


"""simple docstring"""
import numpy as np

__SCREAMING_SNAKE_CASE							:      Optional[int]						=      [
    ['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    )   ->None:



											"""simple docstring"""



											snake_case_          =						np.array(UpperCAmelCase_    )



				def 						lowerCAmelCase    (			self							: Any						,    UpperCAmelCase_							: str    )   ->np.ndarray:



											"""simple docstring"""



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



				def 						lowerCAmelCase    (			self							: Optional[Any]						,    UpperCAmelCase_							: int						,    UpperCAmelCase_							: int    )   ->str:



											"""simple docstring"""



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



				def 						lowerCAmelCase    (			self							: Optional[Any]						,    UpperCAmelCase_							: str    )   ->str:



											"""simple docstring"""



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

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

																		snake_case_          =						numbers[0]
																		snake_case_          =						numbers[1]

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

											return encoded_message



				def 						lowerCAmelCase    (			self							: str						,    UpperCAmelCase_							: str    )   ->str:



											"""simple docstring"""



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

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

											return decoded_message







"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__SCREAMING_SNAKE_CASE							:      Dict						=      logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE							:      Tuple						=      {
    'google/mobilenet_v1_1.0_224': 'https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json',
    'google/mobilenet_v1_0.75_192': 'https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json',
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}





class        __A       (snake_case__):





							'''simple docstring'''

							__lowercase:						List[Any]							 =      """mobilenet_v1"""



							def __init__(			self							: Union[str, Any]						,    UpperCAmelCase_							: str=3						,    UpperCAmelCase_							: List[Any]=224						,    UpperCAmelCase_							: List[Any]=1.0						,    UpperCAmelCase_							: Any=8						,    UpperCAmelCase_							: int="relu6"						,    UpperCAmelCase_							: str=True						,    UpperCAmelCase_							: List[str]=0.999						,    UpperCAmelCase_							: Optional[Any]=0.02						,    UpperCAmelCase_							: List[Any]=0.001						,    **UpperCAmelCase_							: Any						,    )   ->Union[str, Any]:



														"""simple docstring"""



														super().__init__(**UpperCAmelCase_    )

														if depth_multiplier <= 0:
																					raise ValueError("""depth_multiplier must be greater than zero."""    )

														snake_case_          =						num_channels
														snake_case_          =						image_size
														snake_case_          =						depth_multiplier
														snake_case_          =						min_depth
														snake_case_          =						hidden_act
														snake_case_          =						tf_padding
														snake_case_          =						classifier_dropout_prob
														snake_case_          =						initializer_range
														snake_case_          =						layer_norm_eps





class        __A       (snake_case__):





							'''simple docstring'''

							__lowercase:						int							 =      version.parse("""1.11""")



							@property
							def 						lowerCAmelCase    (			self							: Union[str, Any]    )   ->Mapping[str, Mapping[int, str]]:



														"""simple docstring"""



														return OrderedDict([("""pixel_values""", {0: """batch"""})]    )



							@property
							def 						lowerCAmelCase    (			self							: int    )   ->Mapping[str, Mapping[int, str]]:



														"""simple docstring"""



														if self.task == "image-classification":
																					return OrderedDict([("""logits""", {0: """batch"""})]    )
														else:
																					return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]    )



							@property
							def 						lowerCAmelCase    (			self							: int    )   ->float:



														"""simple docstring"""



														return 1E-4



