





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      :       Union[str, Any]									=  True
except ImportError:
    lowercase      :       List[str]									=  False

lowercase      :       List[str]									=  logging.get_logger(__name__)  # pylint: disable=invalid-name



def A_	(		A__				)  ->		Dict:
       return AddNewModelCommand(args.testing		,      args.testing_file		,      path=args.path				)





class  A__    (							__UpperCAmelCase	):




   """simple docstring"""



   @staticmethod
   def 							__lowercase		(					lowercase)			->						Union[str, Any]:







          '''simple docstring'''

          a__						:	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=lowercase					,  help='Configuration file on which to run.')
          add_new_model_parser.add_argument(
              '--path'					,  type=lowercase					,  help='Path to cookiecutter. Should only be used for testing purposes.')
          add_new_model_parser.set_defaults(func=lowercase)

   def __init__(					self					,  lowercase					,  lowercase					,  lowercase=None					,  *lowercase)			->						Union[str, Any]:







          '''simple docstring'''

          a__						:	Optional[int] =				testing
          a__						:	int =				testing_file
          a__						:	str =				path

   def 							__lowercase		(					self)			->						Optional[int]:







          '''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
          a__						:	List[Any] =				[directory for directory in os.listdir() if 'cookiecutter-template-' == directory[:22]]
          if len(lowercase) > 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__						:	Tuple =				(
              Path(lowercase).parent.parent.parent.parent if self._path is None else Path(self._path).parent.parent
          )
          a__						:	Optional[Any] =				path_to_transformer_root / 'templates' / 'adding_a_new_model'

          # Execute cookiecutter
          if not self._testing:
                 cookiecutter(str(lowercase))
          else:
                 with open(self._testing_file					,  'r') as configuration_file:
                        a__						:	Any =				json.load(lowercase)

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

          a__						:	str =				[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__						:	List[str] =				json.load(lowercase)

          a__						:	List[Any] =				configuration['lowercase_modelname']
          a__						:	List[str] =				configuration['generate_tensorflow_pytorch_and_flax']
          os.remove(F'{directory}/configuration.json')

          a__						:	List[Any] =				'PyTorch' in generate_tensorflow_pytorch_and_flax
          a__						:	Union[str, Any] =				'TensorFlow' in generate_tensorflow_pytorch_and_flax
          a__						:	List[Any] =				'Flax' in generate_tensorflow_pytorch_and_flax

          a__						:	List[str] =				F'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
          os.makedirs(lowercase					,  exist_ok=lowercase)
          os.makedirs(F'{path_to_transformer_root}/tests/models/{lowercase_model_name}'					,  exist_ok=lowercase)

          # 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(lowercase):
                 with open(lowercase					,  'r') as f:
                        a__						:	Optional[int] =				f.readlines()
                 with open(lowercase					,  'w') as f:
                        for line in lines:
                               if "# Copied from transformers." not in line:
                                      f.write(lowercase)

          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(lowercase					,  lowercase					,  lowercase):
                 # Create temp file
                 a__ ,							a__						:	Dict =				mkstemp()
                 a__						:	Dict =				False
                 with fdopen(lowercase					,  'w') as new_file:
                        with open(lowercase) as old_file:
                               for line in old_file:
                                      new_file.write(lowercase)
                                      if line_to_copy_below in line:
                                             a__						:	int =				True
                                             for line_to_copy in lines_to_copy:
                                                    new_file.write(lowercase)

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

          def skip_units(lowercase):
                 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(lowercase):
                 with open(lowercase) as datafile:
                        a__						:	Any =				[]
                        a__						:	List[Any] =				False
                        a__						:	str =				False
                        for line in datafile:
                               if "# To replace in: " in line and "##" not in line:
                                      a__						:	Dict =				line.split('"')[1]
                                      a__						:	Tuple =				skip_units(lowercase)
                               elif "# Below: " in line and "##" not in line:
                                      a__						:	Optional[int] =				line.split('"')[1]
                                      a__						:	Union[str, Any] =				skip_units(lowercase)
                               elif "# End." in line and "##" not in line:
                                      if not skip_file and not skip_snippet:
                                             replace(lowercase					,  lowercase					,  lowercase)

