

from __future__ import absolute_import, division, print_function, unicode_literals

from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss

from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.roberta.modeling_roberta import (
    ROBERTA_INPUTS_DOCSTRING,
    ROBERTA_START_DOCSTRING,
    RobertaEmbeddings,
)

from .modeling_highway_bert import BertPreTrainedModel, DeeBertModel, HighwayException, entropy






@add_start_docstrings(
    'The RoBERTa Model transformer with early exiting (DeeRoBERTa). '							,	__lowercase							,	)
class _UpperCamelCase							(							__lowercase   ):
			'''simple docstring'''







			lowerCamelCase__           =RobertaConfig
			lowerCamelCase__           ='roberta'
			def __init__(			self							: Union[str, Any]      ,      a							: List[Any]	)							->       Union[str, Any]:

				"""simple docstring"""

				super().__init__(__A	)

				SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       RobertaEmbeddings(__A	)
				self.init_weights()






@add_start_docstrings(
    'RoBERTa Model (with early exiting - DeeRoBERTa) with a classifier on top,\n    also takes care of multi-layer training. '							,	__lowercase							,	)
class _UpperCamelCase							(							__lowercase   ):
			'''simple docstring'''







			lowerCamelCase__           =RobertaConfig
			lowerCamelCase__           ='roberta'
			def __init__(			self							: Tuple      ,      a							: List[str]	)							->       Dict:

				"""simple docstring"""

				super().__init__(__A	)
				SCREAMING_SNAKE_CASE   :      Any				     =       config.num_labels
				SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       config.num_hidden_layers

				SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       DeeRobertaModel(__A	)
				SCREAMING_SNAKE_CASE   :      int				     =       nn.Dropout(config.hidden_dropout_prob	)
				SCREAMING_SNAKE_CASE   :      Dict				     =       nn.Linear(config.hidden_size      ,      self.config.num_labels	)






			@add_start_docstrings_to_model_forward(__A	)
			def 							__UpperCamelCase (			self							: Optional[int]      ,      a							: int=None      ,      a							: Union[str, Any]=None      ,      a							: Optional[int]=None      ,      a							: Union[str, Any]=None      ,      a							: Optional[Any]=None      ,      a							: Tuple=None      ,      a							: Tuple=None      ,      a							: Optional[Any]=-1      ,      a							: List[str]=False      ,      )							->       str:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      List[Any]				     =       self.num_layers
				try:
					SCREAMING_SNAKE_CASE   :      List[str]				     =       self.roberta(
					    __A      ,      attention_mask=__A      ,      token_type_ids=__A      ,      position_ids=__A      ,      head_mask=__A      ,      inputs_embeds=__A      ,      )

					SCREAMING_SNAKE_CASE   :      int				     =       outputs[1]

					SCREAMING_SNAKE_CASE   :      int				     =       self.dropout(__A	)
					SCREAMING_SNAKE_CASE   :      List[str]				     =       self.classifier(__A	)
					SCREAMING_SNAKE_CASE   :      Tuple				     =       (logits,) + outputs[2:]  # add hidden states and attention if they are here
				except HighwayException as e:
					SCREAMING_SNAKE_CASE   :      Dict				     =       e.message
					SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       e.exit_layer
					SCREAMING_SNAKE_CASE   :      Any				     =       outputs[0]

				if not self.training:
					SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       entropy(__A	)
					SCREAMING_SNAKE_CASE   :      List[str]				     =       []
					SCREAMING_SNAKE_CASE   :      str				     =       []
				if labels is not None:
					if self.num_labels == 1:
						#  We are doing regression
						SCREAMING_SNAKE_CASE   :      str				     =       MSELoss()
						SCREAMING_SNAKE_CASE   :      Optional[int]				     =       loss_fct(logits.view(-1	)      ,      labels.view(-1	)	)
					else:
						SCREAMING_SNAKE_CASE   :      str				     =       CrossEntropyLoss()
						SCREAMING_SNAKE_CASE   :      str				     =       loss_fct(logits.view(-1      ,      self.num_labels	)      ,      labels.view(-1	)	)

