





'''simple docstring'''




class 			SCREAMING_SNAKE_CASE   :


					def __init__(						self						,     _UpperCAmelCase = ""						,     _UpperCAmelCase = False):

										'''simple docstring'''






										__A						:			dict[str, RadixNode]								=	{}

										# A node will be a leaf if the tree contains its word
										__A						:			str								=	is_leaf

										__A						:			Any								=	prefix


					def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase):

										'''simple docstring'''






										__A						:			Tuple								=	0
										for q, w in zip(self.prefix						,     lowerCamelCase__):
															if q != w:
																				break

															x += 1

										return self.prefix[:x], self.prefix[x:], word[x:]


					def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase):

										'''simple docstring'''






										for word in words:
															self.insert(lowerCamelCase__)


					def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase):

										'''simple docstring'''






										if self.prefix == word:
															__A						:			List[Any]								=	True

										# Case 2: The node has no edges that have a prefix to the word
										# Solution: We create an edge from the current node to a new one
										# containing the word
										elif word[0] not in self.nodes:
															__A						:			str								=	RadixNode(prefix=lowerCamelCase__						,     is_leaf=lowerCamelCase__)

										else:
															__A						:			Tuple								=	self.nodes[word[0]]
															__A						:			Union[str, Any]								=	incoming_node.match(
															    lowerCamelCase__)

															# Case 3: The node prefix is equal to the matching
															# Solution: We insert remaining word on the next node
															if remaining_prefix == "":
																				self.nodes[matching_string[0]].insert(lowerCamelCase__)

															# Case 4: The word is greater equal to the matching
															# Solution: Create a node in between both nodes, change
															# prefixes and add the new node for the remaining word
															else:
																				__A						:			Optional[int]								=	remaining_prefix

																				__A						:			List[Any]								=	self.nodes[matching_string[0]]
																				__A						:			Any								=	RadixNode(lowerCamelCase__						,     lowerCamelCase__)
																				__A						:			int								=	aux_node

																				if remaining_word == "":
																									__A						:			List[str]								=	True
																				else:
																									self.nodes[matching_string[0]].insert(lowerCamelCase__)


					def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase):

										'''simple docstring'''






										__A						:			Union[str, Any]								=	self.nodes.get(word[0]						,     lowerCamelCase__)
										if not incoming_node:
															return False
										else:
															__A						:			Tuple								=	incoming_node.match(
															    lowerCamelCase__)
															# If there is remaining prefix, the word can't be on the tree
															if remaining_prefix != "":
																				return False
															# This applies when the word and the prefix are equal
															elif remaining_word == "":
																				return incoming_node.is_leaf
															# We have word remaining so we check the next node
															else:
																				return incoming_node.find(lowerCamelCase__)


					def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase):

										'''simple docstring'''






										__A						:			List[Any]								=	self.nodes.get(word[0]						,     lowerCamelCase__)
										if not incoming_node:
															return False
										else:
															__A						:			List[str]								=	incoming_node.match(
															    lowerCamelCase__)
															# If there is remaining prefix, the word can't be on the tree
															if remaining_prefix != "":
																				return False
															# We have word remaining so we check the next node
															elif remaining_word != "":
																				return incoming_node.delete(lowerCamelCase__)
															else:
																				# If it is not a leaf, we don't have to delete
																				if not incoming_node.is_leaf:
																									return False
																				else:
																									# We delete the nodes if no edges go from it
																									if len(incoming_node.nodes) == 0:
																														del self.nodes[word[0]]
																														# We merge the current node with its only child
																														if len(self.nodes) == 1 and not self.is_leaf:
																																			__A						:			Any								=	list(self.nodes.values())[0]
																																			__A						:			Optional[Any]								=	merging_node.is_leaf
																																			self.prefix += merging_node.prefix
																																			__A						:			Tuple								=	merging_node.nodes
																																			         # If there is more than 1 edge, we just mark it as non-leaf
																									elif len(incoming_node.nodes) > 1:
																														__A						:			str								=	False
																									# If there is 1 edge, we merge it with its child
																									else:
																														__A						:			str								=	list(incoming_node.nodes.values())[0]
																														__A						:			Optional[Any]								=	merging_node.is_leaf
																														incoming_node.prefix += merging_node.prefix
																														__A						:			Optional[int]								=	merging_node.nodes

																									return True


					def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase = 0):

										'''simple docstring'''






										if self.prefix != "":
															print('-' * height						,     self.prefix						,     '  (leaf)' if self.is_leaf else '')

										for value in self.nodes.values():
															value.print_tree(height + 1)






def 	_lowerCAmelCase      (  )					->					Dict:
					__A						:			Tuple								=	'''banana bananas bandana band apple all beast'''.split()
					__A						:			Union[str, Any]								=	RadixNode()
					root.insert_many(__snake_case      )

					assert all(root.find(__snake_case      ) for word in words      )
					assert not root.find('bandanas'      )
					assert not root.find('apps'      )
					root.delete('all'      )
					assert not root.find('all'      )
					root.delete('banana'      )
					assert not root.find('banana'      )
					assert root.find('bananas'      )

					return True






def 	_lowerCAmelCase      (  )					->					List[str]:
					assert test_trie()






def 	_lowerCAmelCase      (  )					->					Optional[Any]:
					__A						:			Dict								=	RadixNode()
					__A						:			int								=	'''banana bananas bandanas bandana band apple all beast'''.split()
					root.insert_many(__snake_case      )

					print('Words:'			,							__snake_case      )
					print('Tree:'      )
					root.print_tree()


if __name__ == "__main__":
		main()






