m_last_allocator_settings = env;
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}
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std::vector<std::string> config;
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lexArgs(env.value(), config);
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lexArgs(env, config);
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for (size_t i = 0; i < config.size(); i++) {
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std::string_view config_item_view(config[i]);
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@ -487,9 +484,6 @@ size_t CUDAAllocatorConfig::parsePinnedUseBackgroundThreads(
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return i;
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}
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// General caching allocator utilities
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void setAllocatorSettings(const std::string& env) {
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CUDACachingAllocator::CUDAAllocatorConfig::instance().parseArgs(env.c_str());
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}
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REGISTER_ALLOCATOR_CONFIG_PARSE_HOOK(CUDAAllocatorConfig)
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} // namespace c10::cuda::CUDACachingAllocator
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@ -1,16 +1,10 @@
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#pragma once
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#include <c10/core/AllocatorConfig.h>
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#include <c10/cuda/CUDAMacros.h>
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#include <c10/util/Exception.h>
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#include <c10/util/env.h>
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#include <atomic>
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#include <cstddef>
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#include <cstdlib>
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#include <mutex>
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#include <string>
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#include <vector>
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namespace c10::cuda::CUDACachingAllocator {
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enum class Expandable_Segments_Handle_Type : int {
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@ -111,13 +105,40 @@ class C10_CUDA_API CUDAAllocatorConfig {
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env = c10::utils::get_env("PYTORCH_HIP_ALLOC_CONF");
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}
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#endif
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inst->parseArgs(env);
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// Note: keep the parsing order and logic stable to avoid potential
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// performance regressions in internal tests.
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if (!env.has_value()) {
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env = c10::utils::get_env("PYTORCH_ALLOC_CONF");
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}
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if (env.has_value()) {
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inst->parseArgs(env.value());
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}
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return inst;
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})();
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return *s_instance;
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}
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void parseArgs(const std::optional<std::string>& env);
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// Use `Construct On First Use Idiom` to avoid `Static Initialization Order`
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// issue.
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static const std::unordered_set<std::string>& getKeys() {
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static std::unordered_set<std::string> keys{
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"backend",
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// keep BC for Rocm: `cuda` -> `cud` `a`, to avoid hipify issues
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// NOLINTBEGIN(bugprone-suspicious-missing-comma,-warnings-as-errors)
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"release_lock_on_cud"
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"amalloc",
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"pinned_use_cud"
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"a_host_register",
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// NOLINTEND(bugprone-suspicious-missing-comma,-warnings-as-errors)
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"release_lock_on_hipmalloc",
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"pinned_use_hip_host_register",
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"graph_capture_record_stream_reuse",
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"pinned_reserve_segment_size_mb",
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"pinned_num_register_threads"};
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return keys;
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}
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void parseArgs(const std::string& env);
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private:
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CUDAAllocatorConfig();
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@ -174,7 +195,7 @@ class C10_CUDA_API CUDAAllocatorConfig {
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std::mutex m_last_allocator_settings_mutex;
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};
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// General caching allocator utilities
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C10_CUDA_API void setAllocatorSettings(const std::string& env);
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// Keep this for backwards compatibility
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using c10::CachingAllocator::setAllocatorSettings;
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} // namespace c10::cuda::CUDACachingAllocator
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@ -64,10 +64,6 @@ namespace cuda::CUDACachingAllocator {
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using namespace c10::CachingAllocator;
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using namespace c10::CachingDeviceAllocator;
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// Included here as this is externally used in CUDAAllocatorConfig
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const size_t kLargeBuffer =
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20971520; // "large" allocations may be packed in 20 MiB blocks
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namespace Native {
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//
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@ -1,5 +1,6 @@
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#pragma once
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#include <c10/core/AllocatorConfig.h>
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#include <c10/core/CachingDeviceAllocator.h>
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#include <c10/cuda/CUDAGraphsC10Utils.h>
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#include <c10/cuda/CUDAMacros.h>
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@ -49,10 +50,9 @@ namespace c10::cuda::CUDACachingAllocator {
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// Preserved only for BC reasons
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// NOLINTNEXTLINE(misc-unused-using-decls)
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using c10::CachingAllocator::kLargeBuffer;
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using c10::CachingDeviceAllocator::DeviceStats;
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extern const size_t kLargeBuffer;
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typedef std::shared_ptr<GatheredContext> (*CreateContextFn)();
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// Struct containing info of an allocation block (i.e. a fractional part of a
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