






import argparse

from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging


logging.set_verbosity_info()





def 					lowercase_ (    __snake_case     :							int	,	__snake_case     :							Tuple	,	__snake_case     :							str	,	__snake_case     :							int      )     -> Dict:





				'''simple docstring'''


				snake_case__      :Tuple         =   BigBirdConfig.from_json_file(__snake_case      )
				print(F'Building PyTorch model from configuration: {config}'      )

				if is_trivia_qa:
								snake_case__      :Union[str, Any]         =   BigBirdForQuestionAnswering(__snake_case      )
				else:
								snake_case__      :List[str]         =   BigBirdForPreTraining(__snake_case      )

				# Load weights from tf checkpoint
				load_tf_weights_in_big_bird(__snake_case	,	__snake_case	,	is_trivia_qa=__snake_case      )

				# Save pytorch-model
				print(F'Save PyTorch model to {pytorch_dump_path}'      )
				model.save_pretrained(__snake_case      )


if __name__ == "__main__":
	__UpperCAmelCase							:   Optional[int]							=  argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    "--tf_checkpoint_path", default=None, type=str, required=True, help="Path to the TensorFlow checkpoint path."
	)
	parser.add_argument(
	    "--big_bird_config_file",
	    default=None,
	    type=str,
	    required=True,
	    help=(
	        "The config json file corresponding to the pre-trained BERT model. \n"
	        "This specifies the model architecture."
	    ),
	)
	parser.add_argument(
	    "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
	)
	parser.add_argument(
	    "--is_trivia_qa", action="store_true", help="Whether to convert a model with a trivia_qa head."
	)
	__UpperCAmelCase							:   str							=  parser.parse_args()
	convert_tf_checkpoint_to_pytorch(
	    args.tf_checkpoint_path, args.big_bird_config_file, args.pytorch_dump_path, args.is_trivia_qa
	)







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

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





def 					lowercase_ (    __snake_case     :							Namespace      )     -> Dict:





				'''simple docstring'''


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


class 					_snake_case						(			_A ):






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






	def __init__(		self					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase=None					,*UpperCamelCase       )						->    Any:
					snake_case__      :Union[str, Any]         =   testing
					snake_case__      :Union[str, Any]         =   testing_file
					snake_case__      :List[str]         =   path






	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					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__      :Tuple         =   [directory for directory in os.listdir() if "cookiecutter-template-" == directory[:22]]
					if len(UpperCamelCase       ) > 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__      :str         =   (
					    Path(UpperCamelCase       ).parent.parent.parent.parent if self._path is None else Path(self._path       ).parent.parent
					)
					snake_case__      :Tuple         =   path_to_transformer_root / "templates" / "adding_a_new_model"

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

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

					snake_case__      :List[Any]         =   [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__      :Dict         =   json.load(UpperCamelCase       )

					snake_case__      :Optional[Any]         =   configuration["lowercase_modelname"]
					snake_case__      :List[Any]         =   configuration["generate_tensorflow_pytorch_and_flax"]
					os.remove(f'{directory}/configuration.json'       )

					snake_case__      :Any         =   "PyTorch" in generate_tensorflow_pytorch_and_flax
					snake_case__      :Any         =   "TensorFlow" in generate_tensorflow_pytorch_and_flax
					snake_case__      :Any         =   "Flax" in generate_tensorflow_pytorch_and_flax

					snake_case__      :Dict         =   f'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
					os.makedirs(UpperCamelCase					,exist_ok=UpperCamelCase       )
					os.makedirs(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}'					,exist_ok=UpperCamelCase       )

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

					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
									snake_case__    ,						snake_case__      :Optional[Any]         =   mkstemp()
									snake_case__      :Optional[Any]         =   False
									with fdopen(UpperCamelCase					,"w"       ) as new_file:
													with open(UpperCamelCase       ) as old_file:
																	for line in old_file:
																					new_file.write(UpperCamelCase       )
																					if line_to_copy_below in line:
																									snake_case__      :Optional[Any]         =   True
																									for line_to_copy in lines_to_copy:
																													new_file.write(UpperCamelCase       )

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

					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(UpperCamelCase       ) as datafile:
													snake_case__      :int         =   []
													snake_case__      :Optional[int]         =   False
													snake_case__      :List[str]         =   False
													for line in datafile:
																	if "# To replace in: " in line and "##" not in line:
																					snake_case__      :Optional[Any]         =   line.split("\""       )[1]
																					snake_case__      :Tuple         =   skip_units(UpperCamelCase       )
																	elif "# Below: " in line and "##" not in line:
																					snake_case__      :Optional[Any]         =   line.split("\""       )[1]
																					snake_case__      :List[str]         =   skip_units(UpperCamelCase       )
																	elif "# End." in line and "##" not in line:
																					if not skip_file and not skip_snippet:
																									replace(UpperCamelCase					,UpperCamelCase					,UpperCamelCase       )

																					snake_case__      :Tuple         =   []
																	elif "# Replace with" in line and "##" not in line:
																					snake_case__      :Optional[Any]         =   []
																	elif "##" not in line:
																					lines_to_copy.append(UpperCamelCase       )

									remove(UpperCamelCase       )

					replace_in_files(f'{directory}/to_replace_{lowercase_model_name}.py'       )
					os.rmdir(UpperCamelCase       )