
"""simple docstring"""





import numpy as np

_a									=				[
    ['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    ):

     """simple docstring"""
     UpperCAmelCase_   :   int     	=       np.array(lowercase_    )







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_	,  UpperCAmelCase_   :   int     	=       np.where(letter == self.SQUARE    )
     UpperCAmelCase_   :   Optional[Any]     	=       np.concatenate([indexa + 1, indexa + 1]    )
     return indexes







  def 			UpperCamelCase__   (						self							,  lowercase_							,  lowercase_    ):

     """simple docstring"""
     return self.SQUARE[indexa - 1, indexa - 1]







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   Union[str, Any]     	=       message.lower()
     UpperCAmelCase_   :   int     	=       message.replace("j"							,  "i"    )

     UpperCAmelCase_   :   Union[str, Any]     	=       ""
     for letter_index in range(len(lowercase_    )    ):
        if message[letter_index] != " ":
           UpperCAmelCase_   :   List[Any]     	=       self.letter_to_numbers(message[letter_index]    )
           UpperCAmelCase_   :   Dict     	=       encoded_message + str(numbers[0]    ) + str(numbers[1]    )
        elif message[letter_index] == " ":
           UpperCAmelCase_   :   int     	=       encoded_message + " "

     return encoded_message







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   Any     	=       message.replace(" "							,  "  "    )
     UpperCAmelCase_   :   List[Any]     	=       ""
     for numbers_index in range(int(len(lowercase_    ) / 2    )    ):
        if message[numbers_index * 2] != " ":
           UpperCAmelCase_   :   List[Any]     	=       message[numbers_index * 2]
           UpperCAmelCase_   :   Dict     	=       message[numbers_index * 2 + 1]

           UpperCAmelCase_   :   Tuple     	=       self.numbers_to_letter(int(lowercase_    )							,  int(lowercase_    )    )
           UpperCAmelCase_   :   List[Any]     	=       decoded_message + letter
        elif message[numbers_index * 2] == " ":
           UpperCAmelCase_   :   Optional[Any]     	=       decoded_message + " "

     return decoded_message



'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


_A		:      Optional[Any]						   ={
    '''configuration_mobilevitv2''': [
        '''MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileViTV2Config''',
        '''MobileViTV2OnnxConfig''',
    ],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _A		:      Union[str, Any]						   =[
     '''MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''MobileViTV2ForImageClassification''',
     '''MobileViTV2ForSemanticSegmentation''',
     '''MobileViTV2Model''',
     '''MobileViTV2PreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_mobilevitva import (
     MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
     MobileViTVaConfig,
     MobileViTVaOnnxConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mobilevitva import (
      MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
      MobileViTVaForImageClassification,
      MobileViTVaForSemanticSegmentation,
      MobileViTVaModel,
      MobileViTVaPreTrainedModel,
  )

else:
 import sys

 _A		:      Tuple						   =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)