





"""simple docstring"""





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

  __A											=		True
except ImportError:
  __A											=		False

__A											=		logging.get_logger(__name__)  # pylint: disable=invalid-name
def  __A   (_SCREAMING_SNAKE_CASE			)					->List[str]:





  """simple docstring"""


  return AddNewModelCommand(args.testing     ,   args.testing_file     ,   path=args.path			)






class 					_lowerCAmelCase   (     _a       ):
       """simple docstring"""




       @staticmethod
       def      snake_case						(    __UpperCAmelCase      ):



         '''simple docstring'''

         lowerCAmelCase__			:Tuple											=							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=__UpperCAmelCase    , help='Configuration file on which to run.'      )
         add_new_model_parser.add_argument(
             '--path'    , type=__UpperCAmelCase    , help='Path to cookiecutter. Should only be used for testing purposes.'      )
         add_new_model_parser.set_defaults(func=__UpperCAmelCase      )






       def __init__(    self    , __UpperCAmelCase    , __UpperCAmelCase    , __UpperCAmelCase=None    , *__UpperCAmelCase      ):



         '''simple docstring'''

         lowerCAmelCase__			:Dict											=							testing
         lowerCAmelCase__			:Tuple											=							testing_file
         lowerCAmelCase__			:List[Any]											=							path






       def      snake_case						(    self      ):



         '''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
         lowerCAmelCase__			:Tuple											=							[directory for directory in os.listdir() if 'cookiecutter-template-' == directory[:2_2]]
         if len(__UpperCAmelCase      ) > 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.'      )

         lowerCAmelCase__			:Optional[int]											=							(
             Path(__UpperCAmelCase      ).parent.parent.parent.parent if self._path is None else Path(self._path      ).parent.parent
         )
         lowerCAmelCase__			:List[Any]											=							path_to_transformer_root / 'templates' / 'adding_a_new_model'

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

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

         lowerCAmelCase__			:Dict											=							[directory for directory in os.listdir() if 'cookiecutter-template-' in directory[:2_2]][0]

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

         lowerCAmelCase__			:List[str]											=							configuration['lowercase_modelname']
         lowerCAmelCase__			:List[Any]											=							configuration['generate_tensorflow_pytorch_and_flax']
         os.remove(F"{directory}/configuration.json"      )

         lowerCAmelCase__			:List[str]											=							'PyTorch' in generate_tensorflow_pytorch_and_flax
         lowerCAmelCase__			:Optional[Any]											=							'TensorFlow' in generate_tensorflow_pytorch_and_flax
         lowerCAmelCase__			:Tuple											=							'Flax' in generate_tensorflow_pytorch_and_flax

         lowerCAmelCase__			:List[str]											=							F"{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}"
         os.makedirs(__UpperCAmelCase    , exist_ok=__UpperCAmelCase      )
         os.makedirs(F"{path_to_transformer_root}/tests/models/{lowercase_model_name}"    , exist_ok=__UpperCAmelCase      )

         # 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(__UpperCAmelCase      ):
           with open(__UpperCAmelCase    , 'r'      ) as f:
             lowerCAmelCase__			:Any											=							f.readlines()
           with open(__UpperCAmelCase    , 'w'      ) as f:
             for line in lines:
               if "# Copied from transformers." not in line:
                 f.write(__UpperCAmelCase      )

         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(__UpperCAmelCase    , __UpperCAmelCase    , __UpperCAmelCase      ):
           # Create temp file
           lowerCAmelCase__			:str											=							mkstemp()
           lowerCAmelCase__			:List[Any]											=							False
           with fdopen(__UpperCAmelCase    , 'w'      ) as new_file:
             with open(__UpperCAmelCase      ) as old_file:
               for line in old_file:
                 new_file.write(__UpperCAmelCase      )
                 if line_to_copy_below in line:
                   lowerCAmelCase__			:Dict											=							True
                   for line_to_copy in lines_to_copy:
                     new_file.write(__UpperCAmelCase      )

           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(__UpperCAmelCase    , __UpperCAmelCase      )
           # Remove original file
           remove(__UpperCAmelCase      )
           # Move new file
           move(__UpperCAmelCase    , __UpperCAmelCase      )

         def skip_units(__UpperCAmelCase      ):
           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(__UpperCAmelCase      ):
           with open(__UpperCAmelCase      ) as datafile:
             lowerCAmelCase__			:Any											=							[]
             lowerCAmelCase__			:Union[str, Any]											=							False
             lowerCAmelCase__			:Optional[Any]											=							False
             for line in datafile:
               if "# To replace in: " in line and "##" not in line:
                 lowerCAmelCase__			:Tuple											=							line.split('"'      )[1]
                 lowerCAmelCase__			:Any											=							skip_units(__UpperCAmelCase      )
               elif "# Below: " in line and "##" not in line:
                 lowerCAmelCase__			:Dict											=							line.split('"'      )[1]
                 lowerCAmelCase__			:List[Any]											=							skip_units(__UpperCAmelCase      )
               elif "# End." in line and "##" not in line:
                 if not skip_file and not skip_snippet:
                   replace(__UpperCAmelCase    , __UpperCAmelCase    , __UpperCAmelCase      )

                 lowerCAmelCase__			:Union[str, Any]											=							[]
               elif "# Replace with" in line and "##" not in line:
                 lowerCAmelCase__			:Any											=							[]
               elif "##" not in line:
                 lines_to_copy.append(__UpperCAmelCase      )

           remove(__UpperCAmelCase      )

         replace_in_files(F"{directory}/to_replace_{lowercase_model_name}.py"      )
         os.rmdir(__UpperCAmelCase      )




def 				UpperCamelCase_(      lowerCamelCase_ )    ->						int:
    if not numbers:
        return 0

    if not isinstance(lowerCamelCase_							, (list, tuple) ) or not all(
        isinstance(lowerCamelCase_							, lowerCamelCase_ ) for number in numbers ):
        raise ValueError('numbers must be an iterable of integers' )

    _lowercase       :							int      		=		numbers[0]

    for i in range(1							, len(lowerCamelCase_ ) ):
        # update the maximum and minimum subarray products
        _lowercase       :							Union[str, Any]      		=		numbers[i]
        if number < 0:
            _lowercase		,				_lowercase       :							Any      		=		min_till_now, max_till_now
        _lowercase       :							Union[str, Any]      		=		max(lowerCamelCase_							, max_till_now * number )
        _lowercase       :							Union[str, Any]      		=		min(lowerCamelCase_							, min_till_now * number )

        # update the maximum product found till now
        _lowercase       :							Optional[Any]      		=		max(lowerCamelCase_							, lowerCamelCase_ )

    return max_prod


