





from __future__ import annotations






def 					SCREAMING_SNAKE_CASE__				(							UpperCamelCase__:				list[float]       , UpperCamelCase__:				list[float]     ):
		SCREAMING_SNAKE_CASE__								=   sorted(numsa + numsa     )
		SCREAMING_SNAKE_CASE__						,    SCREAMING_SNAKE_CASE__								=   divmod(len(UpperCamelCase__     )       , 2     )
		if mod == 1:
				return all_numbers[div]
		else:
				return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	_lowerCamelCase 					=      [float(x) for x in input('Enter the elements of first array: ').split()]
	_lowerCamelCase 					=      [float(x) for x in input('Enter the elements of second array: ').split()]
	print(F'''The median of two arrays is: {median_of_two_arrays(array_a, array_a)}''')



_lowercase							:   Dict						=						"0.21.0"

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
				from .utils import rich



