
'''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

						_snake_case				:   Tuple     =				True
except ImportError:
						_snake_case				:   Optional[int]     =				False

_snake_case				:   Optional[int]     =				logging.get_logger(__name__)  # pylint: disable=invalid-name



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str  ):
						return AddNewModelCommand(args.testing	,			args.testing_file	,			path=args.path  )




class 			lowerCAmelCase (				__lowerCamelCase			):




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




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase					,						UpperCamelCase=None					,						*UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= testing
								_SCREAMING_SNAKE_CASE				= testing_file
								_SCREAMING_SNAKE_CASE				= path




		def     lowercase       (				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
								_SCREAMING_SNAKE_CASE				= [directory for directory in os.listdir() if "cookiecutter-template-" == directory[:22]]
								if len(a_      ) > 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."      )

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

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

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

								_SCREAMING_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:
														_SCREAMING_SNAKE_CASE				= json.load(a_      )

								_SCREAMING_SNAKE_CASE				= configuration["lowercase_modelname"]
								_SCREAMING_SNAKE_CASE				= configuration["generate_tensorflow_pytorch_and_flax"]
								os.remove(F'{directory}/configuration.json'      )

								_SCREAMING_SNAKE_CASE				= "PyTorch" in generate_tensorflow_pytorch_and_flax
								_SCREAMING_SNAKE_CASE				= "TensorFlow" in generate_tensorflow_pytorch_and_flax
								_SCREAMING_SNAKE_CASE				= "Flax" in generate_tensorflow_pytorch_and_flax

								_SCREAMING_SNAKE_CASE				= F'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
								os.makedirs(a_					,						exist_ok=a_      )
								os.makedirs(F'{path_to_transformer_root}/tests/models/{lowercase_model_name}'					,						exist_ok=a_      )

								# 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(UpperCamelCase      ):
														with open(a_					,						"r"      ) as f:
																				_SCREAMING_SNAKE_CASE				= f.readlines()
														with open(a_					,						"w"      ) as f:
																				for line in lines:
																										if "# Copied from transformers." not in line:
																																f.write(a_      )

								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(UpperCamelCase					,						UpperCamelCase					,						UpperCamelCase      ):
														# Create temp file
														_SCREAMING_SNAKE_CASE				= mkstemp()
														_SCREAMING_SNAKE_CASE				= False
														with fdopen(a_					,						"w"      ) as new_file:
																				with open(a_      ) as old_file:
																										for line in old_file:
																																new_file.write(a_      )
																																if line_to_copy_below in line:
																																						_SCREAMING_SNAKE_CASE				= True
																																						for line_to_copy in lines_to_copy:
																																												new_file.write(a_      )

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

								def skip_units(UpperCamelCase      ):
														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(UpperCamelCase      ):
														with open(a_      ) as datafile:
																				_SCREAMING_SNAKE_CASE				= []
																				_SCREAMING_SNAKE_CASE				= False
																				_SCREAMING_SNAKE_CASE				= False
																				for line in datafile:
																										if "# To replace in: " in line and "##" not in line:
																																_SCREAMING_SNAKE_CASE				= line.split("\""      )[1]
																																_SCREAMING_SNAKE_CASE				= skip_units(a_      )
																										elif "# Below: " in line and "##" not in line:
																																_SCREAMING_SNAKE_CASE				= line.split("\""      )[1]
																																_SCREAMING_SNAKE_CASE				= skip_units(a_      )
																										elif "# End." in line and "##" not in line:
																																if not skip_file and not skip_snippet:
																																						replace(a_					,						a_					,						a_      )

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

														remove(a_      )

								replace_in_files(F'{directory}/to_replace_{lowercase_model_name}.py'      )
								os.rmdir(a_      )

'''simple docstring'''







from typing import TYPE_CHECKING

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


_snake_case				:   Optional[Any]     =				{
    """configuration_rag""": ["""RagConfig"""],
    """retrieval_rag""": ["""RagRetriever"""],
    """tokenization_rag""": ["""RagTokenizer"""],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case				:   int     =				[
						    """RagModel""",
						    """RagPreTrainedModel""",
						    """RagSequenceForGeneration""",
						    """RagTokenForGeneration""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case				:   Dict     =				[
						    """TFRagModel""",
						    """TFRagPreTrainedModel""",
						    """TFRagSequenceForGeneration""",
						    """TFRagTokenForGeneration""",
						]


if TYPE_CHECKING:
						from .configuration_rag import RagConfig
						from .retrieval_rag import RagRetriever
						from .tokenization_rag import RagTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_rag import (
												    TFRagModel,
												    TFRagPreTrainedModel,
												    TFRagSequenceForGeneration,
												    TFRagTokenForGeneration,
												)

else:
						import sys

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