

def    __UpperCAmelCase (	__a      :			str		,__a      :			str	)			->     int:

					"""simple docstring"""

					assert x is not None
					assert y is not None

					_a	:    List[str]         =		len(__a	)
					_a	:    List[Any]         =		len(__a	)

					# declaring the array for storing the dp values
					_a	:    List[Any]         =		[[0] * (n + 1) for _ in range(m + 1	)]  # noqa: E741

					for i in range(1		,m + 1	):
										for j in range(1		,n + 1	):
															_a	:    List[Any]         =		1 if x[i - 1] == y[j - 1] else 0

															_a	:    Optional[Any]         =		max(l[i - 1][j]		,l[i][j - 1]		,l[i - 1][j - 1] + match	)

					_a	:    Union[str, Any]         =		''''''
					_a      ,					_a	:    Dict         =		m, n
					while i > 0 and j > 0:
										_a	:    Optional[Any]         =		1 if x[i - 1] == y[j - 1] else 0

										if l[i][j] == l[i - 1][j - 1] + match:
															if match == 1:
																				_a	:    int         =		x[i - 1] + seq
															i -= 1
															j -= 1
										elif l[i][j] == l[i - 1][j]:
															i -= 1
										else:
															j -= 1

					return l[m][n], seq


if __name__ == "__main__":
			a__				=		'''AGGTAB'''
			a__				=		'''GXTXAYB'''
			a__				=		4
			a__				=		'''GTAB'''

			a__		,			a__				=		longest_common_subsequence(a, b)
			print('''len =''', ln, ''', sub-sequence =''', subseq)
			import doctest

			doctest.testmod()






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''']



