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Headers under torch/csrc/distributed may be referened with relative path, e.g., "<c10d/...>". However, relative path cannot be gracefully handled by Meta internal build when the NCCL PG is hipified to support AMD/RCCL because the "hipified" header files are generated in other directories. Moreover, using absolute path for header inclusion is the state-of-the-art in most components in Pytorch. Thus, this patch refactors all header paths in torch/csrc/distributed to be absolute. See D39835774 for more details about Meta internal complication. **How to test**: commit 9e5d199 removes -I./torch/csrc/distributed in compile options. Thus use it to verify we don't miss any relative path use of torch/csrc/distributed headers. Pull Request resolved: https://github.com/pytorch/pytorch/pull/85780 Approved by: https://github.com/kumpera, https://github.com/huydhn
111 lines
4.0 KiB
C++
111 lines
4.0 KiB
C++
#include <c10/util/Logging.h>
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#include <torch/csrc/distributed/c10d/reducer.hpp>
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#include <mutex>
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namespace c10d {
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class TORCH_API Logger {
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public:
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explicit Logger(std::shared_ptr<c10d::Reducer> reducer);
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// Set logging data that can be got during DistributedDataParallel
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// construction time.
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void set_construction_data_and_log(
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const std::string& module_name,
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const std::vector<int>& device_ids,
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int output_device,
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bool broadcast_buffers,
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bool has_sync_bn,
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bool static_graph
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);
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void set_static_graph();
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// An interface for users to get DDPLoggingData and log them
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// in the applications. Explanation of logging fields are in
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// "struct DDPLoggingData" of "torch/c10/util/Logging.h".
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at::DDPLoggingData get_ddp_logging_data();
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// Stream insertion operator for logging data to stream under
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// TORCH_DISTRIBUTED_DEBUG.
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friend std::ostream& operator<<(std::ostream& output, const Logger& logger);
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~Logger() noexcept(false) {
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// Log if DDP graph is static in Logger dtor instead of Reducer dtor since
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// Logger is deleted before Reducer.
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log_if_graph_static(reducer_->ddp_graph_static());
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}
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// Set environment variables.
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void set_env_variables();
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// Set parameters stats.
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void set_parameter_stats();
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// Get size of each bucket (Bytes).
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std::vector<int64_t> get_bucket_sizes();
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// Get variable indices for each bucket.
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std::vector<std::vector<size_t>> get_per_bucket_variable_indices();
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// Set comm. hook, if used
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void set_comm_hook(const std::string& hook);
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// Set running with uneven input detection (model.join() context manager)
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void set_uneven_input_join();
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// Reset performance stats at current iteration
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void reset_performance_stats();
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// Calculate avg stats using cpu timer and gpu timer
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// that has been recorded in reducer.
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void calculate_avg_time(
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int64_t& avg_time,
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int64_t& time_duration,
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Timer& timer,
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Timer::Event start_event,
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Timer::Event end_event);
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// Set the absolute time of the event that has been recorded in reducer.
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void set_event_time(
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int64_t& event_time,
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Timer& timer,
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Timer::Event event
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);
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// Set stats that can be collected only during
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// training loop. It is called at the beginning of forward call
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// to record the run time stats of sampled iterations that previouly ran.
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// GPU performance stats are collected only for single process
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// single device program and single device module right now.
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// TODO to support single process multiple devices and multi device modules,
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// events need to be created and recorded on multiple devices.
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void set_runtime_stats_and_log();
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// Called when DDP/reducer is failing with an error. The
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// logging data structure will have two fields filled: "has_error" indicating
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// that this iteration encountered an error and other fields are not valid,
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// and "error", a string which contains the error message that DDP failed
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// with.
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template <typename... Args>
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void set_error_and_log(const std::string& ddp_error, const Args&... args) {
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ddp_logging_data_->ints_map["has_error"] = 1;
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auto err = c10::str(ddp_error, args...);
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ddp_logging_data_->strs_map["error"] = err;
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// Report the iteration we are erroring at so user knows how many examples
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// successfully processed before this error was hit.
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ddp_logging_data_->ints_map["iteration"] = reducer_->num_iterations_;
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at::LogPyTorchDDPUsage(*ddp_logging_data_);
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}
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// When running without static graph, called when reducer is destroyed to log
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// if graph was actually static and is a candidate for static graph
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// optimization.
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void log_if_graph_static(bool is_static);
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private:
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// ddp_logging_data_ is used to hold all the ddp related logging
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// data fields.
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std::unique_ptr<at::DDPLoggingData> ddp_logging_data_;
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std::shared_ptr<c10d::Reducer> reducer_;
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// track the number of iterations when runtime stats are collected so far.
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long num_iterations_stats_recorded_ = 0;
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};
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} // namespace c10d
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