





# 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


__UpperCamelCase:	Optional[int] = logging.get_logger(__name__)


@dataclass
class       __lowerCAmelCase					:


	'''simple docstring'''





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

			if bnb_abit_compute_dtype is None:
					lowercase__					:      Optional[Any]      =		torch.floataa
			elif isinstance(snake_case__,					snake_case__			):
					lowercase__					:      Union[str, Any]      =		getattr(snake_case__,					snake_case__			)
			elif isinstance(snake_case__,					torch.dtype			):
					lowercase__					:      Union[str, Any]      =		bnb_abit_compute_dtype
			else:
					raise ValueError('bnb_4bit_compute_dtype must be a string or a torch.dtype'			)

			self.post_init()

	def    snake_case__(						self:						int			):






			if not isinstance(self.llm_inta_threshold,					snake_case__			):
					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,					snake_case__			):
					raise ValueError('llm_int8_skip_modules must be a list of strings'			)
			if not isinstance(self.llm_inta_enable_fpaa_cpu_offload,					snake_case__			):
					raise ValueError('llm_int8_enable_fp32_cpu_offload must be a boolean'			)

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

			if not isinstance(self.bnb_abit_use_double_quant,					snake_case__			):
					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    snake_case__(						self:						Any			):
			return self.load_in_abit or self.load_in_abit

	def    snake_case__(						self:						List[Any]			):






			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    snake_case__(						cls:						Union[str, Any],					lowerCamelCase_:						int,					lowerCamelCase_:						Optional[Any],					**lowerCamelCase_:						int			):
			lowercase__					:      Optional[int]      =		cls(**snake_case__			)

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

			if return_unused_kwargs:
					return config, kwargs
			else:
					return config

	def    snake_case__(						self:						Any,					lowerCamelCase_:						Union[str, os.PathLike]			):






			with open(snake_case__,					'w',					encoding='utf-8'			) as writer:
					lowercase__					:      int      =		self.to_dict()
					lowercase__					:      Tuple      =		json.dumps(snake_case__,					indent=2,					sort_keys=snake_case__			) + '\n'

					writer.write(snake_case__			)

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

			return output

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

	def    snake_case__(						self:						int,					lowerCamelCase_:						bool = True			):






			if use_diff is True:
					lowercase__					:      str      =		self.to_diff_dict()
			else:
					lowercase__					:      Union[str, Any]      =		self.to_dict()
			return json.dumps(snake_case__,					indent=2,					sort_keys=snake_case__			) + "\n"





	def    snake_case__(						self:						Optional[int]			):
			lowercase__					:      Optional[Any]      =		self.to_dict()

			# get the default config dict
			lowercase__					:      int      =		BitsAndBytesConfig().to_dict()

			lowercase__					:      Dict      =		{}

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

			return serializable_config_dict





from collections.abc import Sequence


def 							__lowerCAmelCase     (							_UpperCamelCase		:	Sequence[int] | None = None						)		->				int:
 '''simple docstring'''


 if nums is None or not nums:
  raise ValueError('Input sequence should not be empty'						)

 SCREAMING_SNAKE_CASE		    =      nums[0]
 for i in range(1		,				len(_UpperCamelCase						)						):
  SCREAMING_SNAKE_CASE		    =      nums[i]
  SCREAMING_SNAKE_CASE		    =      max(_UpperCamelCase		,				ans + num		,				_UpperCamelCase						)

 return ans


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      # Try on a sample input from the user
      a_     :    str     		=   int(input("Enter number of elements : ").strip())
      a_     :    Any     		=   list(map(int, input("\nEnter the numbers : ").strip().split()))[:n]
      print(max_subsequence_sum(array))

