






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_						:						Optional[int]						      =					True
except ImportError:
   A_						:						List[str]						      =					False

A_						:						Tuple						      =					logging.get_logger(__name__)  # pylint: disable=invalid-name

def     snake_case   (UpperCAmelCase__    )			->							str:
  return AddNewModelCommand(args.testing      ,       args.testing_file      ,       path=args.path    )




class 							_lowerCAmelCase(			UpperCAmelCase_   ):





       """simple docstring"""







       @staticmethod
       def      _a       (   _lowerCamelCase				):
         UpperCamelCase_:   List[str]        =							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    ,     _lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase=None    ,     *_lowerCamelCase				):
         UpperCamelCase_:   List[str]        =							testing
         UpperCamelCase_:   str        =							testing_file
         UpperCamelCase_:   str        =							path





       def      _a       (   self				):
         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
         UpperCamelCase_:   Tuple        =							[directory for directory in os.listdir() if 'cookiecutter-template-' == directory[:2_2]]
         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.'				)

         UpperCamelCase_:   List[Any]        =							(
             Path(_lowerCamelCase				).parent.parent.parent.parent if self._path is None else Path(self._path				).parent.parent
         )
         UpperCamelCase_:   Optional[int]        =							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:
             UpperCamelCase_:   Optional[Any]        =							json.load(_lowerCamelCase				)

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

         UpperCamelCase_:   Optional[Any]        =							[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:
           UpperCamelCase_:   Tuple        =							json.load(_lowerCamelCase				)

         UpperCamelCase_:   Tuple        =							configuration['lowercase_modelname']
         UpperCamelCase_:   Tuple        =							configuration['generate_tensorflow_pytorch_and_flax']
         os.remove(f'''{directory}/configuration.json'''				)

         UpperCamelCase_:   Any        =							'PyTorch' in generate_tensorflow_pytorch_and_flax
         UpperCamelCase_:   int        =							'TensorFlow' in generate_tensorflow_pytorch_and_flax
         UpperCamelCase_:   str        =							'Flax' in generate_tensorflow_pytorch_and_flax

         UpperCamelCase_:   Optional[int]        =							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(_lowerCamelCase				):
           with open(_lowerCamelCase    ,     'r'				) as f:
             UpperCamelCase_:   Optional[int]        =							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(_lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase				):
           # Create temp file
           UpperCamelCase_ ,UpperCamelCase_:   Dict        =							mkstemp()
           UpperCamelCase_:   Optional[Any]        =							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:
                   UpperCamelCase_:   int        =							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(_lowerCamelCase				):
           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(_lowerCamelCase				):
           with open(_lowerCamelCase				) as datafile:
             UpperCamelCase_:   Any        =							[]
             UpperCamelCase_:   Optional[Any]        =							False
             UpperCamelCase_:   Tuple        =							False
             for line in datafile:
               if "# To replace in: " in line and "##" not in line:
                 UpperCamelCase_:   Optional[Any]        =							line.split('"'				)[1]
                 UpperCamelCase_:   Union[str, Any]        =							skip_units(_lowerCamelCase				)
               elif "# Below: " in line and "##" not in line:
                 UpperCamelCase_:   str        =							line.split('"'				)[1]
                 UpperCamelCase_:   List[str]        =							skip_units(_lowerCamelCase				)
               elif "# End." in line and "##" not in line:
                 if not skip_file and not skip_snippet:
                   replace(_lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase				)

                 UpperCamelCase_:   Optional[Any]        =							[]
               elif "# Replace with" in line and "##" not in line:
                 UpperCamelCase_:   Any        =							[]
               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				)



"""simple docstring"""




import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format




class 			__snake_case   :
							__a					 =       None




							def   __a   (     self:    int   ):
										__lowerCamelCase          =      self.feature_extraction_class(**self.feat_extract_dict   )
										__lowerCamelCase          =      json.loads(feat_extract.to_json_string()   )
										for key, value in self.feat_extract_dict.items():
													self.assertEqual(obj[key]     ,							A_   )




							def   __a   (     self:    List[str]   ):
										__lowerCamelCase          =      self.feature_extraction_class(**self.feat_extract_dict   )

										with tempfile.TemporaryDirectory() as tmpdirname:
													__lowerCamelCase          =      os.path.join(A_     ,							"""feat_extract.json"""   )
													feat_extract_first.to_json_file(A_   )
													__lowerCamelCase          =      self.feature_extraction_class.from_json_file(A_   )

										self.assertEqual(feat_extract_second.to_dict()     ,							feat_extract_first.to_dict()   )




							def   __a   (     self:    Optional[Any]   ):
										__lowerCamelCase          =      self.feature_extraction_class(**self.feat_extract_dict   )

										with tempfile.TemporaryDirectory() as tmpdirname:
													__lowerCamelCase          =      feat_extract_first.save_pretrained(A_   )[0]
													check_json_file_has_correct_format(A_   )
													__lowerCamelCase          =      self.feature_extraction_class.from_pretrained(A_   )

										self.assertEqual(feat_extract_second.to_dict()     ,							feat_extract_first.to_dict()   )




							def   __a   (     self:    List[Any]   ):
										__lowerCamelCase          =      self.feature_extraction_class()
										self.assertIsNotNone(A_   )




