




'''simple docstring'''







import operator as op


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

A				:					List[Any]    						=			{'''>''': 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				:					Tuple    						=			[
    '''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				:					List[str]    						=			['''DEEPSPEED''', '''MULTI_GPU''', '''FSDP''', '''MEGATRON_LM''']
A				:					Any    						=			['''DEEPSPEED''', '''MULTI_XPU''', '''FSDP''']










'''simple docstring'''







A				:					Dict    						=			'''Alexander Joslin'''

import operator as op

from .stack import Stack






def 				lowerCAmelCase__	(    lowerCamelCase					:      str       ):
       _A					:     Dict     = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}

       _A					:     Stack[int]     = Stack()
       _A					:     Stack[str]     = Stack()

       for i in equation:
              if i.isdigit():
                     # RULE 1
                     operand_stack.push(int(lowerCamelCase       )       )
              elif i in operators:
                     # RULE 2
                     operator_stack.push(lowerCamelCase       )
              elif i == ")":
                     # RULE 4
                     _A					:     List[str]     = operator_stack.peek()
                     operator_stack.pop()
                     _A					:     Dict     = operand_stack.peek()
                     operand_stack.pop()
                     _A					:     Optional[int]     = operand_stack.peek()
                     operand_stack.pop()

                     _A					:     Dict     = operators[opr](lowerCamelCase  ,lowerCamelCase       )
                     operand_stack.push(lowerCamelCase       )

    # RULE 5
       return operand_stack.peek()


if __name__ == "__main__":
   A				:					Dict    						=			'''(5 + ((4 * 2) * (2 + 3)))'''
   # answer = 45
   print(f"""{equation} = {dijkstras_two_stack_algorithm(equation)}""")






