




'''simple docstring'''






import numpy as np

_lowerCAmelCase				     = [
    ['''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:
							__UpperCamelCase				:      Optional[int]									=       np.array(_UpperCAmelCase      )
				def 	a_	(self			,  _UpperCAmelCase      )     ->	np.ndarray:
							__UpperCamelCase		, __UpperCamelCase				:      Tuple									=       np.where(letter == self.SQUARE      )
							__UpperCamelCase				:      List[Any]									=       np.concatenate([indexa + 1, indexa + 1]      )
							return indexes
				def 	a_	(self			,  _UpperCAmelCase			,  _UpperCAmelCase      )     ->	str:
							return self.SQUARE[indexa - 1, indexa - 1]
				def 	a_	(self			,  _UpperCAmelCase      )     ->	str:
							__UpperCamelCase				:      Optional[int]									=       message.lower()
							__UpperCamelCase				:      List[str]									=       message.replace("j"			,  "i"      )

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

							return encoded_message





				def 	a_	(self			,  _UpperCAmelCase      )     ->	str:
							__UpperCamelCase				:      str									=       message.replace(" "			,  "  "      )
							__UpperCamelCase				:      Dict									=       ""
							for numbers_index in range(int(len(_UpperCAmelCase      ) / 2      )      ):
										if message[numbers_index * 2] != " ":
													__UpperCamelCase				:      List[Any]									=       message[numbers_index * 2]
													__UpperCamelCase				:      Union[str, Any]									=       message[numbers_index * 2 + 1]

													__UpperCamelCase				:      Optional[int]									=       self.numbers_to_letter(int(_UpperCAmelCase      )			,  int(_UpperCAmelCase      )      )
													__UpperCamelCase				:      str									=       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


_lowerCAmelCase				     = {'''configuration_visual_bert''': ['''VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VisualBertConfig''']}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCAmelCase				     = [
				    '''VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''VisualBertForMultipleChoice''',
				    '''VisualBertForPreTraining''',
				    '''VisualBertForQuestionAnswering''',
				    '''VisualBertForRegionToPhraseAlignment''',
				    '''VisualBertForVisualReasoning''',
				    '''VisualBertLayer''',
				    '''VisualBertModel''',
				    '''VisualBertPreTrainedModel''',
				]


if TYPE_CHECKING:
				from .configuration_visual_bert import VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, VisualBertConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_visual_bert import (
								    VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    VisualBertForMultipleChoice,
								    VisualBertForPreTraining,
								    VisualBertForQuestionAnswering,
								    VisualBertForRegionToPhraseAlignment,
								    VisualBertForVisualReasoning,
								    VisualBertLayer,
								    VisualBertModel,
								    VisualBertPreTrainedModel,
								)


else:
				import sys

				_lowerCAmelCase				     = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



