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engine.h
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engine.h
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#pragma once
// Engine implements backpropagation from output variables and their gradients
// to "root" variables (variables created by the user with requires_grad=True).
#include <ATen/Tensor.h>
#include <ATen/ThreadLocalState.h>
#include <ATen/core/ivalue.h>
#include <torch/csrc/Export.h>
#include <torch/csrc/autograd/anomaly_mode.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/functions/basic_ops.h>
#include <torch/csrc/autograd/graph_task.h>
#include <torch/csrc/autograd/input_buffer.h>
#include <torch/csrc/autograd/saved_variable_hooks.h>
#include <torch/csrc/autograd/utils/warnings.h>
#include <c10/util/CallOnce.h>
#include <exception>
#include <functional>
#include <memory>
#include <queue>
#include <utility>
#include <vector>
namespace torch::autograd {
struct ReadyQueue;
}
namespace torch::autograd {
// Maximum reentrant backward depth before switching to a new thread
// This limit is based on the TSAN's deadlock detector, where it will
// fail if a program hold more than 65 locks in one thread at once.
// As we hold mutex in every of our custom C++ autograd Node, we would
// like to avoid TSAN complains on this when doing reentrant backwards
// For reference, see https://github.com/google/sanitizers/issues/950
static constexpr int MAX_DEPTH = 60;
void set_device(int device);
TORCH_API void validate_outputs(
const edge_list& edges,
variable_list& grads,
const std::function<std::string(const std::string&)>& format_error);
struct NodeTask {
std::weak_ptr<GraphTask> base_;
std::shared_ptr<Node> fn_;
// This buffer serves as an implicit "addition" node for all of the
// gradients flowing here. Once all the dependencies are finished, we
// use the contents of this buffer to run the function.
InputBuffer inputs_;
// When worker receives a task with isShutdownTask = true, it will immediately
// exit. The engine sends a shutdown task to every queue upon its destruction.
bool isShutdownTask_;
int getReentrantDepth() const;
NodeTask(
std::weak_ptr<GraphTask> base,
std::shared_ptr<Node> fn,
InputBuffer inputs,
bool isShutdownTask = false)
: base_(std::move(base)),
fn_(std::move(fn)),
inputs_(std::move(inputs)),
isShutdownTask_(isShutdownTask) {}
};
// Guard that sets and restores checkpoint_valid
class CheckpointValidGuard {
public:
explicit CheckpointValidGuard(
const std::shared_ptr<const GraphTask>& graph_task);
~CheckpointValidGuard();
private:
bool prev_checkpoint_valid_state;
};
struct ReadyQueue {
private:
// Returns true when t2 should be (weakly) BEFORE t1 in the queue.
// Shutdown tasks are first and then empty NodeTask are next.
struct CompareNodeTaskTime {
bool operator()(NodeTask const& t1, NodeTask const& t2) {
// NOLINTNEXTLINE(bugprone-branch-clone)
if (t2.isShutdownTask_) {
return true;
} else if (!t1.fn_ || t1.isShutdownTask_) {
return false;
} else if (!t2.fn_) {
return true;
} else if (t1.getReentrantDepth() == t2.getReentrantDepth()) {
return t1.fn_->sequence_nr() < t2.fn_->sequence_nr();
} else {
return t1.getReentrantDepth() < t2.getReentrantDepth();
}
}
};
// To notify threads waiting on the ReadyQueue of available tasks on the heap_
std::condition_variable not_empty_;
// To protect read and writes to heap_
mutable std::mutex mutex_;
std::priority_queue<NodeTask, std::vector<NodeTask>, CompareNodeTaskTime>
heap_;
public:
// incrementOutstandingTasks indicates whether or not we should increment
// 'outstanding_tasks_' for the associated GraphTask. This should mostly
// always be true and is only set false in certain cases (see docs for
// DistEngine.execute_graph_task_until_ready_queue_empty)
void push(NodeTask item, bool incrementOutstandingTasks = true);
void pushShutdownTask();
NodeTask pop();
bool empty() const;
size_t size() const;
};
// A single instance of this struct should be created through the whole process
// lifetime. The worker thread creation logic and Engine's destructor rely on
// this.
struct TORCH_API Engine {
/// Returns a reference to a static `Engine` instance.
static Engine& get_default_engine();
static Engine& get_base_engine();
// compiled_autograd needs to live in a different .so file so that it
// can have python symbols, so we add a layer of indirection
// see [Note: Compiled Autograd]
typedef variable_list (*compiled_autograd_fn)(
const std::shared_ptr<Node>& graph_root,
GraphTask& graph_task,
bool accumulate_grad,
const edge_list& outputs);
static void set_compiled_autograd(compiled_autograd_fn fn);
Engine(const Engine&) = delete;
Engine(Engine&&) = delete;
virtual ~Engine();
// Given a list of (Node, input number) pairs computes the value of the graph
// by following next_edge references.
virtual variable_list execute(
const edge_list& roots,
const variable_list& inputs,
bool keep_graph,
bool create_graph,
bool accumulate_grad,
const edge_list& outputs = {});
// Given a pre-populated GraphTask and GraphRoot, computes the backward pass
// for the graph.
