

# 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


_a:    Optional[Any] 							=			logging.get_logger(__name__)

@dataclass
class 						__UpperCamelCase    :




	def __init__(		self	:						str		,	lowerCAmelCase	:						Tuple=False		,	lowerCAmelCase	:						Dict=False		,	lowerCAmelCase	:						Tuple=6.0		,	lowerCAmelCase	:						List[str]=None		,	lowerCAmelCase	:						Tuple=False		,	lowerCAmelCase	:						int=False		,	lowerCAmelCase	:						Optional[int]=None		,	lowerCAmelCase	:						Tuple="fp4"		,	lowerCAmelCase	:						Optional[int]=False		,	**lowerCAmelCase	:						Optional[Any]		,	):


		'''simple docstring'''







		UpperCAmelCase_       				=			load_in_abit
		UpperCAmelCase_       				=			load_in_abit
		UpperCAmelCase_       				=			llm_inta_threshold
		UpperCAmelCase_       				=			llm_inta_skip_modules
		UpperCAmelCase_       				=			llm_inta_enable_fpaa_cpu_offload
		UpperCAmelCase_       				=			llm_inta_has_fpaa_weight
		UpperCAmelCase_       				=			bnb_abit_quant_type
		UpperCAmelCase_       				=			bnb_abit_use_double_quant

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

		self.post_init()




	def       __A					(		self	:						List[str]							):


		'''simple docstring'''







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

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

		if not isinstance(self.bnb_abit_use_double_quant		,	lowerCAmelCase							):
			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       __A					(		self	:						int							):


		'''simple docstring'''







		return self.load_in_abit or self.load_in_abit




	def       __A					(		self	:						Any							):


		'''simple docstring'''







		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       __A					(		cls	:						Tuple		,	lowerCAmelCase	:						Optional[int]		,	lowerCAmelCase	:						Optional[Any]		,	**lowerCAmelCase	:						int							):


		'''simple docstring'''







		UpperCAmelCase_       				=			cls(**lowerCAmelCase							)

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

		if return_unused_kwargs:
			return config, kwargs
		else:
			return config




	def       __A					(		self	:						List[str]		,	lowerCAmelCase	:						Union[str, os.PathLike]							):


		'''simple docstring'''







		with open(lowerCAmelCase		,	"w"		,	encoding="utf-8"							) as writer:
			UpperCAmelCase_       				=			self.to_dict()
			UpperCAmelCase_       				=			json.dumps(lowerCAmelCase		,	indent=2		,	sort_keys=lowerCAmelCase							) + "\n"

			writer.write(lowerCAmelCase							)




	def       __A					(		self	:						Optional[int]							):


		'''simple docstring'''







		UpperCAmelCase_       				=			copy.deepcopy(self.__dict__							)
		UpperCAmelCase_       				=			str(output["bnb_4bit_compute_dtype"]							).split("."							)[1]

		return output




	def __repr__(		self	:						Optional[int]							):


		'''simple docstring'''







		return F"{self.__class__.__name__} {self.to_json_string()}"




	def       __A					(		self	:						Optional[Any]		,	lowerCAmelCase	:						bool = True							):


		'''simple docstring'''







		if use_diff is True:
			UpperCAmelCase_       				=			self.to_diff_dict()
		else:
			UpperCAmelCase_       				=			self.to_dict()
		return json.dumps(lowerCAmelCase		,	indent=2		,	sort_keys=lowerCAmelCase							) + "\n"




	def       __A					(		self	:						Dict							):


		'''simple docstring'''







		UpperCAmelCase_       				=			self.to_dict()

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

		UpperCAmelCase_       				=			{}

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

		return serializable_config_dict


from collections.abc import Sequence



def       __lowerCAmelCase      (						A       ,     A = False    ):
	if not arr:
		return 0

	UpperCAmelCase_       				=			0 if allow_empty_subarrays else float("-inf"    )
	UpperCAmelCase_       				=			0.0
	for num in arr:
		UpperCAmelCase_       				=			max(0 if allow_empty_subarrays else num       ,     curr_sum + num    )
		UpperCAmelCase_       				=			max(A       ,     A    )

	return max_sum


if __name__ == "__main__":
				from doctest import testmod

				testmod()

				_a:    Any 							=			[-2, 1, -3, 4, -1, 2, 1, -5, 4]
				print(F'{max_subarray_sum(nums) = }')