Document utilities
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@ -81,6 +81,47 @@ def threaded_parallel_map(
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concurrency: Optional[int] = None,
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unordered: bool = False,
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) -> Iterable[Optional[V]]:
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"""Execute a map operation on an iterable stream.
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Similar to [parallel_map][great_ai.utilities.parallel_map.parallel_map.parallel_map]
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but uses threads instead of processes. Hence, it is not helpful in CPU-bound
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situations.
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A custom parallel map operation supporting both synchronous and `async` map
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functions. Exceptions encountered in the map function are sent to the host thread
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where they are either raised (default) or ignored. Each process processes a single
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chunk at once.
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Examples:
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>>> list(threaded_parallel_map(lambda x: x ** 2, [1, 2, 3]))
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[1, 4, 9]
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Args:
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func: The function that should be applied to each element of `input_values`.
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It can `async`, in that case, a new event loop is started for each chunk.
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input_values: An iterable of items that `func` is applied to.
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chunk_size: Tune the number of items processed in each step. Larger numbers
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result in smaller communication overhead but less parallelism at the start
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and end. If `chunk_size` has a `__len__` property, the `chunk_size` is
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calculated automatically if not given.
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ignore_exceptions: Ignore chunks if `next()` raises an exception on
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`input_values`. And return `None` if `func` raised an exception in a worker
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process.
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concurrency: Number of new threads to start.
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unordered: Do not preserve the order of the elements, yield them as soon as they
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have been processed. This decreases the latency caused by
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difficult-to-process items.
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Yields:
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The next result obtained from applying `func` to each input value. May
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contain `None`-s if `ignore_exceptions=True`. May have different order than
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the input if `unordered=True`.
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Raises:
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WorkerException: If there was an error in the `func` function in a background
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thread and `ignore_exceptions=False`.
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"""
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config = get_config(
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function=func,
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input_values=input_values,
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