
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 		lowercase_    (     A__	)							->							Dict:
    """simple docstring"""

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







class   lowerCamelCase	(						A_						):





     @staticmethod
     def 	UpperCAmelCase(_A   :					ArgumentParser     )		->		Union[str, Any]:
         snake_case				  =      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=_A       ,					help="Configuration file on which to run."     )
         add_new_model_parser.add_argument(
             "--path"       ,					type=_A       ,					help="Path to cookiecutter. Should only be used for testing purposes."     )
         add_new_model_parser.set_defaults(func=_A     )





     def __init__(self   :					int       ,					_A   :					bool       ,					_A   :					str       ,					_A   :					Optional[Any]=None       ,					*_A   :					Tuple     )		->		Optional[int]:
         snake_case				  =      testing
         snake_case				  =      testing_file
         snake_case				  =      path





     def 	UpperCAmelCase(self   :					Any     )		->		Any:
         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
         snake_case				  =      [directory for directory in os.listdir() if "cookiecutter-template-" == directory[:2_2]]
         if len(_A     ) > 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."     )

         snake_case				  =      (
             Path(_A     ).parent.parent.parent.parent if self._path is None else Path(self._path     ).parent.parent
         )
         snake_case				  =      path_to_transformer_root / "templates" / "adding_a_new_model"

         # Execute cookiecutter
         if not self._testing:
             cookiecutter(str(_A     )     )
         else:
             with open(self._testing_file       ,					"r"     ) as configuration_file:
                 snake_case				  =      json.load(_A     )

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

         snake_case				  =      [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:
             snake_case				  =      json.load(_A     )

         snake_case				  =      configuration["lowercase_modelname"]
         snake_case				  =      configuration["generate_tensorflow_pytorch_and_flax"]
         os.remove(f'{directory}/configuration.json'     )

         snake_case				  =      "PyTorch" in generate_tensorflow_pytorch_and_flax
         snake_case				  =      "TensorFlow" in generate_tensorflow_pytorch_and_flax
         snake_case				  =      "Flax" in generate_tensorflow_pytorch_and_flax

         snake_case				  =      f'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
         os.makedirs(_A       ,					exist_ok=_A     )
         os.makedirs(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}'       ,					exist_ok=_A     )

         # 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(_A   :					str     ):
             with open(_A       ,					"r"     ) as f:
                 snake_case				  =      f.readlines()
             with open(_A       ,					"w"     ) as f:
                 for line in lines:
                     if "# Copied from transformers." not in line:
                         f.write(_A     )

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

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

         def skip_units(_A   :					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(_A   :					Optional[int]     ):
             with open(_A     ) as datafile:
                 snake_case				  =      []
                 snake_case				  =      False
                 snake_case				  =      False
                 for line in datafile:
                     if "# To replace in: " in line and "##" not in line:
                         snake_case				  =      line.split("\""     )[1]
                         snake_case				  =      skip_units(_A     )
                     elif "# Below: " in line and "##" not in line:
                         snake_case				  =      line.split("\""     )[1]
                         snake_case				  =      skip_units(_A     )
                     elif "# End." in line and "##" not in line:
                         if not skip_file and not skip_snippet:
                             replace(_A       ,					_A       ,					_A     )

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

             remove(_A     )

         replace_in_files(f'{directory}/to_replace_{lowercase_model_name}.py'     )
         os.rmdir(_A     )



import os

# Precomputes a list of the 100 first triangular numbers
_A						      =				[int(0.5 * n * (n + 1)) for n in range(1, 1_01)]



def 		lowercase_    (     )							->							Tuple:
    """simple docstring"""

    snake_case				  =      os.path.dirname(os.path.realpath(A__	)	)
    snake_case				  =      os.path.join(A__				,	"words.txt"	)

    snake_case				  =      ""
    with open(A__	) as f:
        snake_case				  =      f.readline()

    snake_case				  =      [word.strip("\""	) for word in words.strip("\r\n"	).split(","	)]
    snake_case				  =      [
        word
        for word in [sum(ord(A__	) - 64 for x in word	) for word in words]
        if word in TRIANGULAR_NUMBERS
    ]
    return len(A__	)


if __name__ == "__main__":
   print(solution())

