#pragma once #include <ATen/core/function.h> #include <torch/csrc/jit/ir/ir.h> #include <torch/csrc/jit/runtime/graph_executor.h> #include <torch/csrc/utils/memory.h> namespace torch { namespace jit { struct TORCH_API GraphFunction : public Function { GraphFunction( c10::QualifiedName name, std::shared_ptr<Graph> graph, std::function<void(GraphFunction&)> function_creator) : name_(std::move(name)), graph_(std::move(graph)), function_creator_(std::move(function_creator)) {} bool isGraphFunction() const override { return true; } void run(Stack& stack) override; void run(Stack&& stack) override; c10::intrusive_ptr<c10::ivalue::Future> runAsync( Stack& stack, TaskLauncher taskLauncher = at::launch) override; IValue operator()(std::vector<IValue> stack, const Kwargs& kwargs = Kwargs()) override; std::shared_ptr<Graph> graph() const override { return graph_; } std::shared_ptr<Graph> optimized_graph() const override { std::lock_guard<std::recursive_mutex> lock(compile_mutex); if (optimized_graph_) { return *optimized_graph_; } optimized_graph_ = graph_->copy(); if (getGraphExecutorOptimize()) { preoptimizeGraph(*optimized_graph_); } return *optimized_graph_; } void clear_execution_info() override { std::lock_guard<std::recursive_mutex> lock(compile_mutex); if (optimized_graph_) { optimized_graph_.reset(); } executor_.reset(); } const c10::QualifiedName& qualname() const override { return name_; } const std::string& name() const override { return name_.name(); } // if this isn't yet defined, run its method_creator function void ensure_defined() override; size_t num_inputs() const override { return graph()->inputs().size(); } Function& setSchema(FunctionSchema schema) override { schema_ = make_unique<FunctionSchema>(std::move(schema)); return *this; } const FunctionSchema& getSchema() const override; std::string pretty_print_schema() const override { AT_ASSERT(schema_); std::stringstream ss; ss << *schema_; return ss.str(); } GraphExecutorState getDebugState() { return get_executor().getDebugState(); } bool is_optimized() const { TORCH_WARN( "GraphFunction::is_optimized() is deprecated and always returns true. " "Please use getGraphExecutorOptimize()"); return true; } void check_single_output() override { TORCH_CHECK( graph()->outputs().size() == 1, "Method (but not graphs in general) require a single output. Use None/Tuple for 0 or 2+ outputs"); } GraphExecutor& get_executor() override { ensure_defined(); std::lock_guard<std::recursive_mutex> lock(compile_mutex); if (executor_) { return executor_; } check_single_output(); executor_ = GraphExecutor(optimized_graph(), name_.name()); return executor_; } private: c10::QualifiedName name_; // The original, non-optimized graph std::shared_ptr<Graph> graph_; // for debugging and for inlining // Optimized graph, computed lazily. Used for inlining. // Note: this graph is not specialized, only generic optimizations are applied // here. mutable c10::optional<std::shared_ptr<Graph>> optimized_graph_; // GraphFunctions are invokable from multiple threads, so this lock needs to // be held when we're initializing graph executor for the first time or // computing the optimized graph. We're using reentrant mutex so that we don't // need to worry about causing a deadlock by calling one method from another // (e.g. optimized_graph() from get_executor()). mutable std::recursive_mutex compile_mutex; GraphExecutor executor_; // for execution // an optional function that actually creates the method when // ensure_defined() is called. This is used by the compiler so // that it can construct methods out of order std::function<void(GraphFunction&)> function_creator_; // if absent, then we generate a default schema based on the graph // mutable because getSchema caches the default schema if one is requested // before a call to setSchema mutable std::unique_ptr<FunctionSchema> schema_; }; } // namespace jit } // namespace torch