
"""simple docstring"""







# 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__           =	logging.get_logger(__name__)




@dataclass
class 				A__ :

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

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

			self.post_init()

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

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

			if not isinstance(self.bnb_abit_use_double_quant ,	_SCREAMING_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 							__lowerCamelCase							(   self				):
			return self.load_in_abit or self.load_in_abit

		def 							__lowerCamelCase							(   self				):
			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 							__lowerCamelCase							(   cls ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE ,	**_SCREAMING_SNAKE_CASE				):
			__lowerCAmelCase    :		Dict		    =   cls(**_SCREAMING_SNAKE_CASE				)

			__lowerCAmelCase    :		Optional[Any]		    =   []
			for key, value in kwargs.items():
				if hasattr(_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE				):
					setattr(_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE				)
					to_remove.append(_SCREAMING_SNAKE_CASE				)
			for key in to_remove:
				kwargs.pop(_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE				)

			if return_unused_kwargs:
				return config, kwargs
			else:
				return config

		def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE				):
			with open(_SCREAMING_SNAKE_CASE ,	'w' ,	encoding='utf-8'				) as writer:
				__lowerCAmelCase    :		Optional[int]		    =   self.to_dict()
				__lowerCAmelCase    :		Any		    =   json.dumps(_SCREAMING_SNAKE_CASE ,	indent=2 ,	sort_keys=_SCREAMING_SNAKE_CASE				) + '\n'

				writer.write(_SCREAMING_SNAKE_CASE				)

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

			return output

		def __repr__(   self				):
			return f"{self.__class__.__name__} {self.to_json_string()}"

		def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE = True				):
			if use_diff is True:
				__lowerCAmelCase    :		Optional[Any]		    =   self.to_diff_dict()
			else:
				__lowerCAmelCase    :		List[str]		    =   self.to_dict()
			return json.dumps(_SCREAMING_SNAKE_CASE ,	indent=2 ,	sort_keys=_SCREAMING_SNAKE_CASE				) + "\n"







		def 							__lowerCamelCase							(   self				):
			__lowerCAmelCase    :		List[str]		    =   self.to_dict()

			# get the default config dict
			__lowerCAmelCase    :		List[str]		    =   BitsAndBytesConfig().to_dict()

			__lowerCAmelCase    :		Tuple		    =   {}

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

			return serializable_config_dict

"""simple docstring"""







def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase	):
	__lowerCAmelCase    :		List[str]		    =   len(_UpperCamelCase	)
	__lowerCAmelCase    :		Tuple		    =   [[0] * n for i in range(_UpperCamelCase	)]
	for i in range(_UpperCamelCase	):
		__lowerCAmelCase    :		Any		    =   y_points[i]

	for i in range(2 ,						_UpperCamelCase	):
		for j in range(_UpperCamelCase ,						_UpperCamelCase	):
			__lowerCAmelCase    :		int		    =   (
			    (xa - x_points[j - i + 1]) * q[j][i - 1]
			    - (xa - x_points[j]) * q[j - 1][i - 1]
			) / (x_points[j] - x_points[j - i + 1])

	return [q[n - 1][n - 1], q]


if __name__ == "__main__":
							import doctest

							doctest.testmod()