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242 lines
8.2 KiB
Python
242 lines
8.2 KiB
Python
"""Implements InterpreterPoolExecutor."""
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import contextlib
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import pickle
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import textwrap
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from . import thread as _thread
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import _interpreters
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import _interpqueues
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class ExecutionFailed(_interpreters.InterpreterError):
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"""An unhandled exception happened during execution."""
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def __init__(self, excinfo):
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msg = excinfo.formatted
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if not msg:
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if excinfo.type and excinfo.msg:
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msg = f'{excinfo.type.__name__}: {excinfo.msg}'
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else:
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msg = excinfo.type.__name__ or excinfo.msg
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super().__init__(msg)
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self.excinfo = excinfo
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def __str__(self):
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try:
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formatted = self.excinfo.errdisplay
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except Exception:
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return super().__str__()
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else:
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return textwrap.dedent(f"""
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{super().__str__()}
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Uncaught in the interpreter:
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{formatted}
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""".strip())
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UNBOUND = 2 # error; this should not happen.
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class WorkerContext(_thread.WorkerContext):
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@classmethod
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def prepare(cls, initializer, initargs, shared):
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def resolve_task(fn, args, kwargs):
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if isinstance(fn, str):
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# XXX Circle back to this later.
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raise TypeError('scripts not supported')
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if args or kwargs:
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raise ValueError(f'a script does not take args or kwargs, got {args!r} and {kwargs!r}')
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data = textwrap.dedent(fn)
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kind = 'script'
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# Make sure the script compiles.
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# Ideally we wouldn't throw away the resulting code
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# object. However, there isn't much to be done until
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# code objects are shareable and/or we do a better job
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# of supporting code objects in _interpreters.exec().
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compile(data, '<string>', 'exec')
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else:
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# Functions defined in the __main__ module can't be pickled,
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# so they can't be used here. In the future, we could possibly
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# borrow from multiprocessing to work around this.
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data = pickle.dumps((fn, args, kwargs))
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kind = 'function'
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return (data, kind)
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if initializer is not None:
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try:
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initdata = resolve_task(initializer, initargs, {})
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except ValueError:
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if isinstance(initializer, str) and initargs:
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raise ValueError(f'an initializer script does not take args, got {initargs!r}')
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raise # re-raise
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else:
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initdata = None
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def create_context():
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return cls(initdata, shared)
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return create_context, resolve_task
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@classmethod
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@contextlib.contextmanager
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def _capture_exc(cls, resultsid):
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try:
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yield
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except BaseException as exc:
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# Send the captured exception out on the results queue,
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# but still leave it unhandled for the interpreter to handle.
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err = pickle.dumps(exc)
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_interpqueues.put(resultsid, (None, err), 1, UNBOUND)
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raise # re-raise
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@classmethod
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def _send_script_result(cls, resultsid):
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_interpqueues.put(resultsid, (None, None), 0, UNBOUND)
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@classmethod
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def _call(cls, func, args, kwargs, resultsid):
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with cls._capture_exc(resultsid):
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res = func(*args or (), **kwargs or {})
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# Send the result back.
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try:
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_interpqueues.put(resultsid, (res, None), 0, UNBOUND)
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except _interpreters.NotShareableError:
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res = pickle.dumps(res)
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_interpqueues.put(resultsid, (res, None), 1, UNBOUND)
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@classmethod
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def _call_pickled(cls, pickled, resultsid):
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with cls._capture_exc(resultsid):
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fn, args, kwargs = pickle.loads(pickled)
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cls._call(fn, args, kwargs, resultsid)
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def __init__(self, initdata, shared=None):
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self.initdata = initdata
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self.shared = dict(shared) if shared else None
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self.interpid = None
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self.resultsid = None
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def __del__(self):
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if self.interpid is not None:
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self.finalize()
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def _exec(self, script):
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assert self.interpid is not None
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excinfo = _interpreters.exec(self.interpid, script, restrict=True)
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if excinfo is not None:
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raise ExecutionFailed(excinfo)
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def initialize(self):
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assert self.interpid is None, self.interpid
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self.interpid = _interpreters.create(reqrefs=True)
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try:
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_interpreters.incref(self.interpid)
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maxsize = 0
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fmt = 0
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self.resultsid = _interpqueues.create(maxsize, fmt, UNBOUND)
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self._exec(f'from {__name__} import WorkerContext')
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if self.shared:
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_interpreters.set___main___attrs(
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self.interpid, self.shared, restrict=True)
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if self.initdata:
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self.run(self.initdata)
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except BaseException:
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self.finalize()
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raise # re-raise
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def finalize(self):
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interpid = self.interpid
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resultsid = self.resultsid
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self.resultsid = None
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self.interpid = None
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if resultsid is not None:
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try:
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_interpqueues.destroy(resultsid)
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except _interpqueues.QueueNotFoundError:
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pass
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if interpid is not None:
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try:
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_interpreters.decref(interpid)
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except _interpreters.InterpreterNotFoundError:
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pass
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def run(self, task):
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data, kind = task
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if kind == 'script':
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raise NotImplementedError('script kind disabled')
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script = f"""
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with WorkerContext._capture_exc({self.resultsid}):
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{textwrap.indent(data, ' ')}
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WorkerContext._send_script_result({self.resultsid})"""
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elif kind == 'function':
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script = f'WorkerContext._call_pickled({data!r}, {self.resultsid})'
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else:
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raise NotImplementedError(kind)
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try:
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self._exec(script)
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except ExecutionFailed as exc:
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exc_wrapper = exc
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else:
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exc_wrapper = None
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# Return the result, or raise the exception.
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while True:
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try:
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obj = _interpqueues.get(self.resultsid)
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except _interpqueues.QueueNotFoundError:
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raise # re-raise
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except _interpqueues.QueueError:
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continue
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except ModuleNotFoundError:
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# interpreters.queues doesn't exist, which means
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# QueueEmpty doesn't. Act as though it does.
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continue
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else:
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break
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(res, excdata), pickled, unboundop = obj
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assert unboundop is None, unboundop
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if excdata is not None:
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assert res is None, res
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assert pickled
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assert exc_wrapper is not None
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exc = pickle.loads(excdata)
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raise exc from exc_wrapper
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return pickle.loads(res) if pickled else res
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class BrokenInterpreterPool(_thread.BrokenThreadPool):
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"""
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Raised when a worker thread in an InterpreterPoolExecutor failed initializing.
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"""
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class InterpreterPoolExecutor(_thread.ThreadPoolExecutor):
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BROKEN = BrokenInterpreterPool
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@classmethod
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def prepare_context(cls, initializer, initargs, shared):
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return WorkerContext.prepare(initializer, initargs, shared)
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def __init__(self, max_workers=None, thread_name_prefix='',
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initializer=None, initargs=(), shared=None):
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"""Initializes a new InterpreterPoolExecutor instance.
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Args:
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max_workers: The maximum number of interpreters that can be used to
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execute the given calls.
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thread_name_prefix: An optional name prefix to give our threads.
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initializer: A callable or script used to initialize
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each worker interpreter.
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initargs: A tuple of arguments to pass to the initializer.
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shared: A mapping of shareabled objects to be inserted into
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each worker interpreter.
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"""
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super().__init__(max_workers, thread_name_prefix,
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initializer, initargs, shared=shared)
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