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





@dataclass
class 							lowercase						:


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

         if bnb_abit_compute_dtype is None:
               lowercase_     =      torch.floataa
         elif isinstance(__lowerCAmelCase   ,		__lowerCAmelCase):
               lowercase_     =      getattr(__lowerCAmelCase   ,		__lowerCAmelCase)
         elif isinstance(__lowerCAmelCase   ,		torch.dtype):
               lowercase_     =      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				:	str)      ->					Any:
         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 __UpperCAmelCase       (   self				:	List[str])      ->					str:
         return self.load_in_abit or self.load_in_abit


   def __UpperCAmelCase       (   self				:	str)      ->					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 __UpperCAmelCase       (   cls				:	Dict   ,		__lowerCAmelCase				:	Any   ,		__lowerCAmelCase				:	str   ,		**__lowerCAmelCase				:	Dict)      ->					int:
         lowercase_     =      cls(**__lowerCAmelCase)

         lowercase_     =      []
         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 __UpperCAmelCase       (   self				:	Union[str, Any]   ,		__lowerCAmelCase				:	Union[str, os.PathLike])      ->					Optional[Any]:
         with open(__lowerCAmelCase   ,		"w"   ,		encoding="utf-8") as writer:
               lowercase_     =      self.to_dict()
               lowercase_     =      json.dumps(__lowerCAmelCase   ,		indent=2   ,		sort_keys=__lowerCAmelCase) + "\n"

               writer.write(__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Union[str, Any])      ->					Dict[str, Any]:
         lowercase_     =      copy.deepcopy(self.__dict__)
         lowercase_     =      str(output["bnb_4bit_compute_dtype"]).split(".")[1]

         return output


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


   def __UpperCAmelCase       (   self				:	str   ,		__lowerCAmelCase				:	bool = True)      ->					str:
         if use_diff is True:
               lowercase_     =      self.to_diff_dict()
         else:
               lowercase_     =      self.to_dict()
         return json.dumps(__lowerCAmelCase   ,		indent=2   ,		sort_keys=__lowerCAmelCase) + "\n"


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Dict[str, Any]:
         lowercase_     =      self.to_dict()

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

         lowercase_     =      {}

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

         return serializable_config_dict







'''simple docstring'''

import json
import sys


def __a (	__lowerCamelCase			:						Optional[int] ,		__lowerCamelCase			:						Union[str, Any]				)	->							Optional[Any]:
      '''simple docstring'''


      with open(__lowerCamelCase ,		encoding="utf-8"				) as f:
            lowercase_     =      json.load(__lowerCamelCase				)

      lowercase_     =      ["<details>", "<summary>Show updated benchmarks!</summary>", " "]

      for benchmark_name in sorted(__lowerCamelCase				):
            lowercase_     =      results[benchmark_name]

            lowercase_     =      benchmark_name.split("/"				)[-1]
            output_md.append(f'### Benchmark: {benchmark_file_name}'				)

            lowercase_     =      "| metric |"
            lowercase_     =      "|--------|"
            lowercase_     =      "| new / old (diff) |"
            for metric_name in sorted(__lowerCamelCase				):
                  lowercase_     =      benchmark_res[metric_name]
                  lowercase_     =      metric_vals["new"]
                  lowercase_     =      metric_vals.get("old" ,		__lowerCamelCase				)
                  lowercase_     =      metric_vals.get("diff" ,		__lowerCamelCase				)

                  lowercase_     =      f' {new_val:f}' if isinstance(__lowerCamelCase ,		(int, float)				) else "None"

                  if old_val is not None:
                        val_str += f' / {old_val:f}' if isinstance(__lowerCamelCase ,		(int, float)				) else "None"
                  if dif_val is not None:
                        val_str += f' ({dif_val:f})' if isinstance(__lowerCamelCase ,		(int, float)				) else "None"

                  title += " " + metric_name + " |"
                  lines += "---|"
                  value += val_str + " |"

            output_md += [title, lines, value, " "]

      output_md.append("</details>"				)

      with open(__lowerCamelCase ,		"w" ,		encoding="utf-8"				) as f:
            f.writelines("\n".join(__lowerCamelCase				)				)


if __name__ == "__main__":
       lowerCAmelCase_ : List[Any]						  =      sys.argv[1]
       lowerCAmelCase_ : Any						  =      sys.argv[2]

       format_json_to_md(input_json_file, output_md_file)






