
import enum
import warnings

from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_tf_available():
			import tensorflow as tf

			from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING

if is_torch_available():
			from ..models.auto.modeling_auto import MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING

_A     =  logging.get_logger(__name__)





class 			_lowerCAmelCase      (			enum.Enum ):
				_lowercase    	=0
				_lowercase    	=1





@add_end_docstrings(__a )
class 			_lowerCAmelCase      (			__a ):
				_lowercase    	='''generated'''




				def __init__(      self       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )       ->   Tuple:
							super().__init__(*_UpperCamelCase       ,       **_UpperCamelCase  )

							self.check_model_type(
							    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
							    if self.framework == "tf"
							    else MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING  )




				def   __a		(      self       ,       _UpperCamelCase=None       ,       _UpperCamelCase=None       ,       _UpperCamelCase=None       ,       _UpperCamelCase=None       ,       _UpperCamelCase=None       ,       _UpperCamelCase=None       ,       **_UpperCamelCase       ,       )       ->   Optional[Any]:
							lowerCAmelCase_      			=			{}
							if truncation is not None:
										lowerCAmelCase_      			=			truncation

							lowerCAmelCase_      			=			generate_kwargs

							lowerCAmelCase_      			=			{}
							if return_tensors is not None and return_type is None:
										lowerCAmelCase_      			=			ReturnType.TENSORS if return_tensors else ReturnType.TEXT
							if return_type is not None:
										lowerCAmelCase_      			=			return_type

							if clean_up_tokenization_spaces is not None:
										lowerCAmelCase_      			=			clean_up_tokenization_spaces

							if stop_sequence is not None:
										lowerCAmelCase_      			=			self.tokenizer.encode(_UpperCamelCase       ,       add_special_tokens=_UpperCamelCase  )
										if len(_UpperCamelCase  ) > 1:
													warnings.warn(
													    "Stopping on a multiple token sequence is not yet supported on transformers. The first token of"
													    " the stop sequence will be used as the stop sequence string in the interim."  )
										lowerCAmelCase_      			=			stop_sequence_ids[0]

							return preprocess_params, forward_params, postprocess_params




				def   __a		(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   Tuple:
							return True




				def   __a		(      self       ,       *_UpperCamelCase       ,       _UpperCamelCase  )       ->   List[Any]:
							lowerCAmelCase_      			=			self.model.config.prefix if self.model.config.prefix is not None else ""
							if isinstance(args[0]       ,       _UpperCamelCase  ):
										if self.tokenizer.pad_token_id is None:
													raise ValueError("Please make sure that the tokenizer has a pad_token_id when using a batch input"  )
										lowerCAmelCase_      			=			([prefix + arg for arg in args[0]],)
										lowerCAmelCase_      			=			True

							elif isinstance(args[0]       ,       _UpperCamelCase  ):
										lowerCAmelCase_      			=			(prefix + args[0],)
										lowerCAmelCase_      			=			False
							else:
										raise ValueError(
										    f""" `args[0]`: {args[0]} have the wrong format. The should be either of type `str` or type `list`"""  )
							lowerCAmelCase_      			=			self.tokenizer(*_UpperCamelCase       ,       padding=_UpperCamelCase       ,       truncation=_UpperCamelCase       ,       return_tensors=self.framework  )
							# This is produced by tokenizers but is an invalid generate kwargs
							if "token_type_ids" in inputs:
										del inputs["token_type_ids"]
							return inputs




				def __call__(      self       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )       ->   int:
							lowerCAmelCase_      			=			super().__call__(*_UpperCamelCase       ,       **_UpperCamelCase  )
							if (
							    isinstance(args[0]       ,       _UpperCamelCase  )
							    and all(isinstance(_UpperCamelCase       ,       _UpperCamelCase  ) for el in args[0]  )
							    and all(len(_UpperCamelCase  ) == 1 for res in result  )
							):
										return [res[0] for res in result]
							return result




