






'''simple docstring'''







class _lowercase	:




							def __init__(							self:				str			,							UpperCamelCase__:				str = ""			,							UpperCamelCase__:				bool = False     ):
														# Mapping from the first character of the prefix of the node
														lowerCamelCase__					:	dict[str, RadixNode]         =       {}

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

														lowerCamelCase__					:	Optional[Any]         =       prefix




							def 		lowerCamelCase_				(							self:				int			,							UpperCamelCase__:				str     ):
														lowerCamelCase__					:	Tuple         =       0
														for q, w in zip(self.prefix			,							UpperCamelCase__     ):
																					if q != w:
																												break

																					x += 1

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




							def 		lowerCamelCase_				(							self:				Optional[int]			,							UpperCamelCase__:				list[str]     ):
														for word in words:
																					self.insert(UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				str			,							UpperCamelCase__:				str     ):
														# Case 1: If the word is the prefix of the node
														# Solution: We set the current node as leaf
														if self.prefix == word:
																					lowerCamelCase__					:	List[str]         =       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:
																					lowerCamelCase__					:	Dict         =       RadixNode(prefix=UpperCamelCase__			,							is_leaf=UpperCamelCase__     )

														else:
																					lowerCamelCase__					:	List[Any]         =       self.nodes[word[0]]
																					lowerCamelCase__  ,		lowerCamelCase__  ,		lowerCamelCase__					:	List[Any]         =       incoming_node.match(
																					    UpperCamelCase__     )

																					# 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(UpperCamelCase__     )

																					# 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:
																												lowerCamelCase__					:	Optional[int]         =       remaining_prefix

																												lowerCamelCase__					:	Union[str, Any]         =       self.nodes[matching_string[0]]
																												lowerCamelCase__					:	List[str]         =       RadixNode(UpperCamelCase__			,							UpperCamelCase__     )
																												lowerCamelCase__					:	Any         =       aux_node

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




							def 		lowerCamelCase_				(							self:				List[Any]			,							UpperCamelCase__:				str     ):
														lowerCamelCase__					:	Optional[Any]         =       self.nodes.get(word[0]			,							UpperCamelCase__     )
														if not incoming_node:
																					return False
														else:
																					lowerCamelCase__  ,		lowerCamelCase__  ,		lowerCamelCase__					:	Tuple         =       incoming_node.match(
																					    UpperCamelCase__     )
																					# 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(UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				Any			,							UpperCamelCase__:				str     ):
														lowerCamelCase__					:	List[str]         =       self.nodes.get(word[0]			,							UpperCamelCase__     )
														if not incoming_node:
																					return False
														else:
																					lowerCamelCase__  ,		lowerCamelCase__  ,		lowerCamelCase__					:	List[str]         =       incoming_node.match(
																					    UpperCamelCase__     )
																					# 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(UpperCamelCase__     )
																					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:
																																																	lowerCamelCase__					:	Dict         =       list(self.nodes.values()     )[0]
																																																	lowerCamelCase__					:	List[Any]         =       merging_node.is_leaf
																																																	self.prefix += merging_node.prefix
																																																	lowerCamelCase__					:	List[Any]         =       merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
																																			elif len(incoming_node.nodes     ) > 1:
																																										lowerCamelCase__					:	Any         =       False
																																			# If there is 1 edge, we merge it with its child
																																			else:
																																										lowerCamelCase__					:	Dict         =       list(incoming_node.nodes.values()     )[0]
																																										lowerCamelCase__					:	List[Any]         =       merging_node.is_leaf
																																										incoming_node.prefix += merging_node.prefix
																																										lowerCamelCase__					:	Optional[int]         =       merging_node.nodes

