



import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List

from ..utils import logging
from . import BaseTransformersCLICommand


try:
 from cookiecutter.main import cookiecutter

 __snake_case						:List[str]      		=     True
except ImportError:
 __snake_case						:Any      		=     False

__snake_case						:int      		=     logging.get_logger(__name__)  # pylint: disable=invalid-name





def      __snake_case	(			_UpperCAmelCase				):
    return AddNewModelCommand(args.testing   , args.testing_file   , path=args.path				)

class     _A       (	__lowerCAmelCase    ):



       @staticmethod
       def 		_lowerCamelCase			(		__SCREAMING_SNAKE_CASE							:     Tuple):


           '''simple docstring'''

           __a						       =				parser.add_parser('''add-new-model''')
           add_new_model_parser.add_argument('''--testing'''     ,		action='''store_true'''     ,		help='''If in testing mode.''')
           add_new_model_parser.add_argument('''--testing_file'''     ,		type=lowerCAmelCase_     ,		help='''Configuration file on which to run.''')
           add_new_model_parser.add_argument(
               '''--path'''     ,		type=lowerCAmelCase_     ,		help='''Path to cookiecutter. Should only be used for testing purposes.''')
           add_new_model_parser.set_defaults(func=lowerCAmelCase_)



       def __init__(		self							:     Optional[Any]     ,		__SCREAMING_SNAKE_CASE							:     Dict     ,		__SCREAMING_SNAKE_CASE							:     List[str]     ,		__SCREAMING_SNAKE_CASE							:     Any=None     ,		*__SCREAMING_SNAKE_CASE							:     Union[str, Any]):


           '''simple docstring'''

           __a						       =				testing
           __a						       =				testing_file
           __a						       =				path





       def 		_lowerCamelCase			(		self							:     List[str]):


           '''simple docstring'''

           warnings.warn(
               '''The command `transformers-cli add-new-model` is deprecated and will be removed in v5 of Transformers. '''
               '''It is not actively maintained anymore, so might give a result that won\'t pass all tests and quality '''
               '''checks, you should use `transformers-cli add-new-model-like` instead.''')
           if not _has_cookiecutter:
               raise ImportError(
                   '''Model creation dependencies are required to use the `add_new_model` command. Install them by running '''
                   '''the following at the root of your `transformers` clone:\n\n\t$ pip install -e .[modelcreation]\n''')
           # Ensure that there is no other `cookiecutter-template-xxx` directory in the current working directory
           __a						       =				[directory for directory in os.listdir() if '''cookiecutter-template-''' == directory[:22]]
           if len(lowerCAmelCase_) > 0:
               raise ValueError(
                   '''Several directories starting with `cookiecutter-template-` in current working directory. '''
                   '''Please clean your directory by removing all folders starting with `cookiecutter-template-` or '''
                   '''change your working directory.''')

           __a						       =				(
               Path(lowerCAmelCase_).parent.parent.parent.parent if self._path is None else Path(self._path).parent.parent
           )
           __a						       =				path_to_transformer_root / '''templates''' / '''adding_a_new_model'''

           # Execute cookiecutter
           if not self._testing:
               cookiecutter(str(lowerCAmelCase_))
           else:
               with open(self._testing_file     ,		'''r''') as configuration_file:
                   __a						       =				json.load(lowerCAmelCase_)

               cookiecutter(
                   str(path_to_cookiecutter if self._path is None else self._path)     ,		no_input=lowerCAmelCase_     ,		extra_context=lowerCAmelCase_     ,		)

           __a						       =				[directory for directory in os.listdir() if '''cookiecutter-template-''' in directory[:22]][0]

           # Retrieve configuration
           with open(directory + '''/configuration.json'''     ,		'''r''') as configuration_file:
               __a						       =				json.load(lowerCAmelCase_)

           __a						       =				configuration['''lowercase_modelname''']
           __a						       =				configuration['''generate_tensorflow_pytorch_and_flax''']
           os.remove(F'{directory}/configuration.json')

           __a						       =				'''PyTorch''' in generate_tensorflow_pytorch_and_flax
           __a						       =				'''TensorFlow''' in generate_tensorflow_pytorch_and_flax
           __a						       =				'''Flax''' in generate_tensorflow_pytorch_and_flax

           __a						       =				F'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
           os.makedirs(lowerCAmelCase_     ,		exist_ok=lowerCAmelCase_)
           os.makedirs(F'{path_to_transformer_root}/tests/models/{lowercase_model_name}'     ,		exist_ok=lowerCAmelCase_)

           # Tests require submodules as they have parent imports
           with open(F'{path_to_transformer_root}/tests/models/{lowercase_model_name}/__init__.py'     ,		'''w'''):
               pass

           shutil.move(
               F'{directory}/__init__.py'     ,		F'{model_dir}/__init__.py'     ,		)
           shutil.move(
               F'{directory}/configuration_{lowercase_model_name}.py'     ,		F'{model_dir}/configuration_{lowercase_model_name}.py'     ,		)

           def remove_copy_lines(__SCREAMING_SNAKE_CASE							:     Dict):
               with open(lowerCAmelCase_     ,		'''r''') as f:
                   __a						       =				f.readlines()
               with open(lowerCAmelCase_     ,		'''w''') as f:
                   for line in lines:
                       if "# Copied from transformers." not in line:
                           f.write(lowerCAmelCase_)

           if output_pytorch:
               if not self._testing:
                   remove_copy_lines(F'{directory}/modeling_{lowercase_model_name}.py')

               shutil.move(
                   F'{directory}/modeling_{lowercase_model_name}.py'     ,		F'{model_dir}/modeling_{lowercase_model_name}.py'     ,		)

