






"""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


_SCREAMING_SNAKE_CASE					:				List[str]					    =						logging.get_logger(__name__)






@dataclass
class      a						:






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

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

      self.post_init()






    def    UpperCamelCase       (       self     :							Tuple					)     ->		List[Any]:
      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    UpperCamelCase       (       self     :							Dict					)     ->		Dict:
      return self.load_in_abit or self.load_in_abit






    def    UpperCamelCase       (       self     :							Dict					)     ->		Dict:
      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    UpperCamelCase       (       cls     :							Any       ,						__SCREAMING_SNAKE_CASE     :							Dict       ,						__SCREAMING_SNAKE_CASE     :							int       ,						**__SCREAMING_SNAKE_CASE     :							List[Any]					)     ->		List[str]:
      lowerCamelCase_         =						cls(**__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						[]
      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    UpperCamelCase       (       self     :							Optional[int]       ,						__SCREAMING_SNAKE_CASE     :							Union[str, os.PathLike]					)     ->		Any:
      with open(__SCREAMING_SNAKE_CASE       ,						'w'       ,						encoding='utf-8'					) as writer:
        lowerCamelCase_         =						self.to_dict()
        lowerCamelCase_         =						json.dumps(__SCREAMING_SNAKE_CASE       ,						indent=2       ,						sort_keys=__SCREAMING_SNAKE_CASE					) + '\n'

        writer.write(__SCREAMING_SNAKE_CASE					)






    def    UpperCamelCase       (       self     :							Optional[int]					)     ->		Dict[str, Any]:
      lowerCamelCase_         =						copy.deepcopy(self.__dict__					)
      lowerCamelCase_         =						str(output['bnb_4bit_compute_dtype']					).split('.'					)[1]

      return output






    def __repr__(       self     :							Optional[int]					)     ->		Dict:
      return F'''{self.__class__.__name__} {self.to_json_string()}'''






    def    UpperCamelCase       (       self     :							Optional[Any]       ,						__SCREAMING_SNAKE_CASE     :							bool = True					)     ->		str:
      if use_diff is True:
        lowerCamelCase_         =						self.to_diff_dict()
      else:
        lowerCamelCase_         =						self.to_dict()
      return json.dumps(__SCREAMING_SNAKE_CASE       ,						indent=2       ,						sort_keys=__SCREAMING_SNAKE_CASE					) + "\n"






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		Dict[str, Any]:
      lowerCamelCase_         =						self.to_dict()

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

      lowerCamelCase_         =						{}

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

      return serializable_config_dict












"""simple docstring"""





import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


_SCREAMING_SNAKE_CASE					:				Optional[int]					    =						'''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
'''






class      a						(					unittest.TestCase  ,      __snake_case		):






    def    UpperCamelCase       (       self     :							int					)     ->		Optional[int]:
      lowerCamelCase_         =						load_tool('text-question-answering'					)
      self.tool.setup()
      lowerCamelCase_         =						load_tool('text-question-answering'       ,						remote=__SCREAMING_SNAKE_CASE					)






    def    UpperCamelCase       (       self     :							Dict					)     ->		Tuple:
      lowerCamelCase_         =						self.tool(__SCREAMING_SNAKE_CASE       ,						'What did Hugging Face do in April 2021?'					)
      self.assertEqual(__SCREAMING_SNAKE_CASE       ,						'launched the BigScience Research Workshop'					)






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		Optional[int]:
      lowerCamelCase_         =						self.remote_tool(__SCREAMING_SNAKE_CASE       ,						'What did Hugging Face do in April 2021?'					)
      self.assertEqual(__SCREAMING_SNAKE_CASE       ,						'launched the BigScience Research Workshop'					)






    def    UpperCamelCase       (       self     :							List[str]					)     ->		Optional[int]:
      lowerCamelCase_         =						self.tool(text=__SCREAMING_SNAKE_CASE       ,						question='What did Hugging Face do in April 2021?'					)
      self.assertEqual(__SCREAMING_SNAKE_CASE       ,						'launched the BigScience Research Workshop'					)






    def    UpperCamelCase       (       self     :							Union[str, Any]					)     ->		int:
      lowerCamelCase_         =						self.remote_tool(text=__SCREAMING_SNAKE_CASE       ,						question='What did Hugging Face do in April 2021?'					)
      self.assertEqual(__SCREAMING_SNAKE_CASE       ,						'launched the BigScience Research Workshop'					)




