140 lines
3.4 KiB
Python
140 lines
3.4 KiB
Python
import multiprocessing as mp
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import queue
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from typing import (
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Callable,
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Iterable,
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List,
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Optional,
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Sequence,
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Tuple,
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TypeVar,
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overload,
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)
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from tqdm.auto import tqdm
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from ..chunk import chunk
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from .get_config import get_config
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from .mapper_function import mapper_function
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T = TypeVar("T")
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V = TypeVar("V")
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@overload
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def parallel_map(
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function: Callable[[T], V],
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input_values: Sequence[T],
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*,
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chunk_length: Optional[int],
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concurrency: Optional[int],
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disable_progress_bar: bool,
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) -> List[V]:
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...
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@overload
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def parallel_map(
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function: Callable[[T], V],
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input_values: Iterable[T],
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*,
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chunk_length: int,
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concurrency: Optional[int],
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disable_progress_bar: bool,
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) -> List[V]:
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...
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def parallel_map(
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function,
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input_values,
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*,
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chunk_length=None,
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concurrency=None,
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disable_progress_bar=False,
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):
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config = get_config(
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function=function,
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input_values=input_values,
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chunk_length=chunk_length,
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concurrency=concurrency,
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)
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if config.concurrency == 1:
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return [
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function(v)
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for v in tqdm(
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input_values,
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desc="Parallel map",
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disable=disable_progress_bar,
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total=config.input_length,
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)
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]
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start_methods = mp.get_all_start_methods()
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ctx = mp.get_context("fork") if "fork" in start_methods else mp.get_context("spawn")
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ctx.freeze_support()
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input_queue = ctx.Queue(0 if config.chunk_count is None else config.chunk_count)
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output_queue = ctx.Queue(0 if config.chunk_count is None else config.chunk_count)
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should_stop = ctx.Event()
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processes = [
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ctx.Process(
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name=f"parallel_map_{i}",
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target=mapper_function,
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kwargs=dict(
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input_queue=input_queue,
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output_queue=output_queue,
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should_stop=should_stop,
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serialized_map_function=config.serialized_map_function,
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),
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)
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for i in range(config.concurrency)
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]
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for p in processes:
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p.start()
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progress = tqdm(
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desc="Parallel map",
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disable=disable_progress_bar,
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total=config.input_length,
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)
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chunks = iter(chunk(enumerate(input_values), chunk_length=config.chunk_length))
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indexed_results: List[Tuple[int, V]] = []
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read_input_length = 0
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is_iteration_over = False
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try:
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while not is_iteration_over or len(indexed_results) < read_input_length:
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if not is_iteration_over:
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try:
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next_chunk = next(chunks)
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input_queue.put(next_chunk)
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read_input_length += len(next_chunk)
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except StopIteration:
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is_iteration_over = True
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try:
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result_chunk = output_queue.get_nowait()
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indexed_results.extend(result_chunk)
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progress.update(len(result_chunk))
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except queue.Empty:
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pass
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should_stop.set()
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except KeyboardInterrupt:
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for p in processes:
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p.terminate()
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finally:
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for p in processes:
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p.join()
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p.close()
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input_queue.close()
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output_queue.close()
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progress.close()
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results = [v for _, v in sorted(indexed_results)]
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return results
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