






import os

import torch

from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version


if is_torch_version(""">=""", FSDP_PYTORCH_VERSION):
					import torch.distributed.checkpoint as dist_cp
					from torch.distributed.checkpoint.default_planner import DefaultLoadPlanner, DefaultSavePlanner
					from torch.distributed.checkpoint.optimizer import load_sharded_optimizer_state_dict
					from torch.distributed.fsdp.fully_sharded_data_parallel import FullyShardedDataParallel as FSDP
					from torch.distributed.fsdp.fully_sharded_data_parallel import StateDictType


SCREAMING_SNAKE_CASE__   :      List[Any]				=		get_logger(__name__)

def   __lowercase       (			snake_case,	snake_case,	snake_case,	snake_case,	snake_case=0			):







				"""simple docstring"""






				os.makedirs(snake_case,	exist_ok=snake_case			)
				with FSDP.state_dict_type(
				    snake_case,	fsdp_plugin.state_dict_type,	fsdp_plugin.state_dict_config,	fsdp_plugin.optim_state_dict_config			):
								__magic_name__		:Tuple   =   model.state_dict()
								if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
												__magic_name__		:List[Any]   =   f'''{MODEL_NAME}.bin''' if model_index == 0 else f'''{MODEL_NAME}_{model_index}.bin'''
												__magic_name__		:int   =   os.path.join(snake_case,	snake_case			)
												if accelerator.process_index == 0:
																logger.info(f'''Saving model to {output_model_file}'''			)
																torch.save(snake_case,	snake_case			)
																logger.info(f'''Model saved to {output_model_file}'''			)
								elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
												__magic_name__		:Optional[int]   =   (
												    f'''{MODEL_NAME}_rank{accelerator.process_index}.bin'''
												    if model_index == 0
												    else f'''{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'''
												)
												__magic_name__		:List[Any]   =   os.path.join(snake_case,	snake_case			)
												logger.info(f'''Saving model to {output_model_file}'''			)
												torch.save(snake_case,	snake_case			)
												logger.info(f'''Model saved to {output_model_file}'''			)
								elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
												__magic_name__		:Optional[Any]   =   os.path.join(snake_case,	f'''{MODEL_NAME}_{model_index}'''			)
												os.makedirs(snake_case,	exist_ok=snake_case			)
												logger.info(f'''Saving model to {ckpt_dir}'''			)
												__magic_name__		:List[Any]   =   {'''model''': state_dict}

												dist_cp.save_state_dict(
												    state_dict=snake_case,	storage_writer=dist_cp.FileSystemWriter(snake_case			),	planner=DefaultSavePlanner(),	)
												logger.info(f'''Model saved to {ckpt_dir}'''			)

def   __lowercase       (			snake_case,	snake_case,	snake_case,	snake_case,	snake_case=0			):







				"""simple docstring"""






				accelerator.wait_for_everyone()
				with FSDP.state_dict_type(
				    snake_case,	fsdp_plugin.state_dict_type,	fsdp_plugin.state_dict_config,	fsdp_plugin.optim_state_dict_config			):
								if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
												if type(snake_case			) != FSDP and accelerator.process_index != 0:
																if not fsdp_plugin.sync_module_states:
																				raise ValueError(
																				    '''Set the `sync_module_states` flag to `True` so that model states are synced across processes when '''
																				    '''initializing FSDP object'''			)
																return
												__magic_name__		:List[Any]   =   f'''{MODEL_NAME}.bin''' if model_index == 0 else f'''{MODEL_NAME}_{model_index}.bin'''
												__magic_name__		:Any   =   os.path.join(snake_case,	snake_case			)
												logger.info(f'''Loading model from {input_model_file}'''			)
												__magic_name__		:Any   =   torch.load(snake_case			)
												logger.info(f'''Model loaded from {input_model_file}'''			)
								elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
												__magic_name__		:Union[str, Any]   =   (
												    f'''{MODEL_NAME}_rank{accelerator.process_index}.bin'''
												    if model_index == 0
												    else f'''{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'''
												)
												__magic_name__		:Tuple   =   os.path.join(snake_case,	snake_case			)
												logger.info(f'''Loading model from {input_model_file}'''			)
												__magic_name__		:List[Any]   =   torch.load(snake_case			)
												logger.info(f'''Model loaded from {input_model_file}'''			)
								elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
												__magic_name__		:Tuple   =   (
												    os.path.join(snake_case,	f'''{MODEL_NAME}_{model_index}'''			)
												    if f'''{MODEL_NAME}''' not in input_dir
												    else input_dir
												)
												logger.info(f'''Loading model from {ckpt_dir}'''			)
												__magic_name__		:Any   =   {'''model''': model.state_dict()}
												dist_cp.load_state_dict(
												    state_dict=snake_case,	storage_reader=dist_cp.FileSystemReader(snake_case			),	planner=DefaultLoadPlanner(),	)
												__magic_name__		:Any   =   state_dict['''model''']
												logger.info(f'''Model loaded from {ckpt_dir}'''			)
								model.load_state_dict(snake_case			)