																																			return True




							def 		lowerCamelCase_				(							self:				Union[str, Any]			,							UpperCamelCase__:				int = 0     ):
														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  SCREAMING_SNAKE_CASE_       ()      ->       bool:
							lowerCamelCase__					:	Optional[Any]         =       """banana bananas bandana band apple all beast""".split()
							lowerCamelCase__					:	Any         =       RadixNode()
							root.insert_many(UpperCamelCase      )

							assert all(root.find(UpperCamelCase      ) 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  SCREAMING_SNAKE_CASE_       ()      ->       None:
							assert test_trie()





def  SCREAMING_SNAKE_CASE_       ()      ->       None:
							lowerCamelCase__					:	int         =       RadixNode()
							lowerCamelCase__					:	Optional[int]         =       """banana bananas bandanas bandana band apple all beast""".split()
							root.insert_many(UpperCamelCase      )

							print("""Words:"""				,			UpperCamelCase      )
							print("""Tree:"""      )
							root.print_tree()


if __name__ == "__main__":
			main()









'''simple docstring'''







import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
			from PIL import Image

			from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor

@require_tokenizers
@require_vision
class _lowercase	(				unittest.TestCase		):




							def 		lowerCamelCase_				(							self:				Dict     ):
														lowerCamelCase__					:	int         =       tempfile.mkdtemp()

														# fmt: off
														lowerCamelCase__					:	int         =       ["""[UNK]""", """[CLS]""", """[SEP]""", """[PAD]""", """[MASK]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing""", """,""", """low""", """lowest"""]
														# fmt: on
														lowerCamelCase__					:	Union[str, Any]         =       os.path.join(self.tmpdirname			,							VOCAB_FILES_NAMES["""vocab_file"""]     )
														with open(self.vocab_file			,							"""w"""			,							encoding="""utf-8"""     ) as vocab_writer:
																					vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]     )     )

														lowerCamelCase__					:	Tuple         =       {
														    """do_resize""": True,
														    """size""": {"""height""": 18, """width""": 18},
														    """do_normalize""": True,
														    """image_mean""": [0.5, 0.5, 0.5],
														    """image_std""": [0.5, 0.5, 0.5],
														}
														lowerCamelCase__					:	Tuple         =       os.path.join(self.tmpdirname			,							UpperCamelCase__     )
														with open(self.image_processor_file			,							"""w"""			,							encoding="""utf-8"""     ) as fp:
																					json.dump(UpperCamelCase__			,							UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				str			,							**UpperCamelCase__:				List[str]     ):
														return BertTokenizer.from_pretrained(self.tmpdirname			,							**UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				int			,							**UpperCamelCase__:				Tuple     ):
														return ViTImageProcessor.from_pretrained(self.tmpdirname			,							**UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				Optional[Any]     ):
														shutil.rmtree(self.tmpdirname     )




							def 		lowerCamelCase_				(							self:				Any     ):
														lowerCamelCase__					:	List[Any]         =       [np.random.randint(255			,							size=(3, 30, 400)			,							dtype=np.uinta     )]

														lowerCamelCase__					:	Tuple         =       [Image.fromarray(np.moveaxis(UpperCamelCase__			,							0			,							-1     )     ) for x in image_inputs]

														return image_inputs




							def 		lowerCamelCase_				(							self:				int     ):
														lowerCamelCase__					:	Optional[Any]         =       self.get_tokenizer()
														lowerCamelCase__					:	Dict         =       self.get_image_processor()

														lowerCamelCase__					:	Optional[Any]         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														processor.save_pretrained(self.tmpdirname     )
														lowerCamelCase__					:	int         =       VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname     )

														self.assertEqual(processor.tokenizer.get_vocab()			,							tokenizer.get_vocab()     )
														self.assertIsInstance(processor.tokenizer			,							(BertTokenizer, BertTokenizerFast)     )

														self.assertEqual(processor.image_processor.to_json_string()			,							image_processor.to_json_string()     )
														self.assertIsInstance(processor.image_processor			,							UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				Tuple     ):
														lowerCamelCase__					:	Dict         =       VisionTextDualEncoderProcessor(
														    tokenizer=self.get_tokenizer()			,							image_processor=self.get_image_processor()     )
														processor.save_pretrained(self.tmpdirname     )

														lowerCamelCase__					:	int         =       self.get_tokenizer(bos_token="""(BOS)"""			,							eos_token="""(EOS)"""     )
														lowerCamelCase__					:	List[Any]         =       self.get_image_processor(do_normalize=UpperCamelCase__			,							padding_value=1.0     )

