
"""simple docstring"""


class 					lowerCAmelCase_					:



						'''simple docstring'''


						def __init__(			self  :   Union[str, Any]   )  -> None:
							A     = {}  # Mapping from char to TrieNode
							A     = False


						def     _SCREAMING_SNAKE_CASE   (			self  :   Optional[Any]	,A_  :   list[str]   )  -> None:
							for word in words:
								self.insert(A_   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   str	,A_  :   str   )  -> None:
							A     = self
							for char in word:
								if char not in curr.nodes:
									A     = TrieNode()
								A     = curr.nodes[char]
							A     = True


						def     _SCREAMING_SNAKE_CASE   (			self  :   Dict	,A_  :   str   )  -> bool:
							A     = self
							for char in word:
								if char not in curr.nodes:
									return False
								A     = curr.nodes[char]
							return curr.is_leaf




						def     _SCREAMING_SNAKE_CASE   (			self  :   Optional[int]	,A_  :   str   )  -> None:

							def _delete(A_  :   TrieNode	,A_  :   str	,A_  :   int   ) -> bool:
								if index == len(A_   ):
									# If word does not exist
									if not curr.is_leaf:
										return False
									A     = False
									return len(curr.nodes   ) == 0
								A     = word[index]
								A     = curr.nodes.get(A_   )
								# If char not in current trie node
								if not char_node:
									return False
								# Flag to check if node can be deleted
								A     = _delete(A_	,A_	,index + 1   )
								if delete_curr:
									del curr.nodes[char]
									return len(curr.nodes   ) == 0
								return delete_curr

							_delete(self	,A_	,0   )






def    _snake_case					(		snake_case__ :  TrieNode						,   snake_case__ :  str  ):
	if node.is_leaf:
		print(snake_case__						,   end=' '  )

	for key, value in node.nodes.items():
		print_words(snake_case__						,   word + key  )






def    _snake_case					(		):
	A     = 'banana bananas bandana band apple all beast'.split()
	A     = TrieNode()
	root.insert_many(snake_case__  )
	# print_words(root, "")
	assert all(root.find(snake_case__  ) for word in words  )
	assert root.find('banana'  )
	assert not root.find('bandanas'  )
	assert not root.find('apps'  )
	assert root.find('apple'  )
	assert root.find('all'  )
	root.delete('all'  )
	assert not root.find('all'  )
	root.delete('banana'  )
	assert not root.find('banana'  )
	assert root.find('bananas'  )
	return True






def    _snake_case					(		snake_case__ :  str						,   snake_case__ :  bool  ):
	print(str(snake_case__  )						,   'works!' if passes else 'doesn\'t work :('  )






def    _snake_case					(		):
	assert test_trie()






def    _snake_case					(		):
	print_results('Testing trie functionality'						,   test_trie()  )


if __name__ == "__main__":
		main()

"""simple docstring"""


from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType







class 					lowerCAmelCase_					(   _lowercase     ):



						'''simple docstring'''


						_lowerCamelCase:     List[str]   =     ['''image_processor''', '''tokenizer''']
						_lowerCamelCase:     Optional[int]   =     '''Pix2StructImageProcessor'''
						_lowerCamelCase:     Dict   =     ('''T5Tokenizer''', '''T5TokenizerFast''')


						def __init__(			self  :   Optional[int]	,A_  :   List[str]	,A_  :   Optional[int]   )  -> int:
							A     = False
							super().__init__(A_	,A_   )


						def __call__(			self  :   Any	,A_  :   List[str]=None	,A_  :   Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None	,A_  :   bool = True	,A_  :   Union[bool, str, PaddingStrategy] = False	,A_  :   Union[bool, str, TruncationStrategy] = None	,A_  :   Optional[int] = None	,A_  :   Optional[int] = 2048	,A_  :   int = 0	,A_  :   Optional[int] = None	,A_  :   Optional[bool] = None	,A_  :   bool = False	,A_  :   bool = False	,A_  :   bool = False	,A_  :   bool = False	,A_  :   bool = False	,A_  :   bool = True	,A_  :   Optional[Union[str, TensorType]] = None	,**A_  :   Tuple	,)  -> BatchEncoding:
							if images is None and text is None:
								raise ValueError('You have to specify either images or text.'   )

							# Get only text
							if images is None and not self.image_processor.is_vqa:
								A     = self.tokenizer
								A     = self.tokenizer(
								    text=A_	,add_special_tokens=A_	,padding=A_	,truncation=A_	,max_length=A_	,stride=A_	,pad_to_multiple_of=A_	,return_attention_mask=A_	,return_overflowing_tokens=A_	,return_special_tokens_mask=A_	,return_offsets_mapping=A_	,return_token_type_ids=A_	,return_length=A_	,verbose=A_	,return_tensors=A_	,**A_	,)
								return text_encoding

							if not self.image_processor.is_vqa:
								# add pixel_values
								A     = self.image_processor(
								    A_	,return_tensors=A_	,max_patches=A_	,**A_   )
							else:
								# add pixel_values and bbox
								A     = self.image_processor(
								    A_	,return_tensors=A_	,max_patches=A_	,header_text=A_	,**A_   )

							if text is not None and not self.image_processor.is_vqa:
								A     = self.tokenizer(
								    text=A_	,add_special_tokens=A_	,padding=A_	,truncation=A_	,max_length=A_	,stride=A_	,pad_to_multiple_of=A_	,return_attention_mask=A_	,return_overflowing_tokens=A_	,return_special_tokens_mask=A_	,return_offsets_mapping=A_	,return_token_type_ids=A_	,return_length=A_	,verbose=A_	,return_tensors=A_	,**A_	,)

								if "attention_mask" in text_encoding:
									A     = text_encoding.pop('attention_mask'   )
								if "input_ids" in text_encoding:
									A     = text_encoding.pop('input_ids'   )
							else:
								A     = None

							if text_encoding is not None:
								encoding_image_processor.update(A_   )

							return encoding_image_processor


						def     _SCREAMING_SNAKE_CASE   (			self  :   Optional[int]	,*A_  :   Optional[Any]	,**A_  :   Dict   )  -> Union[str, Any]:
							return self.tokenizer.batch_decode(*A_	,**A_   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   List[str]	,*A_  :   Tuple	,**A_  :   List[str]   )  -> Any:
							return self.tokenizer.decode(*A_	,**A_   )




						@property
						def     _SCREAMING_SNAKE_CASE   (			self  :   List[str]   )  -> Any:
							A     = self.tokenizer.model_input_names
							A     = self.image_processor.model_input_names
							return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names   )   )