					# work with highway exits
					SCREAMING_SNAKE_CASE   :      int				     =       []
					for highway_exit in outputs[-1]:
						SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       highway_exit[0]
						if not self.training:
							highway_logits_all.append(__A	)
							highway_entropy.append(highway_exit[2]	)
						if self.num_labels == 1:
							#  We are doing regression
							SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       MSELoss()
							SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       loss_fct(highway_logits.view(-1	)      ,      labels.view(-1	)	)
						else:
							SCREAMING_SNAKE_CASE   :      str				     =       CrossEntropyLoss()
							SCREAMING_SNAKE_CASE   :      List[str]				     =       loss_fct(highway_logits.view(-1      ,      self.num_labels	)      ,      labels.view(-1	)	)
						highway_losses.append(__A	)

					if train_highway:
						SCREAMING_SNAKE_CASE   :      str				     =       (sum(highway_losses[:-1]	),) + outputs
						# exclude the final highway, of course
					else:
						SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       (loss,) + outputs
				if not self.training:
					SCREAMING_SNAKE_CASE   :      Any				     =       outputs + ((original_entropy, highway_entropy), exit_layer)
					if output_layer >= 0:
						SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       (
						    (outputs[0],) + (highway_logits_all[output_layer],) + outputs[2:]
						)  # use the highway of the last layer

				return outputs  # (loss), logits, (hidden_states), (attentions), entropy





from collections.abc import Iterable
from typing import Any






class _UpperCamelCase							:
			'''simple docstring'''







			def __init__(			self							: Tuple      ,      a							: int | None = None	)							->       List[Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      Any				     =       value
				SCREAMING_SNAKE_CASE   :      Node | None				     =       None  # Added in order to delete a node easier
				SCREAMING_SNAKE_CASE   :      Node | None				     =       None
				SCREAMING_SNAKE_CASE   :      Node | None				     =       None






			def __repr__(			self							: Optional[Any]	)							->       str:

				"""simple docstring"""

				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 _UpperCamelCase							:
			'''simple docstring'''







			def __init__(			self							: Optional[int]      ,      a							: Node | None = None	)							->       Union[str, Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      List[str]				     =       root
			def __str__(			self							: Any	)							->       str:

				"""simple docstring"""

				return str(self.root	)
			def 							__UpperCamelCase (			self							: List[str]      ,      a							: Node      ,      a							: Node | None	)							->       None:

				"""simple docstring"""

				if new_children is not None:  # reset its kids
					SCREAMING_SNAKE_CASE   :      Dict				     =       node.parent
				if node.parent is not None:  # reset its parent
					if self.is_right(a	):  # If it is the right children
						SCREAMING_SNAKE_CASE   :      Dict				     =       new_children
					else:
						SCREAMING_SNAKE_CASE   :      Any				     =       new_children
				else:
					SCREAMING_SNAKE_CASE   :      List[Any]				     =       new_children
			def 							__UpperCamelCase (			self							: Optional[Any]      ,      a							: Node	)							->       bool:

				"""simple docstring"""

				if node.parent and node.parent.right:
					return node == node.parent.right
				return False
			def 							__UpperCamelCase (			self							: Union[str, Any]	)							->       bool:

				"""simple docstring"""

				return self.root is None
			def 							__UpperCamelCase (			self							: List[str]      ,      a							: int	)							->       None:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      Dict				     =       Node(a	)  # create a new Node
				if self.empty():  # if Tree is empty
					SCREAMING_SNAKE_CASE   :      Tuple				     =       new_node  # set its root
				else:  # Tree is not empty
					SCREAMING_SNAKE_CASE   :      Optional[int]				     =       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:
								SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       new_node  # We insert the new node in a leaf
								break
							else:
								SCREAMING_SNAKE_CASE   :      Any				     =       parent_node.left
						else:
							if parent_node.right is None:
								SCREAMING_SNAKE_CASE   :      str				     =       new_node
								break
							else:
								SCREAMING_SNAKE_CASE   :      Optional[int]				     =       parent_node.right
					SCREAMING_SNAKE_CASE   :      int				     =       parent_node
			def 							__UpperCamelCase (			self							: Any      ,      *a							: str	)							->       None:

				"""simple docstring"""

				for value in values:
					self.__insert(a	)
			def 							__UpperCamelCase (			self							: Tuple      ,      a							: List[Any]	)							->       Node | None:

				"""simple docstring"""

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

				"""simple docstring"""

				if node is None:
					if self.root is None:
						return None
					SCREAMING_SNAKE_CASE   :      Tuple				     =       self.root

				if not self.empty():
					while node.right is not None:
						SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       node.right
				return node
			def 							__UpperCamelCase (			self							: int      ,      a							: Node | None = None	)							->       Node | None:

				"""simple docstring"""

				if node is None:
					SCREAMING_SNAKE_CASE   :      List[Any]				     =       self.root
				if self.root is None:
					return None
				if not self.empty():
					SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       self.root
					while node.left is not None:
						SCREAMING_SNAKE_CASE   :      str				     =       node.left
				return node
			def 							__UpperCamelCase (			self							: Dict      ,      a							: int	)							->       None:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      Dict				     =       self.search(a	)  # 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(a      ,      a	)
					elif node.left is None:  # Has only right children
						self.__reassign_nodes(a      ,      node.right	)
					elif node.right is None:  # Has only left children
						self.__reassign_nodes(a      ,      node.left	)
					else:
						SCREAMING_SNAKE_CASE   :      Tuple				     =       self.get_max(
						    node.left	)  # Gets the max value of the left branch
						self.remove(tmp_node.value	)  # type: ignore
						SCREAMING_SNAKE_CASE   :      str				     =       (
						    tmp_node.value  # type: ignore
						)  # Assigns the value to the node to delete and keep tree structure
			def 							__UpperCamelCase (			self							: List[Any]      ,      a							: Node | None	)							->       Iterable:

				"""simple docstring"""

				if node is not None:
					yield node  # Preorder Traversal
					yield from self.preorder_traverse(node.left	)
					yield from self.preorder_traverse(node.right	)
			def 							__UpperCamelCase (			self							: str      ,      a							: Union[str, Any]=None	)							->       Any:

				"""simple docstring"""

				if traversal_function is None:
					return self.preorder_traverse(self.root	)
				else:
					return traversal_function(self.root	)
			def 							__UpperCamelCase (			self							: Optional[Any]      ,      a							: list      ,      a							: Node | None	)							->       None:

				"""simple docstring"""

				if node:
					self.inorder(a      ,      node.left	)
					arr.append(node.value	)
					self.inorder(a      ,      node.right	)






			def 							__UpperCamelCase (			self							: int      ,      a							: int      ,      a							: Node	)							->       int:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE   :      list[int]				     =       []
				self.inorder(a      ,      a	)  # append all values to list using inorder traversal
				return arr[k - 1]

def  lowerCamelCase__ (					_a):
	SCREAMING_SNAKE_CASE   :      int				     =       []
	if curr_node is not None:
		SCREAMING_SNAKE_CASE   :      List[str]				     =       postorder(curr_node.left) + postorder(curr_node.right) + [curr_node]
	return node_list

def  lowerCamelCase__ (					):
	SCREAMING_SNAKE_CASE   :      int				     =       (8, 3, 6, 1, 10, 14, 13, 4, 7)
	SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       BinarySearchTree()
	for i in testlist:
		t.insert(_a)

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

	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(_a)
		print(_a)


if __name__ == "__main__":
			import doctest

			doctest.testmod(verbose=True)