'''simple docstring'''




from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch

from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch


@require_torch
@require_tf
class 			SCREAMING_SNAKE_CASE   (a__							):


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						:			Optional[int]								=	SMALL_MODEL_IDENTIFIER
          __A						:			Any								=	'pt'
          __A						:			str								=	'tf'


     def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase):

          '''simple docstring'''






          __A						:			Any								=	AutoModel.from_pretrained(self.test_model)
          model_pt.save_pretrained(_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase):

          '''simple docstring'''






          __A						:			Union[str, Any]								=	TFAutoModel.from_pretrained(self.test_model						,     from_pt=_UpperCAmelCase)
          model_tf.save_pretrained(_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						:			Union[str, Any]								=	'mock_framework'

          # Framework provided - return whatever the user provides
          __A						:			Union[str, Any]								=	FeaturesManager.determine_framework(self.test_model						,     _UpperCAmelCase)
          self.assertEqual(_UpperCAmelCase						,     _UpperCAmelCase)

          # Local checkpoint and framework provided - return provided framework
          # PyTorch checkpoint
          with TemporaryDirectory() as local_pt_ckpt:
               self._setup_pt_ckpt(_UpperCAmelCase)
               __A						:			List[str]								=	FeaturesManager.determine_framework(_UpperCAmelCase						,     _UpperCAmelCase)
               self.assertEqual(_UpperCAmelCase						,     _UpperCAmelCase)

          # TensorFlow checkpoint
          with TemporaryDirectory() as local_tf_ckpt:
               self._setup_tf_ckpt(_UpperCAmelCase)
               __A						:			Tuple								=	FeaturesManager.determine_framework(_UpperCAmelCase						,     _UpperCAmelCase)
               self.assertEqual(_UpperCAmelCase						,     _UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          with TemporaryDirectory() as local_pt_ckpt:
               self._setup_pt_ckpt(_UpperCAmelCase)
               __A						:			Optional[int]								=	FeaturesManager.determine_framework(_UpperCAmelCase)
               self.assertEqual(_UpperCAmelCase						,     self.framework_pt)

          # TensorFlow checkpoint
          with TemporaryDirectory() as local_tf_ckpt:
               self._setup_tf_ckpt(_UpperCAmelCase)
               __A						:			List[str]								=	FeaturesManager.determine_framework(_UpperCAmelCase)
               self.assertEqual(_UpperCAmelCase						,     self.framework_tf)

          # Invalid local checkpoint
          with TemporaryDirectory() as local_invalid_ckpt:
               with self.assertRaises(_UpperCAmelCase):
                    __A						:			Tuple								=	FeaturesManager.determine_framework(_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						:			Tuple								=	MagicMock(return_value=_UpperCAmelCase)
          with patch('transformers.onnx.features.is_tf_available'						,     _UpperCAmelCase):
               __A						:			Union[str, Any]								=	FeaturesManager.determine_framework(self.test_model)
               self.assertEqual(_UpperCAmelCase						,     self.framework_pt)

          # PyTorch not in environment -> use TensorFlow
          __A						:			List[str]								=	MagicMock(return_value=_UpperCAmelCase)
          with patch('transformers.onnx.features.is_torch_available'						,     _UpperCAmelCase):
               __A						:			List[Any]								=	FeaturesManager.determine_framework(self.test_model)
               self.assertEqual(_UpperCAmelCase						,     self.framework_tf)

          # Both in environment -> use PyTorch
          __A						:			Any								=	MagicMock(return_value=_UpperCAmelCase)
          __A						:			Dict								=	MagicMock(return_value=_UpperCAmelCase)
          with patch('transformers.onnx.features.is_tf_available'						,     _UpperCAmelCase), patch(
              'transformers.onnx.features.is_torch_available'						,     _UpperCAmelCase):
               __A						:			int								=	FeaturesManager.determine_framework(self.test_model)
               self.assertEqual(_UpperCAmelCase						,     self.framework_pt)

          # Both not in environment -> raise error
          __A						:			List[str]								=	MagicMock(return_value=_UpperCAmelCase)
          __A						:			Tuple								=	MagicMock(return_value=_UpperCAmelCase)
          with patch('transformers.onnx.features.is_tf_available'						,     _UpperCAmelCase), patch(
              'transformers.onnx.features.is_torch_available'						,     _UpperCAmelCase):
               with self.assertRaises(_UpperCAmelCase):
                    __A						:			int								=	FeaturesManager.determine_framework(self.test_model)