def   __lowercase       (			snake_case,	snake_case,	snake_case,	snake_case,	snake_case,	snake_case=0			):







				"""simple docstring"""






				os.makedirs(snake_case,	exist_ok=snake_case			)
				with FSDP.state_dict_type(
				    snake_case,	fsdp_plugin.state_dict_type,	fsdp_plugin.state_dict_config,	fsdp_plugin.optim_state_dict_config			):
								__magic_name__		:List[Any]   =   FSDP.optim_state_dict(snake_case,	snake_case			)
								if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
												if accelerator.process_index == 0:
																__magic_name__		:Optional[int]   =   (
																    f'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else f'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
																)
																__magic_name__		:str   =   os.path.join(snake_case,	snake_case			)
																logger.info(f'''Saving Optimizer state to {output_optimizer_file}'''			)
																torch.save(snake_case,	snake_case			)
																logger.info(f'''Optimizer state saved in {output_optimizer_file}'''			)
								else:
												__magic_name__		:Tuple   =   os.path.join(snake_case,	f'''{OPTIMIZER_NAME}_{optimizer_index}'''			)
												os.makedirs(snake_case,	exist_ok=snake_case			)
												logger.info(f'''Saving Optimizer state to {ckpt_dir}'''			)
												dist_cp.save_state_dict(
												    state_dict={'''optimizer''': optim_state},	storage_writer=dist_cp.FileSystemWriter(snake_case			),	planner=DefaultSavePlanner(),	)
												logger.info(f'''Optimizer state saved in {ckpt_dir}'''			)

def   __lowercase       (			snake_case,	snake_case,	snake_case,	snake_case,	snake_case,	snake_case=0			):







				"""simple docstring"""






				accelerator.wait_for_everyone()
				with FSDP.state_dict_type(
				    snake_case,	fsdp_plugin.state_dict_type,	fsdp_plugin.state_dict_config,	fsdp_plugin.optim_state_dict_config			):
								if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
												__magic_name__		:Tuple   =   None
												# below check should work but currently it isn't working (mostly opytorch issue),
												# in the meantime disabling it at the cost of excess memory usage
												# if accelerator.process_index == 0 or not fsdp_plugin.optim_state_dict_config.rank0_only:
												__magic_name__		:Optional[Any]   =   (
												    f'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else f'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
												)
												__magic_name__		:str   =   os.path.join(snake_case,	snake_case			)
												logger.info(f'''Loading Optimizer state from {input_optimizer_file}'''			)
												__magic_name__		:Optional[int]   =   torch.load(snake_case			)
												logger.info(f'''Optimizer state loaded from {input_optimizer_file}'''			)
								else:
												__magic_name__		:Tuple   =   (
												    os.path.join(snake_case,	f'''{OPTIMIZER_NAME}_{optimizer_index}'''			)
												    if f'''{OPTIMIZER_NAME}''' not in input_dir
												    else input_dir
												)
												logger.info(f'''Loading Optimizer from {ckpt_dir}'''			)
												__magic_name__		:List[str]   =   load_sharded_optimizer_state_dict(
												    model_state_dict=model.state_dict(),	optimizer_key='''optimizer''',	storage_reader=dist_cp.FileSystemReader(snake_case			),	)
												__magic_name__		:str   =   optim_state['''optimizer''']
												logger.info(f'''Optimizer loaded from {ckpt_dir}'''			)
								__magic_name__		:Tuple   =   FSDP.optim_state_dict_to_load(snake_case,	snake_case,	snake_case			)
								optimizer.load_state_dict(snake_case			)












