






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']














def      __A					(     _lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= word.split()

					def justify(_lowercase					,			_lowercase					,			_lowercase ) -> str:
										_A								= max_width - width
										_A								= len(_lowercase )
										if len(_lowercase ) == 1:
															# if there is only word in line
															# just insert overall_spaces_count for the remainder of line
															return line[0] + " " * overall_spaces_count
										else:
															_A								= words_count - 1
															# num_spaces_between_words_list[i] : tells you to insert
															# num_spaces_between_words_list[i] spaces
															# after word on line[i]
															_A								= spaces_to_insert_between_words * [
															    overall_spaces_count // spaces_to_insert_between_words
															]
															_A								= (
															    overall_spaces_count % spaces_to_insert_between_words
															)
															# distribute spaces via round robin to the left words
															for i in range(_lowercase ):
																				num_spaces_between_words_list[i] += 1
															_A								= []
															for i in range(_lowercase ):
																				# add the word
																				aligned_words_list.append(line[i] )
																				# add the spaces to insert
																				aligned_words_list.append(num_spaces_between_words_list[i] * ''' ''' )
															# just add the last word to the sentence
															aligned_words_list.append(line[-1] )
															# join the aligned words list to form a justified line
															return "".join(_lowercase )

					_A								= []
					_A								= []
					_A								= 0
					for word in words:
										if width + len(_lowercase ) + len(_lowercase ) <= max_width:
															# keep adding words until we can fill out max_width
															# width = sum of length of all words (without overall_spaces_count)
															# len(word) = length of current word
															# len(line) = number of overall_spaces_count to insert between words
															line.append(_lowercase )
															width += len(_lowercase )
										else:
															# justify the line and add it to result
															answer.append(justify(_lowercase					,			_lowercase					,			_lowercase ) )
															# reset new line and new width
															_A							,_A								= [word], len(_lowercase )
					_A								= max_width - width - len(_lowercase )
					answer.append(''' '''.join(_lowercase ) + (remaining_spaces + 1) * ''' ''' )
					return answer


if __name__ == "__main__":
				from doctest import testmod

				testmod()



