



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[Any]   	=			False

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

def   _lowerCAmelCase   (						A__	):
      return AddNewModelCommand(args.testing						,  args.testing_file						,  path=args.path	)



class       UpperCAmelCase__(							lowerCamelCase	):

   '''simple docstring'''




   @staticmethod
   def 			UpperCAmelCase		(						lowerCAmelCase  :			ArgumentParser)	->				List[str]:




         """simple docstring"""

         lowercase__     =  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  :			Union[str, Any]			,				lowerCAmelCase  :			bool			,				lowerCAmelCase  :			str			,				lowerCAmelCase  :			List[Any]=None			,				*lowerCAmelCase  :			int)	->				int:




         """simple docstring"""

         lowercase__     =  testing
         lowercase__     =  testing_file
         lowercase__     =  path



   def 			UpperCAmelCase		(						self  :			Optional[int])	->				Optional[Any]:




         """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
         lowercase__     =  [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.')

         lowercase__     =  (
             Path(lowerCAmelCase).parent.parent.parent.parent if self._path is None else Path(self._path).parent.parent
         )
         lowercase__     =  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:
                     lowercase__     =  json.load(lowerCAmelCase)

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

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

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

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

         lowercase__     =  'PyTorch' in generate_tensorflow_pytorch_and_flax
         lowercase__     =  'TensorFlow' in generate_tensorflow_pytorch_and_flax
         lowercase__     =  'Flax' in generate_tensorflow_pytorch_and_flax

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

                                 lowercase__     =  []
                           elif "# Replace with" in line and "##" not in line:
                                 lowercase__     =  []
                           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_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


a__      :				Optional[int]   	=			{
    "configuration_blenderbot": [
        "BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotConfig",
        "BlenderbotOnnxConfig",
    ],
    "tokenization_blenderbot": ["BlenderbotTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a__      :				Any   	=			["BlenderbotTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a__      :				Dict   	=			[
           "BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "BlenderbotForCausalLM",
           "BlenderbotForConditionalGeneration",
           "BlenderbotModel",
           "BlenderbotPreTrainedModel",
       ]


try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a__      :				List[str]   	=			[
           "TFBlenderbotForConditionalGeneration",
           "TFBlenderbotModel",
           "TFBlenderbotPreTrainedModel",
       ]


try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a__      :				int   	=			[
           "FlaxBlenderbotForConditionalGeneration",
           "FlaxBlenderbotModel",
           "FlaxBlenderbotPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_blenderbot import (
           BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
           BlenderbotConfig,
           BlenderbotOnnxConfig,
       )
       from .tokenization_blenderbot import BlenderbotTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_blenderbot import (
                  BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  BlenderbotForCausalLM,
                  BlenderbotForConditionalGeneration,
                  BlenderbotModel,
                  BlenderbotPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_blenderbot import (
                  TFBlenderbotForConditionalGeneration,
                  TFBlenderbotModel,
                  TFBlenderbotPreTrainedModel,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_blenderbot import (
                  FlaxBlenderbotForConditionalGeneration,
                  FlaxBlenderbotModel,
                  FlaxBlenderbotPreTrainedModel,
              )

else:
       import sys

       a__      :				Optional[Any]   	=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
