
import numpy as np

UpperCAmelCase__			 =	[
    ['''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        snake_case_					:

						"""simple docstring"""



						def __init__(self:				Optional[Any]      )						->    None:




											'''simple docstring'''



											__a				:	Optional[Any]			=				np.array(__UpperCAmelCase      )



						def 					UpperCAmelCase__				(self:				Dict   ,				__UpperCAmelCase:				str      )						->    np.ndarray:




											'''simple docstring'''



											__a				:	List[Any]			=				np.where(letter == self.SQUARE      )
											__a				:	Union[str, Any]			=				np.concatenate([indexa + 1, indexa + 1]      )
											return indexes



						def 					UpperCAmelCase__				(self:				str   ,				__UpperCAmelCase:				int   ,				__UpperCAmelCase:				int      )						->    str:




											'''simple docstring'''



											return self.SQUARE[indexa - 1, indexa - 1]



						def 					UpperCAmelCase__				(self:				Optional[int]   ,				__UpperCAmelCase:				str      )						->    str:




											'''simple docstring'''



											__a				:	Optional[int]			=				message.lower()
											__a				:	Dict			=				message.replace("j"   ,				"i"      )

											__a				:	Tuple			=				""
											for letter_index in range(len(__UpperCAmelCase      )      ):
																if message[letter_index] != " ":
																					__a				:	Optional[int]			=				self.letter_to_numbers(message[letter_index]      )
																					__a				:	Optional[Any]			=				encoded_message + str(numbers[0]      ) + str(numbers[1]      )
																elif message[letter_index] == " ":
																					__a				:	Any			=				encoded_message + " "

											return encoded_message



						def 					UpperCAmelCase__				(self:				List[str]   ,				__UpperCAmelCase:				str      )						->    str:




											'''simple docstring'''



											__a				:	Union[str, Any]			=				message.replace(" "   ,				"  "      )
											__a				:	Any			=				""
											for numbers_index in range(int(len(__UpperCAmelCase      ) / 2      )      ):
																if message[numbers_index * 2] != " ":
																					__a				:	str			=				message[numbers_index * 2]
																					__a				:	Tuple			=				message[numbers_index * 2 + 1]

																					__a				:	Tuple			=				self.numbers_to_letter(int(__UpperCAmelCase      )   ,				int(__UpperCAmelCase      )      )
																					__a				:	int			=				decoded_message + letter
																elif message[numbers_index * 2] == " ":
																					__a				:	Union[str, Any]			=				decoded_message + " "

											return decoded_message













from typing import TYPE_CHECKING

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


UpperCAmelCase__			 =	{'''configuration_pegasus''': ['''PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusConfig''']}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	['''PegasusTokenizer''']

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	['''PegasusTokenizerFast''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	[
			    '''PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''PegasusForCausalLM''',
			    '''PegasusForConditionalGeneration''',
			    '''PegasusModel''',
			    '''PegasusPreTrainedModel''',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	[
			    '''TFPegasusForConditionalGeneration''',
			    '''TFPegasusModel''',
			    '''TFPegasusPreTrainedModel''',
			]

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__			 =	[
			    '''FlaxPegasusForConditionalGeneration''',
			    '''FlaxPegasusModel''',
			    '''FlaxPegasusPreTrainedModel''',
			]


if TYPE_CHECKING:
			from .configuration_pegasus import PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_pegasus import PegasusTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_pegasus_fast import PegasusTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_pegasus import (
						    PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
						    PegasusForCausalLM,
						    PegasusForConditionalGeneration,
						    PegasusModel,
						    PegasusPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_pegasus import TFPegasusForConditionalGeneration, TFPegasusModel, TFPegasusPreTrainedModel

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_pegasus import (
						    FlaxPegasusForConditionalGeneration,
						    FlaxPegasusModel,
						    FlaxPegasusPreTrainedModel,
						)

else:
			import sys

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





