backend.ai-kernel-runner 1.4.2

How to write a new computation kernel

Inherit ai.backend.kernel.BaseRunner and implement the following methods:

• async def init_with_loop(self)

  • Called after the asyncio event loop becomes available.

  • Mostly just pass.

  • If your kernel supports interactive user input, then put set self.user_input_queue as an asyncio.Queue object. It’s your job to utilize the queue object for waiting for the user input. (See handle_input() method in ai/backend/kernel/python/inproc.py for reference) If it’s not set, then any attempts for getting interactive user input will simply return "<user-input is unsupported>".

• async def build_heuristic(self)

  • (Batch mode) Write a heuristic code to find some build script or run a good-enough build command for your language/runtime.

  • (Blocking) You don’t have to worry about overlapped execution since the base runner will take care of it.

• async def execute_heuristic(self)

  • (Batch mode) Write a heuristic code to find the main program.

  • (Blocking) You don’t have to worry about overlapped execution since the base runner will take care of it.

• async def query(self, code_text)

  • (Query mode) Directly run the given code snippet. Depending on the language/runtime, you may need to create a temporary file and execute an external program.

  • (Blocking) You don’t have to worry about overlapped execution since the base runner will take care of it.

• async def complete(self, data)

  • (Query mode) Take a dict data that includes the current line of code where the user is typing and return a list of strings that can auto-complete it.

  • (Non-blocking) You should implement this method to run asynchronously with ongoing code execution.

• async def interrupt(self)

  • (Query mode) Send an interruption signal to the running program. The implementation is up to you. The Python runner currently spawns a thread for in-process query-mode execution and use a ctypes hack to throw KeyboardInterrupt exception into it.

  • (Non-blocking) You should implement this method to run asynchronously with ongoing code execution.

NOTE: Existing codes are good referecnes!

How to use in your Backend.AI computation kernels

Install this package using pip via a RUN instruction in Dockerfile. Then, set the CMD instruction like below:

CMD ["/home/backend.ai/jail", "-policy", "/home/backend.ai/policy.yml", \
     "/usr/local/bin/python", "-m", "ai.backend.kernel", "<language>"]

where <language> should be one of the supported language names defined in lang_map variable in ai/backend/kernel/__main__.py file.