from binascii import hexlify
from hashlib import shaaaa
from os import urandom

# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526

lowercase__							:	Dict											=		{
    # 1536-bit
    5: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA237327FFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 2048-bit
    14: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
            + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
            + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
            + "15728E5A8AACAA68FFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 3072-bit
    15: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
            + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
            + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
            + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
            + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
            + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
            + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
            + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
            + "43DB5BFCE0FD108E4B82D120A93AD2CAFFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 4096-bit
    16: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
            + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
            + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
            + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
            + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
            + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
            + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
            + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
            + "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7"
            + "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA"
            + "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6"
            + "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED"
            + "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9"
            + "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934063199"
            + "FFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 6144-bit
    17: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD129024E08"
            + "8A67CC74020BBEA63B139B22514A08798E3404DDEF9519B3CD3A431B"
            + "302B0A6DF25F14374FE1356D6D51C245E485B576625E7EC6F44C42E9"
            + "A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F24117C4B1FE6"
            + "49286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8"
            + "FD24CF5F83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3BE39E772C"
            + "180E86039B2783A2EC07A28FB5C55DF06F4C52C9DE2BCBF695581718"
            + "3995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D"
            + "04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7D"
            + "B3970F85A6E1E4C7ABF5AE8CDB0933D71E8C94E04A25619DCEE3D226"
            + "1AD2EE6BF12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
            + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB3143DB5BFC"
            + "E0FD108E4B82D120A92108011A723C12A787E6D788719A10BDBA5B26"
            + "99C327186AF4E23C1A946834B6150BDA2583E9CA2AD44CE8DBBBC2DB"
            + "04DE8EF92E8EFC141FBECAA6287C59474E6BC05D99B2964FA090C3A2"
            + "233BA186515BE7ED1F612970CEE2D7AFB81BDD762170481CD0069127"
            + "D5B05AA993B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492"
            + "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BDF8FF9406"
            + "AD9E530EE5DB382F413001AEB06A53ED9027D831179727B0865A8918"
            + "DA3EDBEBCF9B14ED44CE6CBACED4BB1BDB7F1447E6CC254B33205151"
            + "2BD7AF426FB8F401378CD2BF5983CA01C64B92ECF032EA15D1721D03"
            + "F482D7CE6E74FEF6D55E702F46980C82B5A84031900B1C9E59E7C97F"
            + "BEC7E8F323A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA"
            + "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE32806A1D58B"
            + "B7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55CDA56C9EC2EF29632"
            + "387FE8D76E3C0468043E8F663F4860EE12BF2D5B0B7474D6E694F91E"
            + "6DCC4024FFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 8192-bit
    18: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
            + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
            + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
            + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
            + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
            + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
            + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
            + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
            + "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7"
            + "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA"
            + "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6"
            + "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED"
            + "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9"
            + "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492"
            + "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BD"
            + "F8FF9406AD9E530EE5DB382F413001AEB06A53ED9027D831"
            + "179727B0865A8918DA3EDBEBCF9B14ED44CE6CBACED4BB1B"
            + "DB7F1447E6CC254B332051512BD7AF426FB8F401378CD2BF"
            + "5983CA01C64B92ECF032EA15D1721D03F482D7CE6E74FEF6"
            + "D55E702F46980C82B5A84031900B1C9E59E7C97FBEC7E8F3"
            + "23A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA"
            + "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE328"
            + "06A1D58BB7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55C"
            + "DA56C9EC2EF29632387FE8D76E3C0468043E8F663F4860EE"
            + "12BF2D5B0B7474D6E694F91E6DBE115974A3926F12FEE5E4"
            + "38777CB6A932DF8CD8BEC4D073B931BA3BC832B68D9DD300"
            + "741FA7BF8AFC47ED2576F6936BA424663AAB639C5AE4F568"
            + "3423B4742BF1C978238F16CBE39D652DE3FDB8BEFC848AD9"
            + "22222E04A4037C0713EB57A81A23F0C73473FC646CEA306B"
            + "4BCBC8862F8385DDFA9D4B7FA2C087E879683303ED5BDD3A"
            + "062B3CF5B3A278A66D2A13F83F44F82DDF310EE074AB6A36"
            + "4597E899A0255DC164F31CC50846851DF9AB48195DED7EA1"
            + "B1D510BD7EE74D73FAF36BC31ECFA268359046F4EB879F92"
            + "4009438B481C6CD7889A002ED5EE382BC9190DA6FC026E47"
            + "9558E4475677E9AA9E3050E2765694DFC81F56E880B96E71"
            + "60C980DD98EDD3DFFFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
}
class 						UpperCAmelCase  :







