
'''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

						lowercase__						       =      True
except ImportError:
						lowercase__						       =      False

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




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__			)  ->							int:


		'''simple docstring'''


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






class 	snake_case__       (      __SCREAMING_SNAKE_CASE					):







		"""simple docstring"""

		@staticmethod
		def       lowerCAmelCase				(      UpperCamelCase__				:			ArgumentParser      )						->			Optional[Any]:






				"""simple docstring"""







				snake_case  :       List[Any]     			=						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				:			Union[str, Any]  ,	UpperCamelCase__				:			bool  ,	UpperCamelCase__				:			str  ,	UpperCamelCase__				:			Any=None  ,	*UpperCamelCase__				:			Optional[Any]      )						->			List[str]:






				"""simple docstring"""







				snake_case  :       Optional[int]     			=						testing
				snake_case  :       Optional[Any]     			=						testing_file
				snake_case  :       int     			=						path



		def       lowerCAmelCase				(      self				:			List[str]      )						->			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
				snake_case  :       Optional[Any]     			=						[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  :       List[Any]     			=						(
				    Path(UpperCamelCase__      ).parent.parent.parent.parent if self._path is None else Path(self._path      ).parent.parent
				)
				snake_case  :       List[str]     			=						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  :       Tuple     			=						json.load(UpperCamelCase__      )

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

				snake_case  :       Tuple     			=						[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  :       List[Any]     			=						json.load(UpperCamelCase__      )

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

				snake_case  :       Dict     			=						'''PyTorch''' in generate_tensorflow_pytorch_and_flax
				snake_case  :       Any     			=						'''TensorFlow''' in generate_tensorflow_pytorch_and_flax
				snake_case  :       Optional[int]     			=						'''Flax''' in generate_tensorflow_pytorch_and_flax

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




'''simple docstring'''
from typing import TYPE_CHECKING

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


lowercase__						       =      {
    "configuration_poolformer": [
        "POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "PoolFormerConfig",
        "PoolFormerOnnxConfig",
    ]
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowercase__						       =      ["PoolFormerFeatureExtractor"]
						lowercase__						       =      ["PoolFormerImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowercase__						       =      [
						    "POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "PoolFormerForImageClassification",
						    "PoolFormerModel",
						    "PoolFormerPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_poolformer import (
						    POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    PoolFormerConfig,
						    PoolFormerOnnxConfig,
						)

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_poolformer import PoolFormerFeatureExtractor
												from .image_processing_poolformer import PoolFormerImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_poolformer import (
												    POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    PoolFormerForImageClassification,
												    PoolFormerModel,
												    PoolFormerPreTrainedModel,
												)


else:
						import sys

						lowercase__						       =      _LazyModule(__name__, globals()["__file__"], _import_structure)