               shutil.move(
                   F'{directory}/test_modeling_{lowercase_model_name}.py'     ,		F'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_{lowercase_model_name}.py'     ,		)
           else:
               os.remove(F'{directory}/modeling_{lowercase_model_name}.py')
               os.remove(F'{directory}/test_modeling_{lowercase_model_name}.py')

           if output_tensorflow:
               if not self._testing:
                   remove_copy_lines(F'{directory}/modeling_tf_{lowercase_model_name}.py')

               shutil.move(
                   F'{directory}/modeling_tf_{lowercase_model_name}.py'     ,		F'{model_dir}/modeling_tf_{lowercase_model_name}.py'     ,		)

               shutil.move(
                   F'{directory}/test_modeling_tf_{lowercase_model_name}.py'     ,		F'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_tf_{lowercase_model_name}.py'     ,		)
           else:
               os.remove(F'{directory}/modeling_tf_{lowercase_model_name}.py')
               os.remove(F'{directory}/test_modeling_tf_{lowercase_model_name}.py')

           if output_flax:
               if not self._testing:
                   remove_copy_lines(F'{directory}/modeling_flax_{lowercase_model_name}.py')

               shutil.move(
                   F'{directory}/modeling_flax_{lowercase_model_name}.py'     ,		F'{model_dir}/modeling_flax_{lowercase_model_name}.py'     ,		)

               shutil.move(
                   F'{directory}/test_modeling_flax_{lowercase_model_name}.py'     ,		F'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_flax_{lowercase_model_name}.py'     ,		)
           else:
               os.remove(F'{directory}/modeling_flax_{lowercase_model_name}.py')
               os.remove(F'{directory}/test_modeling_flax_{lowercase_model_name}.py')

           shutil.move(
               F'{directory}/{lowercase_model_name}.md'     ,		F'{path_to_transformer_root}/docs/source/en/model_doc/{lowercase_model_name}.md'     ,		)

           shutil.move(
               F'{directory}/tokenization_{lowercase_model_name}.py'     ,		F'{model_dir}/tokenization_{lowercase_model_name}.py'     ,		)

           shutil.move(
               F'{directory}/tokenization_fast_{lowercase_model_name}.py'     ,		F'{model_dir}/tokenization_{lowercase_model_name}_fast.py'     ,		)

           from os import fdopen, remove
           from shutil import copymode, move
           from tempfile import mkstemp

           def replace(__SCREAMING_SNAKE_CASE							:     List[str]     ,		__SCREAMING_SNAKE_CASE							:     Optional[int]     ,		__SCREAMING_SNAKE_CASE							:     Union[str, Any]):
               # Create temp file
               __a       ,   __a						       =				mkstemp()
               __a						       =				False
               with fdopen(lowerCAmelCase_     ,		'''w''') as new_file:
                   with open(lowerCAmelCase_) as old_file:
                       for line in old_file:
                           new_file.write(lowerCAmelCase_)
                           if line_to_copy_below in line:
                               __a						       =				True
                               for line_to_copy in lines_to_copy:
                                   new_file.write(lowerCAmelCase_)

               if not line_found:
                   raise ValueError(F'Line {line_to_copy_below} was not found in file.')

               # Copy the file permissions from the old file to the new file
               copymode(lowerCAmelCase_     ,		lowerCAmelCase_)
               # Remove original file
               remove(lowerCAmelCase_)
               # Move new file
               move(lowerCAmelCase_     ,		lowerCAmelCase_)

           def skip_units(__SCREAMING_SNAKE_CASE							:     Tuple):
               return (
                   ("generating PyTorch" in line and not output_pytorch)
                   or ("generating TensorFlow" in line and not output_tensorflow)
                   or ("generating Flax" in line and not output_flax)
               )

           def replace_in_files(__SCREAMING_SNAKE_CASE							:     Tuple):
               with open(lowerCAmelCase_) as datafile:
                   __a						       =				[]
                   __a						       =				False
                   __a						       =				False
                   for line in datafile:
                       if "# To replace in: " in line and "##" not in line:
                           __a						       =				line.split('''\"''')[1]
                           __a						       =				skip_units(lowerCAmelCase_)
                       elif "# Below: " in line and "##" not in line:
                           __a						       =				line.split('''\"''')[1]
                           __a						       =				skip_units(lowerCAmelCase_)
                       elif "# End." in line and "##" not in line:
                           if not skip_file and not skip_snippet:
                               replace(lowerCAmelCase_     ,		lowerCAmelCase_     ,		lowerCAmelCase_)

                           __a						       =				[]
                       elif "# Replace with" in line and "##" not in line:
                           __a						       =				[]
                       elif "##" not in line:
                           lines_to_copy.append(lowerCAmelCase_)

               remove(lowerCAmelCase_)

           replace_in_files(F'{directory}/to_replace_{lowercase_model_name}.py')
           os.rmdir(lowerCAmelCase_)






import math
import sys






def  snake_case  (       snake_case__			:int)						->   int:
       if number != int(snake_case__):
              raise ValueError("""the value of input must be a natural number""")
       if number < 0:
              raise ValueError("""the value of input must not be a negative number""")
       if number == 0:
              return 1
       _A        =  [-1] * (number + 1)
       _A        =  0
       for i in range(1   ,	number + 1):
              _A        =  sys.maxsize
              _A        =  int(math.sqrt(snake_case__))
              for j in range(1   ,	root + 1):
                     _A        =  1 + answers[i - (j**2)]
                     _A        =  min(snake_case__   ,	snake_case__)
              _A        =  answer
       return answers[number]


if __name__ == "__main__":
    import doctest

    doctest.testmod()




