


'''simple docstring'''






from argparse import ArgumentParser

from . import BaseTransformersCLICommand







def 				UpperCamelCase_			(    A__					:   Union[str, Any]					):
  '''simple docstring'''





  return DownloadCommand(args.model							,    args.cache_dir							,    args.force							,    args.trust_remote_code					)






class    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    @staticmethod
    def __lowercase   (   lowerCamelCase    :  ArgumentParser		)   ->  List[Any]:
      lowerCAmelCase_			:      List[Any]			=   parser.add_parser("""download"""		)
      download_parser.add_argument(
          """--cache-dir"""    ,						type=lowerCamelCase    ,						default=lowerCamelCase    ,						help="""Path to location to store the models"""		)
      download_parser.add_argument(
          """--force"""    ,						action="""store_true"""    ,						help="""Force the model to be download even if already in cache-dir"""		)
      download_parser.add_argument(
          """--trust-remote-code"""    ,						action="""store_true"""    ,						help="""Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine"""    ,						)
      download_parser.add_argument("""model"""    ,						type=lowerCamelCase    ,						help="""Name of the model to download"""		)
      download_parser.set_defaults(func=lowerCamelCase		)

    def __init__(   self    :  Union[str, Any]    ,						lowerCamelCase    :  str    ,						lowerCamelCase    :  str    ,						lowerCamelCase    :  bool    ,						lowerCamelCase    :  bool		)   ->  Optional[Any]:
      lowerCAmelCase_			:      Dict			=   model
      lowerCAmelCase_			:      List[Any]			=   cache
      lowerCAmelCase_			:      Tuple			=   force
      lowerCAmelCase_			:      List[str]			=   trust_remote_code





    def __lowercase   (   self    :  List[str]		)   ->  int:
      from ..models.auto import AutoModel, AutoTokenizer

      AutoModel.from_pretrained(
          self._model    ,						cache_dir=self._cache    ,						force_download=self._force    ,						trust_remote_code=self._trust_remote_code		)
      AutoTokenizer.from_pretrained(
          self._model    ,						cache_dir=self._cache    ,						force_download=self._force    ,						trust_remote_code=self._trust_remote_code		)







'''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					:  List[Any]											=      True
except ImportError:
  __A					:  int											=      False

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







def 				UpperCamelCase_			(    A__					:   Namespace					):
  '''simple docstring'''





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






class    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    @staticmethod
    def __lowercase   (   lowerCamelCase    :  ArgumentParser		)   ->  int:
      lowerCAmelCase_			:      Optional[int]			=   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    :  List[str]    ,						lowerCamelCase    :  bool    ,						lowerCamelCase    :  str    ,						lowerCamelCase    :  Any=None    ,						*lowerCamelCase    :  List[str]		)   ->  Optional[Any]:
      lowerCAmelCase_			:      int			=   testing
      lowerCAmelCase_			:      Union[str, Any]			=   testing_file
      lowerCAmelCase_			:      Tuple			=   path





    def __lowercase   (   self    :  Tuple		)   ->  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
      lowerCAmelCase_			:      int			=   [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."""		)

      lowerCAmelCase_			:      List[Any]			=   (
          Path(lowerCamelCase		).parent.parent.parent.parent if self._path is None else Path(self._path		).parent.parent
      )
      lowerCAmelCase_			:      Dict			=   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:
          lowerCAmelCase_			:      Tuple			=   json.load(lowerCamelCase		)

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

      lowerCAmelCase_			:      List[str]			=   [directory for directory in os.listdir() if """cookiecutter-template-""" in directory[:22]][0]

      # Retrieve configuration
      with open(directory + """/configuration.json"""    ,						"""r"""		) as configuration_file:
        lowerCAmelCase_			:      Tuple			=   json.load(lowerCamelCase		)

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

      lowerCAmelCase_			:      Dict			=   """PyTorch""" in generate_tensorflow_pytorch_and_flax
      lowerCAmelCase_			:      Optional[int]			=   """TensorFlow""" in generate_tensorflow_pytorch_and_flax
      lowerCAmelCase_			:      List[str]			=   """Flax""" in generate_tensorflow_pytorch_and_flax

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

              lowerCAmelCase_			:      Dict			=   []
            elif "# Replace with" in line and "##" not in line:
              lowerCAmelCase_			:      int			=   []
            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		)



