



# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case__					:     List[str]    		=   {
    """configuration_mgp_str""": ["""MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MgpstrConfig"""],
    """processing_mgp_str""": ["""MgpstrProcessor"""],
    """tokenization_mgp_str""": ["""MgpstrTokenizer"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case__					:     Dict    		=   [
	    """MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """MgpstrModel""",
	    """MgpstrPreTrainedModel""",
	    """MgpstrForSceneTextRecognition""",
	]

if TYPE_CHECKING:
	from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
	from .processing_mgp_str import MgpstrProcessor
	from .tokenization_mgp_str import MgpstrTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_mgp_str import (
		    MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MgpstrForSceneTextRecognition,
		    MgpstrModel,
		    MgpstrPreTrainedModel,
		)
else:
	import sys

	snake_case__					:     Union[str, Any]    		=   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








import numpy as np

snake_case__					:     Tuple    		=   [
    ["""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	:							Dict	):






							'''simple docstring'''



							__lowercase		       =			np.array(lowerCamelCase	)



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							__lowercase       ,    __lowercase		       =			np.where(letter == self.SQUARE	)
							__lowercase		       =			np.concatenate([indexa + 1, indexa + 1]	)
							return indexes



						def     _snake_case	(	self	:							List[Any]							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							__lowercase		       =			self.SQUARE[indexa - 1, indexa - 1]
							return letter



						def     _snake_case	(	self	:							int							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							__lowercase		       =			message.lower()
							__lowercase		       =			message.replace(" "							,      ""	)
							__lowercase		       =			message.replace("j"							,      "i"	)

							__lowercase		       =			np.empty((2, len(lowerCamelCase	))	)
							for letter_index in range(len(lowerCamelCase	)	):
								__lowercase		       =			self.letter_to_numbers(message[letter_index]	)

								__lowercase		       =			numbers[0]
								__lowercase		       =			numbers[1]

							__lowercase		       =			first_step.reshape(2 * len(lowerCamelCase	)	)
							__lowercase		       =			""
							for numbers_index in range(len(lowerCamelCase	)	):
								__lowercase		       =			int(second_step[numbers_index * 2]	)
								__lowercase		       =			int(second_step[(numbers_index * 2) + 1]	)
								__lowercase		       =			self.numbers_to_letter(lowerCamelCase							,      lowerCamelCase	)
								__lowercase		       =			encoded_message + letter

							return encoded_message



						def     _snake_case	(	self	:							Optional[Any]							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							__lowercase		       =			message.lower()
							message.replace(" "							,      ""	)
							__lowercase		       =			np.empty(2 * len(lowerCamelCase	)	)
							for letter_index in range(len(lowerCamelCase	)	):
								__lowercase		       =			self.letter_to_numbers(message[letter_index]	)
								__lowercase		       =			numbers[0]
								__lowercase		       =			numbers[1]

							__lowercase		       =			first_step.reshape((2, len(lowerCamelCase	))	)
							__lowercase		       =			""
							for numbers_index in range(len(lowerCamelCase	)	):
								__lowercase		       =			int(second_step[0, numbers_index]	)
								__lowercase		       =			int(second_step[1, numbers_index]	)
								__lowercase		       =			self.numbers_to_letter(lowerCamelCase							,      lowerCamelCase	)
								__lowercase		       =			decoded_message + letter

							return decoded_message



