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


snake_case      =    logging.get_logger(__name__)

snake_case      =    {
    "google/mobilenet_v2_1.4_224": "https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json",
    "google/mobilenet_v2_1.0_224": "https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json",
    "google/mobilenet_v2_0.75_160": "https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json",
    "google/mobilenet_v2_0.35_96": "https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json",
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}



class __A     (      __lowercase						):

							'''simple docstring'''

							a_     =					"mobilenet_v2"






							def __init__(				self   ,	_snake_case=3   ,	_snake_case=224   ,	_snake_case=1.0   ,	_snake_case=8   ,	_snake_case=8   ,	_snake_case=6   ,	_snake_case=32   ,	_snake_case=True   ,	_snake_case=True   ,	_snake_case="relu6"   ,	_snake_case=True   ,	_snake_case=0.8   ,	_snake_case=0.02   ,	_snake_case=0.001   ,	_snake_case=255   ,	**_snake_case   ,	):
												super().__init__(**_snake_case )

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

												_lowerCAmelCase			:		Dict          = num_channels
												_lowerCAmelCase			:		Optional[Any]          = image_size
												_lowerCAmelCase			:		Dict          = depth_multiplier
												_lowerCAmelCase			:		Dict          = depth_divisible_by
												_lowerCAmelCase			:		Dict          = min_depth
												_lowerCAmelCase			:		Optional[Any]          = expand_ratio
												_lowerCAmelCase			:		int          = output_stride
												_lowerCAmelCase			:		Optional[Any]          = first_layer_is_expansion
												_lowerCAmelCase			:		Optional[Any]          = finegrained_output
												_lowerCAmelCase			:		List[Any]          = hidden_act
												_lowerCAmelCase			:		str          = tf_padding
												_lowerCAmelCase			:		int          = classifier_dropout_prob
												_lowerCAmelCase			:		int          = initializer_range
												_lowerCAmelCase			:		Any          = layer_norm_eps
												_lowerCAmelCase			:		Any          = semantic_loss_ignore_index



class __A     (      __lowercase						):

							'''simple docstring'''

							a_     =					version.parse('''1.11'''						)






							@property
							def 	SCREAMING_SNAKE_CASE__			(				self ):
												return OrderedDict([("pixel_values", {0: "batch"})] )






							@property
							def 	SCREAMING_SNAKE_CASE__			(				self ):

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






							@property
							def 	SCREAMING_SNAKE_CASE__			(				self ):
												return 1E-4








from __future__ import annotations

lowerCamelCase__						=				"#"







class 							lowerCAmelCase__   :

						def __init__(      self					)       ->   None:


								'''simple docstring'''

								_UpperCamelCase         =						{}

						def 			A_					(      self							,				a					)       ->   None:


								'''simple docstring'''

								_UpperCamelCase         =						self._trie
								for char in text:
										if char not in trie:
												_UpperCamelCase         =						{}
										_UpperCamelCase         =						trie[char]
								_UpperCamelCase         =						True

						def 			A_					(      self							,				a					)       ->   tuple | list:


								'''simple docstring'''

								_UpperCamelCase         =						self._trie
								for char in prefix:
										if char in trie:
												_UpperCamelCase         =						trie[char]
										else:
												return []
								return self._elements(a					)







						def 			A_					(      self							,				a					)       ->   tuple:


								'''simple docstring'''

								_UpperCamelCase         =						[]
								for c, v in d.items():
										_UpperCamelCase         =						[""" """] if c == END else [(c + s) for s in self._elements(a					)]
										result.extend(a					)
								return tuple(a					)




lowerCamelCase__						=				Trie()
lowerCamelCase__						=				("depart", "detergent", "daring", "dog", "deer", "deal")
for word in words:
		trie.insert_word(word)


def 				__A(lowerCAmelCase			)		->					tuple:

		"""simple docstring"""






		_UpperCamelCase         =						trie.find_word(lowerCAmelCase			)
		return tuple(string + word for word in suffixes			)


def 				__A()		->					None:

		"""simple docstring"""






		print(autocomplete_using_trie("""de"""			)			)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()



