

"""simple docstring"""




from __future__ import annotations

A_							:			Dict											= "#"





class    lowerCamelCase						:

			def __init__(					self				:						Optional[Any]       )   ->    None:
						SCREAMING_SNAKE_CASE__								=      {}

			def 					SCREAMING_SNAKE_CASE				(					self				:						Dict    ,				__UpperCAmelCase				:						Optional[Any]       )   ->    None:
						SCREAMING_SNAKE_CASE__								=      self._trie
						for char in text:
									if char not in trie:
												SCREAMING_SNAKE_CASE__								=      {}
									SCREAMING_SNAKE_CASE__								=      trie[char]
						SCREAMING_SNAKE_CASE__								=      True

			def 					SCREAMING_SNAKE_CASE				(					self				:						Any    ,				__UpperCAmelCase				:						Optional[Any]       )   ->    tuple | list:
						SCREAMING_SNAKE_CASE__								=      self._trie
						for char in prefix:
									if char in trie:
												SCREAMING_SNAKE_CASE__								=      trie[char]
									else:
												return []
						return self._elements(__A       )





			def 					SCREAMING_SNAKE_CASE				(					self				:						Optional[Any]    ,				__UpperCAmelCase				:						Any       )   ->    tuple:
						SCREAMING_SNAKE_CASE__								=      []
						for c, v in d.items():
									SCREAMING_SNAKE_CASE__								=      [""" """] if c == END else [(c + s) for s in self._elements(__A       )]
									result.extend(__A       )
						return tuple(__A       )
A_							:			int											= Trie()
A_							:			Any											= ("depart", "detergent", "daring", "dog", "deer", "deal")
for word in words:
						trie.insert_word(word)

def 	A       (     snake_case__    ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__								=      trie.find_word(a__    )
			return tuple(string + word for word in suffixes    )

def 	A       (     ):




			'''simple docstring'''


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


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()








"""simple docstring"""




# 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

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A_							:			Dict											= {
    "configuration_efficientnet": [
        "EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientNetConfig",
        "EfficientNetOnnxConfig",
    ]
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_							:			List[Any]											= ["EfficientNetImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_							:			Dict											= [
						    "EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "EfficientNetForImageClassification",
						    "EfficientNetModel",
						    "EfficientNetPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_efficientnet import (
						    EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    EfficientNetConfig,
						    EfficientNetOnnxConfig,
						)

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_efficientnet import EfficientNetImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_efficientnet import (
												    EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    EfficientNetForImageClassification,
												    EfficientNetModel,
												    EfficientNetPreTrainedModel,
												)

else:
						import sys

						A_							:			List[Any]											= _LazyModule(__name__, globals()["__file__"], _import_structure)


