


# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import copy
import importlib.metadata
import json
import os
from dataclasses import dataclass
from typing import Any, Dict, Union

from packaging import version

from ..utils import is_torch_available, logging


if is_torch_available():
   import torch


lowerCamelCase__							:						Dict							     =   logging.get_logger(__name__)
@dataclass
class 		__magic_name__						:





     '''simple docstring'''



     def __init__(					self:Dict     ,		_a:Any=False     ,		_a:str=False     ,		_a:Optional[int]=6.0     ,		_a:Any=None     ,		_a:List[str]=False     ,		_a:int=False     ,		_a:Dict=None     ,		_a:int="fp4"     ,		_a:Optional[Any]=False     ,		**_a:List[Any]     ,		):
       snake_case__						= load_in_abit
       snake_case__						= load_in_abit
       snake_case__						= llm_inta_threshold
       snake_case__						= llm_inta_skip_modules
       snake_case__						= llm_inta_enable_fpaa_cpu_offload
       snake_case__						= llm_inta_has_fpaa_weight
       snake_case__						= bnb_abit_quant_type
       snake_case__						= bnb_abit_use_double_quant

       if bnb_abit_compute_dtype is None:
         snake_case__						= torch.floataa
       elif isinstance(_a     ,		_a   ):
         snake_case__						= getattr(_a     ,		_a   )
       elif isinstance(_a     ,		torch.dtype   ):
         snake_case__						= bnb_abit_compute_dtype
       else:
         raise ValueError('''bnb_4bit_compute_dtype must be a string or a torch.dtype'''   )

       self.post_init()

     def 	SCREAMING_SNAKE_CASE__						(					self:str   ):
       if not isinstance(self.llm_inta_threshold     ,		_a   ):
         raise ValueError('''llm_int8_threshold must be a float'''   )

       if self.llm_inta_skip_modules is not None and not isinstance(self.llm_inta_skip_modules     ,		_a   ):
         raise ValueError('''llm_int8_skip_modules must be a list of strings'''   )
       if not isinstance(self.llm_inta_enable_fpaa_cpu_offload     ,		_a   ):
         raise ValueError('''llm_int8_enable_fp32_cpu_offload must be a boolean'''   )

       if not isinstance(self.llm_inta_has_fpaa_weight     ,		_a   ):
         raise ValueError('''llm_int8_has_fp16_weight must be a boolean'''   )

       if self.bnb_abit_compute_dtype is not None and not isinstance(self.bnb_abit_compute_dtype     ,		torch.dtype   ):
         raise ValueError('''bnb_4bit_compute_dtype must be torch.dtype'''   )

       if not isinstance(self.bnb_abit_quant_type     ,		_a   ):
         raise ValueError('''bnb_4bit_quant_type must be a string'''   )

       if not isinstance(self.bnb_abit_use_double_quant     ,		_a   ):
         raise ValueError('''bnb_4bit_use_double_quant must be a boolean'''   )

       if self.load_in_abit and not version.parse(importlib.metadata.version('''bitsandbytes'''   )   ) >= version.parse(
           '''0.39.0'''   ):
         raise ValueError(
             '''4 bit quantization requires bitsandbytes>=0.39.0 - please upgrade your bitsandbytes version'''   )

     def 	SCREAMING_SNAKE_CASE__						(					self:Optional[Any]   ):
       return self.load_in_abit or self.load_in_abit

     def 	SCREAMING_SNAKE_CASE__						(					self:Tuple   ):
       if self.load_in_abit:
         return "llm_int8"
       elif self.load_in_abit and self.bnb_abit_quant_type == "fp4":
         return "fp4"
       elif self.load_in_abit and self.bnb_abit_quant_type == "nf4":
         return "nf4"
       else:
         return None

     @classmethod
     def 	SCREAMING_SNAKE_CASE__						(					cls:List[str]     ,		_a:int     ,		_a:int     ,		**_a:Any   ):
       snake_case__						= cls(**_a   )

       snake_case__						= []
       for key, value in kwargs.items():
         if hasattr(_a     ,		_a   ):
           setattr(_a     ,		_a     ,		_a   )
           to_remove.append(_a   )
       for key in to_remove:
         kwargs.pop(_a     ,		_a   )

       if return_unused_kwargs:
         return config, kwargs
       else:
         return config

     def 	SCREAMING_SNAKE_CASE__						(					self:Dict     ,		_a:Union[str, os.PathLike]   ):
       with open(_a     ,		'''w'''     ,		encoding='''utf-8'''   ) as writer:
         snake_case__						= self.to_dict()
         snake_case__						= json.dumps(_a     ,		indent=2     ,		sort_keys=_a   ) + '''\n'''

         writer.write(_a   )

     def 	SCREAMING_SNAKE_CASE__						(					self:List[str]   ):
       snake_case__						= copy.deepcopy(self.__dict__   )
       snake_case__						= str(output['''bnb_4bit_compute_dtype''']   ).split('''.'''   )[1]

       return output

     def __repr__(					self:List[Any]   ):
       return F"""{self.__class__.__name__} {self.to_json_string()}"""

     def 	SCREAMING_SNAKE_CASE__						(					self:Optional[Any]     ,		_a:bool = True   ):
       if use_diff is True:
         snake_case__						= self.to_diff_dict()
       else:
         snake_case__						= self.to_dict()
       return json.dumps(_a     ,		indent=2     ,		sort_keys=_a   ) + "\n"







     def 	SCREAMING_SNAKE_CASE__						(					self:Union[str, Any]   ):
       snake_case__						= self.to_dict()

       # get the default config dict
       snake_case__						= BitsAndBytesConfig().to_dict()

       snake_case__						= {}

       # only serialize values that differ from the default config
       for key, value in config_dict.items():
         if value != default_config_dict[key]:
           snake_case__						= value

       return serializable_config_dict





lowerCamelCase__							:						List[str]							     =   """Alexander Joslin"""

import operator as op

from .stack import Stack







def SCREAMING_SNAKE_CASE	(			__lowerCAmelCase				)    ->				int:
  snake_case__						= {'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-''': op.sub}

  snake_case__						= Stack()
  snake_case__						= 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
      snake_case__						= operator_stack.peek()
      operator_stack.pop()
      snake_case__						= operand_stack.peek()
      operand_stack.pop()
      snake_case__						= operand_stack.peek()
      operand_stack.pop()

      snake_case__						= operators[opr](__lowerCAmelCase							,   __lowerCAmelCase				)
      operand_stack.push(__lowerCAmelCase				)

    # RULE 5
  return operand_stack.peek()


if __name__ == "__main__":
   lowerCamelCase__							:						Optional[Any]							     =   """(5 + ((4 * 2) * (2 + 3)))"""
   # answer = 45
   print(F"""{equation} = {dijkstras_two_stack_algorithm(equation)}""")