						'''simple docstring'''





						def __init__(		self				:	Tuple			,      __lowercase				:	int = 14		):






							"""simple docstring"""






							if group not in primes:
								raise ValueError("Unsupported Group"		)
							snake_case_						       =	primes[group]["prime"]
							snake_case_						       =	primes[group]["generator"]

							snake_case_						       =	int(hexlify(urandom(32		)		)			,      base=16		)






						def 			snake_case__		(		self				:	Tuple		):






							"""simple docstring"""






							return hex(self.__private_key		)[2:]






						def 			snake_case__		(		self				:	Optional[int]		):






							"""simple docstring"""






							snake_case_						       =	pow(self.generator			,      self.__private_key			,      self.prime		)
							return hex(__lowercase		)[2:]






						def 			snake_case__		(		self				:	int			,      __lowercase				:	int		):






							"""simple docstring"""






							return (
							    2 <= key <= self.prime - 2
							    and pow(__lowercase			,      (self.prime - 1) // 2			,      self.prime		) == 1
							)






						def 			snake_case__		(		self				:	Union[str, Any]			,      __lowercase				:	str		):






							"""simple docstring"""






							snake_case_						       =	int(__lowercase			,      base=16		)
							if not self.is_valid_public_key(__lowercase		):
								raise ValueError("Invalid public key"		)
							snake_case_						       =	pow(__lowercase			,      self.__private_key			,      self.prime		)
							return shaaaa(str(__lowercase		).encode()		).hexdigest()






						@staticmethod
						def 			snake_case__		(		__lowercase				:	int			,      __lowercase				:	int		):






							"""simple docstring"""






							return (
							    2 <= remote_public_key_str <= prime - 2
							    and pow(__lowercase			,      (prime - 1) // 2			,      __lowercase		) == 1
							)






						@staticmethod
						def 			snake_case__		(		__lowercase				:	str			,      __lowercase				:	str			,      __lowercase				:	int = 14		):






							"""simple docstring"""






							snake_case_						       =	int(__lowercase			,      base=16		)
							snake_case_						       =	int(__lowercase			,      base=16		)
							snake_case_						       =	primes[group]["prime"]
							if not DiffieHellman.is_valid_public_key_static(__lowercase			,      __lowercase		):
								raise ValueError("Invalid public key"		)
							snake_case_						       =	pow(__lowercase			,      __lowercase			,      __lowercase		)
							return shaaaa(str(__lowercase		).encode()		).hexdigest()


if __name__ == "__main__":
		import doctest

		doctest.testmod()
