



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

 __snake_case		:str   	=  True
except ImportError:
 __snake_case		:str   	=  False

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





def   __snake_case			(    _UpperCAmelCase       ):
    return AddNewModelCommand(args.testing     ,				args.testing_file     ,				path=args.path       )

class 					_A (			__UpperCAmelCase					):



       @staticmethod
       def 	_lowerCamelCase    (	__SCREAMING_SNAKE_CASE							:  ArgumentParser):


           '''simple docstring'''

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



       def __init__(	self							:  Any  ,	__SCREAMING_SNAKE_CASE							:  bool  ,	__SCREAMING_SNAKE_CASE							:  str  ,	__SCREAMING_SNAKE_CASE							:  int=None  ,	*__SCREAMING_SNAKE_CASE							:  List[Any]):


           '''simple docstring'''

           __a		 =       testing
           __a		 =       testing_file
           __a		 =       path





       def 	_lowerCamelCase    (	self							:  List[str]):


           '''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		 =       [directory for directory in os.listdir() if '''cookiecutter-template-''' == directory[:22]]
           if len(__SCREAMING_SNAKE_CASE) > 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		 =       (
               Path(__SCREAMING_SNAKE_CASE).parent.parent.parent.parent if self._path is None else Path(self._path).parent.parent
           )
           __a		 =       path_to_transformer_root / '''templates''' / '''adding_a_new_model'''

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

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

           __a		 =       [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		 =       json.load(__SCREAMING_SNAKE_CASE)

           __a		 =       configuration['''lowercase_modelname''']
           __a		 =       configuration['''generate_tensorflow_pytorch_and_flax''']
           os.remove(F'{directory}/configuration.json')

           __a		 =       '''PyTorch''' in generate_tensorflow_pytorch_and_flax
           __a		 =       '''TensorFlow''' in generate_tensorflow_pytorch_and_flax
           __a		 =       '''Flax''' in generate_tensorflow_pytorch_and_flax

           __a		 =       F'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
           os.makedirs(__SCREAMING_SNAKE_CASE  ,	exist_ok=__SCREAMING_SNAKE_CASE)
           os.makedirs(F'{path_to_transformer_root}/tests/models/{lowercase_model_name}'  ,	exist_ok=__SCREAMING_SNAKE_CASE)

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

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

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

           def skip_units(__SCREAMING_SNAKE_CASE							:  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(__SCREAMING_SNAKE_CASE							:  str):
               with open(__SCREAMING_SNAKE_CASE) as datafile:
                   __a		 =       []
                   __a		 =       False
                   __a		 =       False
                   for line in datafile:
                       if "# To replace in: " in line and "##" not in line:
                           __a		 =       line.split('''"''')[1]
                           __a		 =       skip_units(__SCREAMING_SNAKE_CASE)
                       elif "# Below: " in line and "##" not in line:
                           __a		 =       line.split('''"''')[1]
                           __a		 =       skip_units(__SCREAMING_SNAKE_CASE)
                       elif "# End." in line and "##" not in line:
                           if not skip_file and not skip_snippet:
                               replace(__SCREAMING_SNAKE_CASE  ,	__SCREAMING_SNAKE_CASE  ,	__SCREAMING_SNAKE_CASE)

                           __a		 =       []
                       elif "# Replace with" in line and "##" not in line:
                           __a		 =       []
                       elif "##" not in line:
                           lines_to_copy.append(__SCREAMING_SNAKE_CASE)

               remove(__SCREAMING_SNAKE_CASE)

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










from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset

class 					_A (			__UpperCAmelCase					):



       def 	_lowerCamelCase    (	self							:  int):


           '''simple docstring'''

           return [
               {"col_1": 3, "col_2": "a"},
               {"col_1": 2, "col_2": "b"},
               {"col_1": 1, "col_2": "c"},
               {"col_1": 0, "col_2": "d"},
           ]



       def 	_lowerCamelCase    (	self							:  Tuple):


           '''simple docstring'''

           __a		 =       {'''col_1''': [3, 2, 1, 0], '''col_2''': ['''a''', '''b''', '''c''', '''d''']}
           return Dataset.from_dict(__SCREAMING_SNAKE_CASE)



       def 	_lowerCamelCase    (	self							:  Any):


           '''simple docstring'''

           __a		 =       self._create_example_records()
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           self.assertListEqual(dset.column_names  ,	['''col_1''', '''col_2'''])
           for i, r in enumerate(__SCREAMING_SNAKE_CASE):
               self.assertDictEqual(__SCREAMING_SNAKE_CASE  ,	example_records[i])



       def 	_lowerCamelCase    (	self							:  Optional[Any]):


           '''simple docstring'''

           __a		 =       self._create_example_records()
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           __a		 =       Dataset.from_dict({k: [r[k] for r in example_records] for k in example_records[0]})
           self.assertEqual(dset.info  ,	dset_from_dict.info)



       def 	_lowerCamelCase    (	self							:  int):  # checks what happens with missing columns


           '''simple docstring'''

           __a		 =       [{'''col_1''': 1}, {'''col_2''': '''x'''}]
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           self.assertDictEqual(dset[0]  ,	{'''col_1''': 1})
           self.assertDictEqual(dset[1]  ,	{'''col_1''': None})  # NB: first record is used for columns



       def 	_lowerCamelCase    (	self							:  Optional[Any]):  # checks if the type can be inferred from the second record


           '''simple docstring'''

           __a		 =       [{'''col_1''': []}, {'''col_1''': [1, 2]}]
           __a		 =       Dataset.from_list(__SCREAMING_SNAKE_CASE)
           self.assertEqual(dset.info.features['''col_1''']  ,	Sequence(Value('''int64''')))





       def 	_lowerCamelCase    (	self							:  List[Any]):


           '''simple docstring'''

           __a		 =       Dataset.from_list([])
           self.assertEqual(len(__SCREAMING_SNAKE_CASE)  ,	0)
           self.assertListEqual(dset.column_names  ,	[])





