Implementation:Tensorflow Serving Executor

Knowledge Sources	Tensorflow_Serving
Domains	Concurrency, Abstraction
Last Updated	2026-02-13 00:00 GMT

Overview

An abstract interface for scheduling closures for execution, providing a decoupling point between task submission and the threading strategy.

Description

Executor is a minimal abstract base class with a single pure virtual method Schedule() that accepts a std::function<void()> closure. Implementations must be thread-safe. The interface allows the serving system to be agnostic about the underlying threading model; callers submit work via Schedule() and the concrete implementation decides how to execute it (e.g., in a thread pool, inline, or via some other mechanism). This abstraction is used throughout the serving system wherever asynchronous or deferred execution is needed.

Usage

Use Executor as the interface type when accepting an execution strategy as a dependency. Implement it with ThreadPoolExecutor or a custom executor depending on the deployment environment.

Code Reference

Source Location

• Repository: Tensorflow_Serving
• File: tensorflow_serving/util/executor.h
• Lines: 1-39

Signature

class Executor {
 public:
  virtual ~Executor() = default;
  virtual void Schedule(std::function<void()> fn) = 0;
};

Import

#include "tensorflow_serving/util/executor.h"

I/O Contract

Inputs

Name	Type	Required	Description
fn	std::function<void()>	Yes	The closure to schedule for execution

Outputs

Name	Type	Description
(none)	void	The closure is scheduled; execution timing depends on the implementation

Usage Examples

Scheduling Work

void DoAsyncWork(Executor* executor) {
  executor->Schedule([]() {
    // Perform background work
    ProcessBatch();
  });
}

Related Pages

• Principle:Tensorflow_Serving_Executor_Abstraction