														lowerCamelCase__					:	Tuple         =       VisionTextDualEncoderProcessor.from_pretrained(
														    self.tmpdirname			,							bos_token="""(BOS)"""			,							eos_token="""(EOS)"""			,							do_normalize=UpperCamelCase__			,							padding_value=1.0     )

														self.assertEqual(processor.tokenizer.get_vocab()			,							tokenizer_add_kwargs.get_vocab()     )
														self.assertIsInstance(processor.tokenizer			,							(BertTokenizer, BertTokenizerFast)     )

														self.assertEqual(processor.image_processor.to_json_string()			,							image_processor_add_kwargs.to_json_string()     )
														self.assertIsInstance(processor.image_processor			,							UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				Union[str, Any]     ):
														lowerCamelCase__					:	Optional[Any]         =       self.get_image_processor()
														lowerCamelCase__					:	Union[str, Any]         =       self.get_tokenizer()

														lowerCamelCase__					:	Any         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														lowerCamelCase__					:	List[Any]         =       self.prepare_image_inputs()

														lowerCamelCase__					:	List[str]         =       image_processor(UpperCamelCase__			,							return_tensors="""np"""     )
														lowerCamelCase__					:	Optional[Any]         =       processor(images=UpperCamelCase__			,							return_tensors="""np"""     )

														for key in input_feat_extract.keys():
																					self.assertAlmostEqual(input_feat_extract[key].sum()			,							input_processor[key].sum()			,							delta=1e-2     )




							def 		lowerCamelCase_				(							self:				Optional[int]     ):
														lowerCamelCase__					:	Any         =       self.get_image_processor()
														lowerCamelCase__					:	List[str]         =       self.get_tokenizer()

														lowerCamelCase__					:	List[Any]         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														lowerCamelCase__					:	List[Any]         =       """lower newer"""

														lowerCamelCase__					:	Union[str, Any]         =       processor(text=UpperCamelCase__     )

														lowerCamelCase__					:	Any         =       tokenizer(UpperCamelCase__     )

														for key in encoded_tok.keys():
																					self.assertListEqual(encoded_tok[key]			,							encoded_processor[key]     )




							def 		lowerCamelCase_				(							self:				Dict     ):
														lowerCamelCase__					:	Optional[Any]         =       self.get_image_processor()
														lowerCamelCase__					:	List[Any]         =       self.get_tokenizer()

														lowerCamelCase__					:	List[Any]         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														lowerCamelCase__					:	Any         =       """lower newer"""
														lowerCamelCase__					:	Dict         =       self.prepare_image_inputs()

														lowerCamelCase__					:	Tuple         =       processor(text=UpperCamelCase__			,							images=UpperCamelCase__     )

														self.assertListEqual(list(inputs.keys()     )			,							["""input_ids""", """token_type_ids""", """attention_mask""", """pixel_values"""]     )

														# test if it raises when no input is passed
														with self.assertRaises(UpperCamelCase__     ):
																					processor()




							def 		lowerCamelCase_				(							self:				int     ):
														lowerCamelCase__					:	List[str]         =       self.get_image_processor()
														lowerCamelCase__					:	List[str]         =       self.get_tokenizer()

														lowerCamelCase__					:	int         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														lowerCamelCase__					:	Dict         =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

														lowerCamelCase__					:	Union[str, Any]         =       processor.batch_decode(UpperCamelCase__     )
														lowerCamelCase__					:	Dict         =       tokenizer.batch_decode(UpperCamelCase__     )

														self.assertListEqual(UpperCamelCase__			,							UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				List[str]     ):
														lowerCamelCase__					:	Any         =       self.get_image_processor()
														lowerCamelCase__					:	Union[str, Any]         =       self.get_tokenizer()

														lowerCamelCase__					:	int         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														lowerCamelCase__					:	Optional[Any]         =       """lower newer"""
														lowerCamelCase__					:	str         =       self.prepare_image_inputs()

														lowerCamelCase__					:	int         =       processor(text=UpperCamelCase__			,							images=UpperCamelCase__     )

														self.assertListEqual(list(inputs.keys()     )			,							processor.model_input_names     )