                                      a__						:	Optional[Any] =				[]
                               elif "# Replace with" in line and "##" not in line:
                                      a__						:	List[Any] =				[]
                               elif "##" not in line:
                                      lines_to_copy.append(lowercase)

                 remove(lowercase)

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









from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_torch_available():
    import torch

if is_torch_tpu_available(check_device=False):
    import torch_xla.core.xla_model as xm


lowercase      :       List[str]									=  logging.get_logger(__name__)





@dataclass
class  A__    (							__UpperCAmelCase	):




   """simple docstring"""



   __A   :				Optional[Any]         =  [
       '''no_inference''',
       '''no_cuda''',
       '''no_tpu''',
       '''no_speed''',
       '''no_memory''',
       '''no_env_print''',
       '''no_multi_process''',
   ]

   def __init__(					self					,  **lowercase)			->						Tuple:







          '''simple docstring'''

          for deprecated_arg in self.deprecated_args:
                 if deprecated_arg in kwargs:
                        a__						:	Union[str, Any] =				deprecated_arg[3:]
                        setattr(self					,  lowercase					,  not kwargs.pop(lowercase))
                        logger.warning(
                            F'{deprecated_arg} is depreciated. Please use --no_{positive_arg} or'
                            F' {positive_arg}={kwargs[positive_arg]}')

          a__						:	Union[str, Any] =				kwargs.pop('torchscript'					,  self.torchscript)
          a__						:	Tuple =				kwargs.pop('torch_xla_tpu_print_metrics'					,  self.torch_xla_tpu_print_metrics)
          a__						:	Tuple =				kwargs.pop('fp16_opt_level'					,  self.fpaa_opt_level)
          super().__init__(**lowercase)

   __A   :				bool         =  field(default=__UpperCAmelCase ,  metadata={'''help''': '''Trace the models using torchscript'''}	)
   __A   :				bool         =  field(default=__UpperCAmelCase ,  metadata={'''help''': '''Print Xla/PyTorch tpu metrics'''}	)
   __A   :				str         =  field(
       default='''O1''' ,  metadata={
           '''help''': (
               '''For fp16: Apex AMP optimization level selected in [\'O0\', \'O1\', \'O2\', and \'O3\']. '''
               '''See details at https://nvidia.github.io/apex/amp.html'''
           )
       } ,  )

   @cached_property
   def 							__lowercase		(					self)			->						Tuple["torch.device", int]:







          '''simple docstring'''

          requires_backends(self					,  ['torch'])
          logger.info('PyTorch: setting up devices')
          if not self.cuda:
                 a__						:	List[str] =				torch.device('cpu')
                 a__						:	Optional[Any] =				0
          elif is_torch_tpu_available():
                 a__						:	List[str] =				xm.xla_device()
                 a__						:	Union[str, Any] =				0
          else:
                 a__						:	List[Any] =				torch.device('cuda' if torch.cuda.is_available() else 'cpu')
                 a__						:	Optional[int] =				torch.cuda.device_count()
          return device, n_gpu

   @property
   def 							__lowercase		(					self)			->						List[str]:







          '''simple docstring'''

          return is_torch_tpu_available() and self.tpu

   @property
   def 							__lowercase		(					self)			->						int:







          '''simple docstring'''

          requires_backends(self					,  ['torch'])
          # TODO(PVP): currently only single GPU is supported
          return torch.cuda.current_device()

   @property
   def 							__lowercase		(					self)			->						"torch.device":







          '''simple docstring'''

          requires_backends(self					,  ['torch'])
          return self._setup_devices[0]

   @property
   def 							__lowercase		(					self)			->						Dict:







          '''simple docstring'''

          requires_backends(self					,  ['torch'])
          return self._setup_devices[1]

   @property
   def 							__lowercase		(					self)			->						Optional[int]:







          '''simple docstring'''

          return self.n_gpu > 0