				def   __a		(      self       ,       _UpperCamelCase       ,       _UpperCamelCase=TruncationStrategy.DO_NOT_TRUNCATE       ,       **_UpperCamelCase  )       ->   Optional[int]:
							lowerCAmelCase_      			=			self._parse_and_tokenize(_UpperCamelCase       ,       truncation=_UpperCamelCase       ,       **_UpperCamelCase  )
							return inputs




				def   __a		(      self       ,       _UpperCamelCase       ,       **_UpperCamelCase  )       ->   Any:
							if self.framework == "pt":
										lowerCAmelCase_			,						lowerCAmelCase_      			=			model_inputs["input_ids"].shape
							elif self.framework == "tf":
										lowerCAmelCase_			,						lowerCAmelCase_      			=			tf.shape(model_inputs["input_ids"]  ).numpy()

							lowerCAmelCase_      			=			generate_kwargs.get("min_length"       ,       self.model.config.min_length  )
							lowerCAmelCase_      			=			generate_kwargs.get("max_length"       ,       self.model.config.max_length  )
							self.check_inputs(_UpperCamelCase       ,       generate_kwargs["min_length"]       ,       generate_kwargs["max_length"]  )
							lowerCAmelCase_      			=			self.model.generate(**_UpperCamelCase       ,       **_UpperCamelCase  )
							lowerCAmelCase_      			=			output_ids.shape[0]
							if self.framework == "pt":
										lowerCAmelCase_      			=			output_ids.reshape(_UpperCamelCase       ,       out_b // in_b       ,       *output_ids.shape[1:]  )
							elif self.framework == "tf":
										lowerCAmelCase_      			=			tf.reshape(_UpperCamelCase       ,       (in_b, out_b // in_b, *output_ids.shape[1:])  )
							return {"output_ids": output_ids}




				def   __a		(      self       ,       _UpperCamelCase       ,       _UpperCamelCase=ReturnType.TEXT       ,       _UpperCamelCase=False  )       ->   List[Any]:
							lowerCAmelCase_      			=			[]
							for output_ids in model_outputs["output_ids"][0]:
										if return_type == ReturnType.TENSORS:
													lowerCAmelCase_      			=			{f"""{self.return_name}_token_ids""": output_ids}
										elif return_type == ReturnType.TEXT:
													lowerCAmelCase_      			=			{
													    f"""{self.return_name}_text""": self.tokenizer.decode(
													        _UpperCamelCase       ,       skip_special_tokens=_UpperCamelCase       ,       clean_up_tokenization_spaces=_UpperCamelCase       ,       )
													}
										records.append(_UpperCamelCase  )
							return records





@add_end_docstrings(__a )
class 			_lowerCAmelCase      (			__a ):
				_lowercase    	='''summary'''




				def __call__(      self       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )       ->   int:
							return super().__call__(*_UpperCamelCase       ,       **_UpperCamelCase  )




				def   __a		(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   bool:
							if max_length < min_length:
										logger.warning(f"""Your min_length={min_length} must be inferior than your max_length={max_length}."""  )

							if input_length < max_length:
										logger.warning(
										    f"""Your max_length is set to {max_length}, but your input_length is only {input_length}. Since this is """
										    "a summarization task, where outputs shorter than the input are typically wanted, you might "
										    f"""consider decreasing max_length manually, e.g. summarizer('...', max_length={input_length//2})"""  )





@add_end_docstrings(__a )
class 			_lowerCAmelCase      (			__a ):
				_lowercase    	='''translation'''




				def   __a		(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   Any:
							if input_length > 0.9 * max_length:
										logger.warning(
										    f"""Your input_length: {input_length} is bigger than 0.9 * max_length: {max_length}. You might consider """
										    "increasing your max_length manually, e.g. translator('...', max_length=400)"  )
							return True




				def   __a		(      self       ,       *_UpperCamelCase       ,       _UpperCamelCase=TruncationStrategy.DO_NOT_TRUNCATE       ,       _UpperCamelCase=None       ,       _UpperCamelCase=None  )       ->   int:
							if getattr(self.tokenizer       ,       "_build_translation_inputs"       ,       _UpperCamelCase  ):
										return self.tokenizer._build_translation_inputs(
										    *_UpperCamelCase       ,       return_tensors=self.framework       ,       truncation=_UpperCamelCase       ,       src_lang=_UpperCamelCase       ,       tgt_lang=_UpperCamelCase  )
							else:
										return super()._parse_and_tokenize(*_UpperCamelCase       ,       truncation=_UpperCamelCase  )




