Move files

src/great_ai/utilities/parallel_map/get_config.py

@@ -1,56 +0,0 @@
-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__")
-
-    if concurrency is None:
-        concurrency = len(os.sched_getaffinity(0))
-    assert concurrency >= 1, "At least one mapper process has to be created"
-
-    if chunk_size is None:
-        if is_input_sequence:
-            chunk_size = max(1, ceil(len(input_values) / 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 is_input_sequence:
-        chunk_count = ceil(len(input_values) / chunk_size)
-        if chunk_count < concurrency:
-            logger.warning(
-                f"Limiting concurrency to {chunk_count} because there are only {chunk_count} chunks"
-            )
-            concurrency = chunk_count
-
-    if concurrency == 1:
-        logger.warning("Running in series, there is no reason for parallelism")
-
-    input_length = len(input_values) if is_input_sequence else None
-
-    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