//
// NB: This API should only be used by internal autograd specific
// machinery and shouldn't be exposed to users in anyway.
virtual c10::intrusive_ptr<at::ivalue::Future> execute_with_graph_task(
const std::shared_ptr<GraphTask>& graph_task,
std::shared_ptr<Node> graph_root,
InputBuffer&& input_buffer);
virtual std::unique_ptr<AnomalyMetadata> make_anomaly_metadata() {
return std::make_unique<AnomalyMetadata>();
}
virtual std::unique_ptr<SavedVariableHooks> get_default_saved_variable_hooks() {
return nullptr;
}
// We pass cpu_ready_queue to evaluate_function, so that it knows
// the correct ready queue to push to after a NodeTask is ready
void evaluate_function(
std::shared_ptr<GraphTask>& graph_task,
Node* func,
InputBuffer& inputs,
const std::shared_ptr<ReadyQueue>& cpu_ready_queue);
void initialize_device_threads_pool();
virtual void thread_on_exception(
const std::shared_ptr<GraphTask>& graph_task,
const std::shared_ptr<Node>& fn,
std::exception& e);
void queue_callback(std::function<void()> callback);
bool is_checkpoint_valid();
// Should be called after fork to notify that worker threads are gone
void release_workers();
// Must be called by subclass before destructing to avoid a data-race-on-vptr.
void stop();
// Initializes a device thread for the autograd engine.
virtual void thread_init(
int device,
const std::shared_ptr<ReadyQueue>& ready_queue,
bool should_increment = true);
protected:
Engine();
void compute_dependencies(Node* root, GraphTask& task, uint64_t min_topo_nr);
// initialize the thread local ready queue with the ready queue that is
// created elsewhere (i.e. thread_init, Engine::execute, etc), or create a new
// ready queue if ready_queue is not provided.
void init_local_ready_queue(
std::shared_ptr<ReadyQueue> ready_queue = nullptr);
std::shared_ptr<ReadyQueue> ready_queue(
std::shared_ptr<ReadyQueue> cpu_ready_queue,
at::Device device);
std::shared_ptr<ReadyQueue> ready_queue_by_index(
std::shared_ptr<ReadyQueue> cpu_ready_queue,
int device_index);
// start device threads (CUDA, XLA, etc.) in Engine,
// note that it does NOT start CPU thread.
void start_device_threads();
void increment_non_reentrant_thread_count();
void decrement_non_reentrant_thread_count();
virtual void thread_main(const std::shared_ptr<GraphTask>& task);
void reentrant_thread_init();
void add_thread_pool_task(const std::weak_ptr<GraphTask>& graph_task);
// Ensures device_ready_queues_ are initialized only once
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
c10::once_flag start_device_threads_flag_;
// Safe to read device_ready_queues_ without synchronization after
// initialization
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
std::vector<std::shared_ptr<ReadyQueue>> device_ready_queues_;
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
std::vector<std::function<void()>> final_callbacks_;
// To protect reads and writes to final_callbacks_
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
std::mutex post_callbacks_lock_;
// How many nested reentrant calls are allowed until a new thread is used
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
int max_recursion_depth_;
struct ThreadPoolShared {
// Data structures used by the threads for executing reentrant backwards
// tasks. See Note [Reentrant backwards]
// Number of available threads for processing new GraphTasks.
unsigned int num_workers_{0};
// The threads will wait on work_ to be notified of GraphTasks
std::condition_variable work_;
// To protect reads and writes to graphtask_queue_ and num_workers_
// and for synchronizing creating new threads when needed
std::mutex mutex_;
// Workers will process the GraphTasks added to this queue. A GraphTask is
// allocated inside Engine::execute and lives for the duration of execute
std::queue<std::weak_ptr<GraphTask>> graphtasks_queue_;
ThreadPoolShared() = default;
};
// Temporary workaround until shutting down threads is done
// We need shared ownership of all these objects because the threads are
// leaked when Engine shuts down, so there may be threads waiting on work_ for
// the graphtasks_queue_ to be nonempty.
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
std::shared_ptr<ThreadPoolShared> thread_pool_shared_;
private:
// Number of non-reentrant threads
std::atomic<uint32_t> non_reentrant_device_thread_count_;
// Destructor will wait for non-reentrant threads to finish
std::condition_variable non_reentrant_device_thread_condvar_;
std::mutex non_reentrant_device_thread_mutex_;
// stop() must be called before the destruction path goes down to the base
// class, in order to avoid a data-race-on-vptr. Use this boolean to guard
// whether stop() has already been called, so we can call this in every
// destructor of the class hierarchy.
bool stopped_{false};
};
// allow python_engine to override the default engine when it loads
using EngineStub = Engine& (*)();
TORCH_API void set_default_engine_stub(EngineStub stub);
} // namespace torch::autograd