				def   __a		(      self       ,       _UpperCamelCase=None       ,       _UpperCamelCase=None       ,       **_UpperCamelCase  )       ->   Optional[int]:
							lowerCAmelCase_			,						lowerCAmelCase_			,						lowerCAmelCase_      			=			super()._sanitize_parameters(**_UpperCamelCase  )
							if src_lang is not None:
										lowerCAmelCase_      			=			src_lang
							if tgt_lang is not None:
										lowerCAmelCase_      			=			tgt_lang
							if src_lang is None and tgt_lang is None:
										# Backward compatibility, direct arguments use is preferred.
										lowerCAmelCase_      			=			kwargs.get("task"       ,       self.task  )
										lowerCAmelCase_      			=			task.split("_"  )
										if task and len(_UpperCamelCase  ) == 4:
													# translation, XX, to YY
													lowerCAmelCase_      			=			items[1]
													lowerCAmelCase_      			=			items[3]
							return preprocess_params, forward_params, postprocess_params




				def __call__(      self       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )       ->   List[str]:
							return super().__call__(*_UpperCamelCase       ,       **_UpperCamelCase  )





from collections.abc import Iterable
from typing import Any





class 			_lowerCAmelCase      :




				def __init__(      self       ,       _UpperCamelCase = None  )       ->   str:
							lowerCAmelCase_      			=			value
							lowerCAmelCase_      			=			None  # Added in order to delete a node easier
							lowerCAmelCase_      			=			None
							lowerCAmelCase_      			=			None




				def __repr__(      self  )       ->   str:
							from pprint import pformat

							if self.left is None and self.right is None:
										return str(self.value  )
							return pformat({f"""{self.value}""": (self.left, self.right)}       ,       indent=1  )





class 			_lowerCAmelCase      :




				def __init__(      self       ,       _UpperCamelCase = None  )       ->   Union[str, Any]:
							lowerCAmelCase_      			=			root




				def __str__(      self  )       ->   str:
							return str(self.root  )




				def   __a		(      self       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   None:
							if new_children is not None:  # reset its kids
										lowerCAmelCase_      			=			node.parent
							if node.parent is not None:  # reset its parent
										if self.is_right(_UpperCamelCase  ):  # If it is the right children
													lowerCAmelCase_      			=			new_children
										else:
													lowerCAmelCase_      			=			new_children
							else:
										lowerCAmelCase_      			=			new_children




				def   __a		(      self       ,       _UpperCamelCase  )       ->   bool:
							if node.parent and node.parent.right:
										return node == node.parent.right
							return False




				def   __a		(      self  )       ->   bool:
							return self.root is None




				def   __a		(      self       ,       _UpperCamelCase  )       ->   None:
							lowerCAmelCase_      			=			Node(_UpperCamelCase  )  # create a new Node
							if self.empty():  # if Tree is empty
										lowerCAmelCase_      			=			new_node  # set its root
							else:  # Tree is not empty
										lowerCAmelCase_      			=			self.root  # from root
										if parent_node is None:
													return
										while True:  # While we don't get to a leaf
													if value < parent_node.value:  # We go left
																if parent_node.left is None:
																			lowerCAmelCase_      			=			new_node  # We insert the new node in a leaf
																			break
																else:
																			lowerCAmelCase_      			=			parent_node.left
													else:
																if parent_node.right is None:
																			lowerCAmelCase_      			=			new_node
																			break
																else:
																			lowerCAmelCase_      			=			parent_node.right
										lowerCAmelCase_      			=			parent_node




				def   __a		(      self       ,       *_UpperCamelCase  )       ->   None:
							for value in values:
										self.__insert(_UpperCamelCase  )




