






'''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    	=   True
except ImportError:
      __A    	=   False

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




def        _SCREAMING_SNAKE_CASE  (				A  :       Namespace  )    -> str:







   """simple docstring"""
   return AddNewModelCommand(args.testing  ,		args.testing_file  ,		path=args.path  )





class a_    (    UpperCamelCase_							):







   @staticmethod
   def     SCREAMING_SNAKE_CASE__					(__a)			->      Union[str, Any]:
      """simple docstring"""






      __snake_case				:      Optional[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=__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					,   __a					,   __a					,   __a=None					,   *__a)			->      int:
      """simple docstring"""






      __snake_case				:      Optional[int]     							= testing
      __snake_case				:      List[str]     							= testing_file
      __snake_case				:      Optional[Any]     							= path







   def     SCREAMING_SNAKE_CASE__					(self)			->      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				:      Any     							= [directory for directory in os.listdir() if 'cookiecutter-template-' == directory[:2_2]]
      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.')

      __snake_case				:      Union[str, Any]     							= (
          Path(__a).parent.parent.parent.parent if self._path is None else Path(self._path).parent.parent
      )
      __snake_case				:      str     							= 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:
            __snake_case				:      List[Any]     							= json.load(__a)

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

      __snake_case				:      Union[str, Any]     							= [directory for directory in os.listdir() if 'cookiecutter-template-' in directory[:2_2]][0]

      # Retrieve configuration
      with open(directory + '/configuration.json'					,   'r') as configuration_file:
         __snake_case				:      List[str]     							= json.load(__a)

      __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				:      str     							= 'PyTorch' in generate_tensorflow_pytorch_and_flax
      __snake_case				:      str     							= 'TensorFlow' in generate_tensorflow_pytorch_and_flax
      __snake_case				:      Any     							= 'Flax' in generate_tensorflow_pytorch_and_flax

      __snake_case				:      Optional[Any]     							= 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(__a):
         with open(__a					,   'r') as f:
            __snake_case				:      Optional[int]     							= 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(__a					,   __a					,   __a):
         # Create temp file
         __snake_case							,__snake_case				:      Any     							= mkstemp()
         __snake_case				:      Any     							= 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:
                     __snake_case				:      Union[str, Any]     							= 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(__a):
         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(__a):
         with open(__a) as datafile:
            __snake_case				:      Optional[Any]     							= []
            __snake_case				:      Optional[int]     							= False
            __snake_case				:      List[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				:      Dict     							= skip_units(__a)
               elif "# Below: " in line and "##" not in line:
                  __snake_case				:      Optional[Any]     							= line.split('"')[1]
                  __snake_case				:      Union[str, Any]     							= skip_units(__a)
               elif "# End." in line and "##" not in line:
                  if not skip_file and not skip_snippet:
                     replace(__a					,   __a					,   __a)

                  __snake_case				:      List[Any]     							= []
               elif "# Replace with" in line and "##" not in line:
                  __snake_case				:      List[str]     							= []
               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'''






# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A    	=   {'''configuration_timm_backbone''': ['''TimmBackboneConfig''']}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __A    	=   ['''TimmBackbone''']


if TYPE_CHECKING:
      from .configuration_timm_backbone import TimmBackboneConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_timm_backbone import TimmBackbone

else:
      import sys

      __A    	=   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)