


import operator as op


_A		       =						'scaler.pt'
_A		       =						'pytorch_model'
_A		       =						'random_states'
_A		       =						'optimizer'
_A		       =						'scheduler'
_A		       =						'pytorch_model.bin'
_A		       =						'pytorch_model.bin.index.json'
_A		       =						'model.safetensors'
_A		       =						'model.safetensors.index.json'
_A		       =						'1.10.2'
_A		       =						'py38'
_A		       =						'4.17.0'
_A		       =						['ml.p3.16xlarge', 'ml.p3dn.24xlarge', 'ml.p4dn.24xlarge']
_A		       =						['FULL_SHARD', 'SHARD_GRAD_OP', 'NO_SHARD', 'HYBRID_SHARD', 'HYBRID_SHARD_ZERO2']
_A		       =						['TRANSFORMER_BASED_WRAP', 'SIZE_BASED_WRAP', 'NO_WRAP']
_A		       =						['BACKWARD_PRE', 'BACKWARD_POST', 'NO_PREFETCH']
_A		       =						['FULL_STATE_DICT', 'LOCAL_STATE_DICT', 'SHARDED_STATE_DICT']
_A		       =						'2.0.1'
_A		       =						['pdsh', 'standard', 'openmpi', 'mvapich']
_A		       =						['default', 'reduce-overhead', 'max-autotune']

_A		       =						{'>': op.gt, '>=': op.ge, '==': op.eq, '!=': op.ne, '<=': op.le, '<': op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
_A		       =						[
    'nnodes',
    'nproc_per_node',
    'rdzv_backend',
    'rdzv_endpoint',
    'rdzv_id',
    'rdzv_conf',
    'standalone',
    'max_restarts',
    'monitor_interval',
    'start_method',
    'role',
    'module',
    'm',
    'no_python',
    'run_path',
    'log_dir',
    'r',
    'redirects',
    't',
    'tee',
    'node_rank',
    'master_addr',
    'master_port',
]

_A		       =						['DEEPSPEED', 'MULTI_GPU', 'FSDP', 'MEGATRON_LM']
_A		       =						['DEEPSPEED', 'MULTI_XPU', 'FSDP']







from __future__ import annotations




def 				a						(							snake_case__:					list[int]						,   snake_case__:					int						,   snake_case__:					int						,   snake_case__:					int					):


				'''simple docstring'''
				if (direction == 1 and array[indexa] > array[indexa]) or (
				    direction == 0 and array[indexa] < array[indexa]
				):
								lowercase_  ,	lowercase_       =					array[indexa], array[indexa]




def 				a						(							snake_case__:					list[int]						,   snake_case__:					int						,   snake_case__:					int						,   snake_case__:					int					):


				'''simple docstring'''
				if length > 1:
								lowercase_       =					int(length / 2					)
								for i in range(snake_case__						,   low + middle					):
												comp_and_swap(snake_case__						,   snake_case__						,   i + middle						,   snake_case__					)
								bitonic_merge(snake_case__						,   snake_case__						,   snake_case__						,   snake_case__					)
								bitonic_merge(snake_case__						,   low + middle						,   snake_case__						,   snake_case__					)




def 				a						(							snake_case__:					list[int]						,   snake_case__:					int						,   snake_case__:					int						,   snake_case__:					int					):


				'''simple docstring'''
				if length > 1:
								lowercase_       =					int(length / 2					)
								bitonic_sort(snake_case__						,   snake_case__						,   snake_case__						,   1					)
								bitonic_sort(snake_case__						,   low + middle						,   snake_case__						,   0					)
								bitonic_merge(snake_case__						,   snake_case__						,   snake_case__						,   snake_case__					)


if __name__ == "__main__":
						__a  			=					input('Enter numbers separated by a comma:\n').strip()
						__a  			=					[int(item.strip()) for item in user_input.split(',')]

						bitonic_sort(unsorted, 0, len(unsorted), 1)
						print('\nSorted array in ascending order is: ', end='')
						print(*unsorted, sep=', ')

						bitonic_merge(unsorted, 0, len(unsorted), 0)
						print('Sorted array in descending order is: ', end='')
						print(*unsorted, sep=', ')




