great-ai/great_ai/utilities/parallel_map/get_config.py

52 lines
1.7 KiB
Python

import os
from math import ceil
from typing import Callable, Iterable, Optional, Sequence, Union
from ..logger import get_logger
from .parallel_map_configuration import ParallelMapConfiguration
logger = get_logger("parallel_map")
def get_config(
*,
function: Callable,
input_values: Union[Sequence, Iterable],
chunk_size: Optional[int],
concurrency: Optional[int],
) -> ParallelMapConfiguration:
is_input_sequence = hasattr(input_values, "__len__")
input_length = len(input_values) if is_input_sequence else None # type: ignore
if concurrency is None:
concurrency = os.cpu_count() or 1
assert concurrency >= 1, "At least one mapper process has to be created"
if chunk_size is None:
if input_length is not None:
chunk_size = max(1, ceil(input_length / concurrency / 10))
else:
raise ValueError(
"The argument for `values` does not implement `__len__`, therefore, you must provide a `chunk_size`"
)
assert chunk_size >= 1, "Chunks have to contain at least one element"
chunk_count: Optional[int] = None
if input_length is not None:
chunk_count = ceil(input_length / chunk_size)
if chunk_count < concurrency:
logger.warning(
f"Limiting concurrency to {chunk_count} because there are only {chunk_count} chunks"
)
concurrency = chunk_count
config = ParallelMapConfiguration(
concurrency=concurrency,
chunk_count=chunk_count,
chunk_size=chunk_size,
input_length=input_length,
function_name=function.__name__ if hasattr(function, "__name__") else "unknown",
)
return config