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

  SCREAMING_SNAKE_CASE			:						Dict				  =		True
except ImportError:
  SCREAMING_SNAKE_CASE			:						List[Any]				  =		False

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



def 	__A		(      _A       ):



 """simple docstring"""


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






class  A_			(							a_			):

  @staticmethod
  def 		_UpperCAmelCase (		__SCREAMING_SNAKE_CASE			:   ArgumentParser							):
   __a							=	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=__SCREAMING_SNAKE_CASE  ,				help="Configuration file on which to run."							)
   add_new_model_parser.add_argument(
       "--path"  ,				type=__SCREAMING_SNAKE_CASE  ,				help="Path to cookiecutter. Should only be used for testing purposes."							)
   add_new_model_parser.set_defaults(func=__SCREAMING_SNAKE_CASE							)

  def __init__(		self			:   Optional[Any]  ,				__SCREAMING_SNAKE_CASE			:   bool  ,				__SCREAMING_SNAKE_CASE			:   str  ,				__SCREAMING_SNAKE_CASE			:   Any=None  ,				*__SCREAMING_SNAKE_CASE			:   Any							):
   __a							=	testing
   __a							=	testing_file
   __a							=	path

  def 		_UpperCAmelCase (		self			:   Dict							):
   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
   __a							=	[directory for directory in os.listdir() if "cookiecutter-template-" == directory[:22]]
   if len(__SCREAMING_SNAKE_CASE							) > 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."							)

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

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

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

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

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

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

   __a							=	"PyTorch" in generate_tensorflow_pytorch_and_flax
   __a							=	"TensorFlow" in generate_tensorflow_pytorch_and_flax
   __a							=	"Flax" in generate_tensorflow_pytorch_and_flax

   __a							=	f"""{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}"""
   os.makedirs(__SCREAMING_SNAKE_CASE  ,				exist_ok=__SCREAMING_SNAKE_CASE							)
   os.makedirs(f"""{path_to_transformer_root}/tests/models/{lowercase_model_name}"""  ,				exist_ok=__SCREAMING_SNAKE_CASE							)

   # 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(__SCREAMING_SNAKE_CASE			:   List[str]							):
    with open(__SCREAMING_SNAKE_CASE  ,				"r"							) as f:
     __a							=	f.readlines()
    with open(__SCREAMING_SNAKE_CASE  ,				"w"							) as f:
     for line in lines:
      if "# Copied from transformers." not in line:
       f.write(__SCREAMING_SNAKE_CASE							)

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

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

   def skip_units(__SCREAMING_SNAKE_CASE			:   List[Any]							):
    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(__SCREAMING_SNAKE_CASE			:   Union[str, Any]							):
    with open(__SCREAMING_SNAKE_CASE							) as datafile:
     __a							=	[]
     __a							=	False
     __a							=	False
     for line in datafile:
      if "# To replace in: " in line and "##" not in line:
       __a							=	line.split("\""							)[1]
       __a							=	skip_units(__SCREAMING_SNAKE_CASE							)
      elif "# Below: " in line and "##" not in line:
       __a							=	line.split("\""							)[1]
       __a							=	skip_units(__SCREAMING_SNAKE_CASE							)
      elif "# End." in line and "##" not in line:
       if not skip_file and not skip_snippet:
        replace(__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE							)

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

    remove(__SCREAMING_SNAKE_CASE							)

   replace_in_files(f"""{directory}/to_replace_{lowercase_model_name}.py"""							)
   os.rmdir(__SCREAMING_SNAKE_CASE							)



from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE			:						Optional[int]				  =		{
    """configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
    """feature_extraction_mctct""": ["""MCTCTFeatureExtractor"""],
    """processing_mctct""": ["""MCTCTProcessor"""],
}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE			:						Optional[Any]				  =		[
      """MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """MCTCTForCTC""",
      """MCTCTModel""",
      """MCTCTPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig
  from .feature_extraction_mctct import MCTCTFeatureExtractor
  from .processing_mctct import MCTCTProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mctct import MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST, MCTCTForCTC, MCTCTModel, MCTCTPreTrainedModel

else:
  import sys

  SCREAMING_SNAKE_CASE			:						Union[str, Any]				  =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


