"""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

    __UpperCamelCase									=			True
except ImportError:
    __UpperCamelCase									=			False

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







def 					UpperCAmelCase    (		UpperCAmelCase					)				->      Optional[int]:
     return AddNewModelCommand(args.testing						,					args.testing_file						,					path=args.path					)




class  UpperCamelCase					(				lowerCAmelCase__   ):







       @staticmethod
       def 		a_						( lowerCAmelCase__)      ->      Optional[int]:
            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=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__)      ->      int:
            snake_case_					       =					testing
            snake_case_					       =					testing_file
            snake_case_					       =					path







       def 		a_						( self)      ->      int:
            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[: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.')

            snake_case_					       =					(
                Path(lowerCAmelCase__).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(lowerCAmelCase__))
            else:
                 with open(self._testing_file,							'r') as configuration_file:
                      snake_case_					       =					json.load(lowerCAmelCase__)

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

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

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

            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(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:
                      snake_case_					       =					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
                 snake_case_       ,	snake_case_					       =					mkstemp()
                 snake_case_					       =					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:
                                     snake_case_					       =					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:
                      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(lowerCAmelCase__)
                           elif "# Below: " in line and "##" not in line:
                                snake_case_					       =					line.split('"')[1]
                                snake_case_					       =					skip_units(lowerCAmelCase__)
                           elif "# End." in line and "##" not in line:
                                if not skip_file and not skip_snippet:
                                     replace(lowerCAmelCase__,							lowerCAmelCase__,							lowerCAmelCase__)

                                snake_case_					       =					[]
                           elif "# Replace with" in line and "##" not in line:
                                snake_case_					       =					[]
                           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__)




from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__				=		{'''configuration_mmbt''': ['''MMBTConfig''']}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a__				=		['''MMBTForClassification''', '''MMBTModel''', '''ModalEmbeddings''']


if TYPE_CHECKING:
			from .configuration_mmbt import MMBTConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
			import sys

			a__				=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



