


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

 SCREAMING_SNAKE_CASE       :      Tuple												= True
except ImportError:
 SCREAMING_SNAKE_CASE       :      List[Any]												= False

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



def 				UpperCamelCase_(      lowerCamelCase_ )    ->						List[str]:
    return AddNewModelCommand(args.testing							, args.testing_file							, path=args.path )






class _lowerCamelCase(						_a   ):
       @staticmethod
       def 			UpperCamelCase     (					lowerCamelCase)       ->   List[Any]:




           """simple docstring"""

           _lowercase       :							Tuple      		=		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=lowerCamelCase,      help='Configuration file on which to run.')
           add_new_model_parser.add_argument(
               '--path',      type=lowerCamelCase,      help='Path to cookiecutter. Should only be used for testing purposes.')
           add_new_model_parser.set_defaults(func=lowerCamelCase)
       def __init__(					self,      lowerCamelCase,      lowerCamelCase,      lowerCamelCase=None,      *lowerCamelCase)       ->   str:




           """simple docstring"""

           _lowercase       :							Dict      		=		testing
           _lowercase       :							Tuple      		=		testing_file
           _lowercase       :							List[Any]      		=		path




       def 			UpperCamelCase     (					self)       ->   Dict:




           """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
           _lowercase       :							Tuple      		=		[directory for directory in os.listdir() if 'cookiecutter-template-' == directory[:22]]
           if len(lowerCamelCase) > 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.')

           _lowercase       :							Optional[int]      		=		(
               Path(lowerCamelCase).parent.parent.parent.parent if self._path is None else Path(self._path).parent.parent
           )
           _lowercase       :							List[Any]      		=		path_to_transformer_root / 'templates' / 'adding_a_new_model'

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

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

           _lowercase       :							Dict      		=		[directory for directory in os.listdir() if 'cookiecutter-template-' in directory[:22]][0]

           # Retrieve configuration
           with open(directory + '/configuration.json',      'r') as configuration_file:
               _lowercase       :							Dict      		=		json.load(lowerCamelCase)

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

           _lowercase       :							List[str]      		=		'PyTorch' in generate_tensorflow_pytorch_and_flax
           _lowercase       :							Optional[Any]      		=		'TensorFlow' in generate_tensorflow_pytorch_and_flax
           _lowercase       :							Tuple      		=		'Flax' in generate_tensorflow_pytorch_and_flax

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

           # 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(lowerCamelCase):
               with open(lowerCamelCase,      'r') as f:
                   _lowercase       :							Any      		=		f.readlines()
               with open(lowerCamelCase,      'w') as f:
                   for line in lines:
                       if "# Copied from transformers." not in line:
                           f.write(lowerCamelCase)

           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(lowerCamelCase,      lowerCamelCase,      lowerCamelCase):
               # Create temp file
               _lowercase		,				_lowercase       :							str      		=		mkstemp()
               _lowercase       :							List[Any]      		=		False
               with fdopen(lowerCamelCase,      'w') as new_file:
                   with open(lowerCamelCase) as old_file:
                       for line in old_file:
                           new_file.write(lowerCamelCase)
                           if line_to_copy_below in line:
                               _lowercase       :							Dict      		=		True
                               for line_to_copy in lines_to_copy:
                                   new_file.write(lowerCamelCase)

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

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

                           _lowercase       :							Union[str, Any]      		=		[]
                       elif "# Replace with" in line and "##" not in line:
                           _lowercase       :							Any      		=		[]
                       elif "##" not in line:
                           lines_to_copy.append(lowerCamelCase)

               remove(lowerCamelCase)

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






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_tf_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE       :      List[str]												= {
    "configuration_speech_to_text": ["SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "Speech2TextConfig"],
    "processing_speech_to_text": ["Speech2TextProcessor"],
}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE       :      Union[str, Any]												= ["Speech2TextTokenizer"]

try:
 if not is_speech_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE       :      int												= ["Speech2TextFeatureExtractor"]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE       :      Optional[Any]												= [
     "TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TFSpeech2TextForConditionalGeneration",
     "TFSpeech2TextModel",
     "TFSpeech2TextPreTrainedModel",
 ]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE       :      str												= [
     "SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "Speech2TextForConditionalGeneration",
     "Speech2TextModel",
     "Speech2TextPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_speech_to_text import SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextConfig
 from .processing_speech_to_text import SpeechaTextProcessor

 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_speech_to_text import SpeechaTextTokenizer

 try:
  if not is_speech_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_speech_to_text import SpeechaTextFeatureExtractor

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_speech_to_text import (
      TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFSpeechaTextForConditionalGeneration,
      TFSpeechaTextModel,
      TFSpeechaTextPreTrainedModel,
  )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_speech_to_text import (
      SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
      SpeechaTextForConditionalGeneration,
      SpeechaTextModel,
      SpeechaTextPreTrainedModel,
  )

else:
 import sys

 SCREAMING_SNAKE_CASE       :      Optional[Any]												= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