				def   __a		(      self       ,       _UpperCamelCase  )       ->   Node | None:
							if self.empty():
										raise IndexError("Warning: Tree is empty! please use another."  )
							else:
										lowerCAmelCase_      			=			self.root
										# use lazy evaluation here to avoid NoneType Attribute error
										while node is not None and node.value is not value:
													lowerCAmelCase_      			=			node.left if value < node.value else node.right
										return node




				def   __a		(      self       ,       _UpperCamelCase = None  )       ->   Node | None:
							if node is None:
										if self.root is None:
													return None
										lowerCAmelCase_      			=			self.root

							if not self.empty():
										while node.right is not None:
													lowerCAmelCase_      			=			node.right
							return node




				def   __a		(      self       ,       _UpperCamelCase = None  )       ->   Node | None:
							if node is None:
										lowerCAmelCase_      			=			self.root
							if self.root is None:
										return None
							if not self.empty():
										lowerCAmelCase_      			=			self.root
										while node.left is not None:
													lowerCAmelCase_      			=			node.left
							return node




				def   __a		(      self       ,       _UpperCamelCase  )       ->   None:
							lowerCAmelCase_      			=			self.search(_UpperCamelCase  )  # Look for the node with that label
							if node is not None:
										if node.left is None and node.right is None:  # If it has no children
													self.__reassign_nodes(_UpperCamelCase       ,       _UpperCamelCase  )
										elif node.left is None:  # Has only right children
													self.__reassign_nodes(_UpperCamelCase       ,       node.right  )
										elif node.right is None:  # Has only left children
													self.__reassign_nodes(_UpperCamelCase       ,       node.left  )
										else:
													lowerCAmelCase_      			=			self.get_max(
													    node.left  )  # Gets the max value of the left branch
													self.remove(tmp_node.value  )  # type: ignore
													lowerCAmelCase_      			=			(
													    tmp_node.value  # type: ignore
													)  # Assigns the value to the node to delete and keep tree structure




				def   __a		(      self       ,       _UpperCamelCase  )       ->   Iterable:
							if node is not None:
										yield node  # Preorder Traversal
										yield from self.preorder_traverse(node.left  )
										yield from self.preorder_traverse(node.right  )




				def   __a		(      self       ,       _UpperCamelCase=None  )       ->   Any:
							if traversal_function is None:
										return self.preorder_traverse(self.root  )
							else:
										return traversal_function(self.root  )




				def   __a		(      self       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   None:
							if node:
										self.inorder(_UpperCamelCase       ,       node.left  )
										arr.append(node.value  )
										self.inorder(_UpperCamelCase       ,       node.right  )




				def   __a		(      self       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   int:
							lowerCAmelCase_      			=			[]
							self.inorder(_UpperCamelCase       ,       _UpperCamelCase  )  # append all values to list using inorder traversal
							return arr[k - 1]






def      lowerCamelCase__       (       __lowerCAmelCase						:						Node | None       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			[]
			if curr_node is not None:
						lowerCAmelCase_      			=			postorder(curr_node.left       ) + postorder(curr_node.right       ) + [curr_node]
			return node_list






def      lowerCamelCase__       (       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			(8, 3, 6, 1, 10, 14, 13, 4, 7)
			lowerCAmelCase_      			=			BinarySearchTree()
			for i in testlist:
						t.insert(__lowerCAmelCase       )

			# Prints all the elements of the list in order traversal
			print(__lowerCAmelCase       )

			if t.search(6       ) is not None:
						print("The value 6 exists"       )
			else:
						print("The value 6 doesn't exist"       )

			if t.search(-1       ) is not None:
						print("The value -1 exists"       )
			else:
						print("The value -1 doesn't exist"       )

			if not t.empty():
						print("Max Value: "					,							t.get_max().value       )  # type: ignore
						print("Min Value: "					,							t.get_min().value       )  # type: ignore

			for i in testlist:
						t.remove(__lowerCAmelCase       )
						print(__lowerCAmelCase       )


if __name__ == "__main__":
			import doctest

			doctest.testmod(verbose=True)



