




'''simple docstring'''







import os
import sys
import unittest


lowercase      :   Tuple      =       os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
lowercase      :   Optional[int]      =       os.path.join(git_repo_path, """src""", """transformers""")

lowercase      :   int      =       """
{0} = None
"""

lowercase      :   Tuple      =       """
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
"""


lowercase      :   int      =       """
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
"""







class 					_a (unittest.TestCase	):





     '''simple docstring'''



     def 			snake_case_      (				self							)      ->				str:
          snake_case			:      List[Any]        =			find_backend("""    _import_structure[\"models.albert\"].append(\"AlbertTokenizerFast\")"""							)
          self.assertIsNone(__a							)

          snake_case			:      str        =			find_backend("""    if not is_tokenizers_available():"""							)
          self.assertEqual(__a							,"""tokenizers"""							)

          snake_case			:      List[str]        =			find_backend("""    if not is_tensorflow_text_available():"""							)
          self.assertEqual(__a							,"""tensorflow_text"""							)

          snake_case			:      str        =			find_backend("""    if not (is_sentencepiece_available() and is_tokenizers_available()):"""							)
          self.assertEqual(__a							,"""sentencepiece_and_tokenizers"""							)

          snake_case			:      Any        =			find_backend(
              """    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"""							)
          self.assertEqual(__a							,"""sentencepiece_and_tensorflow_text"""							)

          snake_case			:      List[Any]        =			find_backend(
              """    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):"""							)
          self.assertEqual(__a							,"""sentencepiece_and_tokenizers_and_vision"""							)







     def 			snake_case_      (				self							)      ->				Tuple:
          snake_case			:      int        =			read_init()
          # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
          self.assertIn("""torch"""							,__a							)
          self.assertIn("""tensorflow_text"""							,__a							)
          self.assertIn("""sentencepiece_and_tokenizers"""							,__a							)

          # Likewise, we can't assert on the exact content of a key
          self.assertIn("""BertModel"""							,objects["""torch"""]							)
          self.assertIn("""TFBertModel"""							,objects["""tf"""]							)
          self.assertIn("""FlaxBertModel"""							,objects["""flax"""]							)
          self.assertIn("""BertModel"""							,objects["""torch"""]							)
          self.assertIn("""TFBertTokenizer"""							,objects["""tensorflow_text"""]							)
          self.assertIn("""convert_slow_tokenizer"""							,objects["""sentencepiece_and_tokenizers"""]							)







     def 			snake_case_      (				self							)      ->				Union[str, Any]:
          snake_case			:      Optional[Any]        =			create_dummy_object("""CONSTANT"""							,"""'torch'"""							)
          self.assertEqual(__a							,"""\nCONSTANT = None\n"""							)

          snake_case			:      int        =			create_dummy_object("""function"""							,"""'torch'"""							)
          self.assertEqual(
              __a							,"""\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"""							)

          snake_case			:      Optional[int]        =			"""
class FakeClass(metaclass=DummyObject):
    _backends = 'torch'

    def __init__(self, *args, **kwargs):
        requires_backends(self, 'torch')
"""
          snake_case			:      List[Any]        =			create_dummy_object("""FakeClass"""							,"""'torch'"""							)
          self.assertEqual(__a							,__a							)







     def 			snake_case_      (				self							)      ->				str:
          snake_case			:      Union[str, Any]        =			"""# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


CONSTANT = None


def function(*args, **kwargs):
    requires_backends(function, [\"torch\"])


class FakeClass(metaclass=DummyObject):
    _backends = [\"torch\"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, [\"torch\"])
"""
          snake_case			:      Tuple        =			create_dummy_files({"""torch""": ["""CONSTANT""", """function""", """FakeClass"""]}							)
          self.assertEqual(dummy_files["""torch"""]							,__a							)









'''simple docstring'''







import numpy as np

lowercase      :   str      =       [
    ["""a""", """b""", """c""", """d""", """e"""],
    ["""f""", """g""", """h""", """i""", """k"""],
    ["""l""", """m""", """n""", """o""", """p"""],
    ["""q""", """r""", """s""", """t""", """u"""],
    ["""v""", """w""", """x""", """y""", """z"""],
]







class 					_a :





     '''simple docstring'''



     def __init__(				self							)      ->				None:
          snake_case			:      Dict        =			np.array(__a							)







     def 			snake_case_      (				self							,__a							)      ->				np.ndarray:
          snake_case ,		snake_case			:      Optional[Any]        =			np.where(letter == self.SQUARE							)
          snake_case			:      List[Any]        =			np.concatenate([indexa + 1, indexa + 1]							)
          return indexes







     def 			snake_case_      (				self							,__a							,__a							)      ->				str:
          snake_case			:      List[Any]        =			self.SQUARE[indexa - 1, indexa - 1]
          return letter







     def 			snake_case_      (				self							,__a							)      ->				str:
          snake_case			:      List[Any]        =			message.lower()
          snake_case			:      Dict        =			message.replace(""" """							,""""""							)
          snake_case			:      List[str]        =			message.replace("""j"""							,"""i"""							)

          snake_case			:      Optional[int]        =			np.empty((2, len(__a							))							)
          for letter_index in range(len(__a							)							):
               snake_case			:      Tuple        =			self.letter_to_numbers(message[letter_index]							)

               snake_case			:      Optional[Any]        =			numbers[0]
               snake_case			:      List[str]        =			numbers[1]

          snake_case			:      List[str]        =			first_step.reshape(2 * len(__a							)							)
          snake_case			:      List[Any]        =			""""""
          for numbers_index in range(len(__a							)							):
               snake_case			:      List[str]        =			int(second_step[numbers_index * 2]							)
               snake_case			:      List[Any]        =			int(second_step[(numbers_index * 2) + 1]							)
               snake_case			:      str        =			self.numbers_to_letter(__a							,__a							)
               snake_case			:      Any        =			encoded_message + letter

          return encoded_message







     def 			snake_case_      (				self							,__a							)      ->				str:
          snake_case			:      Any        =			message.lower()
          message.replace(""" """							,""""""							)
          snake_case			:      Dict        =			np.empty(2 * len(__a							)							)
          for letter_index in range(len(__a							)							):
               snake_case			:      str        =			self.letter_to_numbers(message[letter_index]							)
               snake_case			:      Any        =			numbers[0]
               snake_case			:      int        =			numbers[1]

          snake_case			:      List[str]        =			first_step.reshape((2, len(__a							))							)
          snake_case			:      Dict        =			""""""
          for numbers_index in range(len(__a							)							):
               snake_case			:      Optional[Any]        =			int(second_step[0, numbers_index]							)
               snake_case			:      Optional[int]        =			int(second_step[1, numbers_index]							)
               snake_case			:      Tuple        =			self.numbers_to_letter(__a							,__a							)
               snake_case			:      int        =			decoded_message + letter

          return decoded_message



