
from __future__ import annotations

import unittest

from transformers import MPNetConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
				import tensorflow as tf

				from transformers.models.mpnet.modeling_tf_mpnet import (
				    TFMPNetForMaskedLM,
				    TFMPNetForMultipleChoice,
				    TFMPNetForQuestionAnswering,
				    TFMPNetForSequenceClassification,
				    TFMPNetForTokenClassification,
				    TFMPNetModel,
				)







class 							UpperCAmelCase	:

					def __init__(			self      :					List[Any] ,      lowerCAmelCase      :					Optional[int] ,      lowerCAmelCase      :					Dict=13 ,      lowerCAmelCase      :					Optional[int]=7 ,      lowerCAmelCase      :					str=True ,      lowerCAmelCase      :					str=True ,      lowerCAmelCase      :					Dict=False ,      lowerCAmelCase      :					int=True ,      lowerCAmelCase      :					List[Any]=99 ,      lowerCAmelCase      :					List[Any]=64 ,      lowerCAmelCase      :					List[str]=2 ,      lowerCAmelCase      :					int=4 ,      lowerCAmelCase      :					Tuple=64 ,      lowerCAmelCase      :					Any="gelu" ,      lowerCAmelCase      :					Tuple=0.1 ,      lowerCAmelCase      :					List[Any]=0.1 ,      lowerCAmelCase      :					Optional[Any]=512 ,      lowerCAmelCase      :					Tuple=16 ,      lowerCAmelCase      :					Tuple=2 ,      lowerCAmelCase      :					Any=0.02 ,      lowerCAmelCase      :					str=3 ,      lowerCAmelCase      :					Optional[Any]=4 ,      lowerCAmelCase      :					List[str]=None ,      ):
											lowercase       :    Union[str, Any]											=  parent
											lowercase       :    Any											=  batch_size
											lowercase       :    List[Any]											=  seq_length
											lowercase       :    int											=  is_training
											lowercase       :    Optional[Any]											=  use_input_mask
											lowercase       :    Union[str, Any]											=  use_token_type_ids
											lowercase       :    Dict											=  use_labels
											lowercase       :    List[str]											=  vocab_size
											lowercase       :    int											=  hidden_size
											lowercase       :    List[str]											=  num_hidden_layers
											lowercase       :    int											=  num_attention_heads
											lowercase       :    Any											=  intermediate_size
											lowercase       :    Tuple											=  hidden_act
											lowercase       :    int											=  hidden_dropout_prob
											lowercase       :    Optional[int]											=  attention_probs_dropout_prob
											lowercase       :    Optional[int]											=  max_position_embeddings
											lowercase       :    List[str]											=  type_vocab_size
											lowercase       :    Optional[Any]											=  type_sequence_label_size
											lowercase       :    Tuple											=  initializer_range
											lowercase       :    int											=  num_labels
											lowercase       :    int											=  num_choices
											lowercase       :    List[str]											=  scope

					def        _lowerCAmelCase	(			self      :					List[str]					):
											lowercase       :    int											=  ids_tensor([self.batch_size, self.seq_length] ,      self.vocab_size					)

											lowercase       :    List[str]											=  None
											if self.use_input_mask:
																	lowercase       :    Union[str, Any]											=  random_attention_mask([self.batch_size, self.seq_length]					)

											lowercase       :    List[Any]											=  None
											lowercase       :    List[str]											=  None
											lowercase       :    Any											=  None
											if self.use_labels:
																	lowercase       :    Any											=  ids_tensor([self.batch_size] ,      self.type_sequence_label_size					)
																	lowercase       :    List[Any]											=  ids_tensor([self.batch_size, self.seq_length] ,      self.num_labels					)
																	lowercase       :    Tuple											=  ids_tensor([self.batch_size] ,      self.num_choices					)

											lowercase       :    Optional[int]											=  MPNetConfig(
											    vocab_size=self.vocab_size ,      hidden_size=self.hidden_size ,      num_hidden_layers=self.num_hidden_layers ,      num_attention_heads=self.num_attention_heads ,      intermediate_size=self.intermediate_size ,      hidden_act=self.hidden_act ,      hidden_dropout_prob=self.hidden_dropout_prob ,      attention_probs_dropout_prob=self.attention_probs_dropout_prob ,      max_position_embeddings=self.max_position_embeddings ,      initializer_range=self.initializer_range ,      )
											return config, input_ids, input_mask, sequence_labels, token_labels, choice_labels

					def        _lowerCAmelCase	(			self      :					Dict ,      lowerCAmelCase      :					Union[str, Any] ,      lowerCAmelCase      :					Any ,      lowerCAmelCase      :					Any ,      lowerCAmelCase      :					Any ,      lowerCAmelCase      :					Optional[Any] ,      lowerCAmelCase      :					List[str]					):
											lowercase       :    Dict											=  TFMPNetModel(config=lowerCAmelCase					)
											lowercase       :    Union[str, Any]											=  {'''input_ids''': input_ids, '''attention_mask''': input_mask}
											lowercase       :    str											=  model(lowerCAmelCase					)
											lowercase       :    Optional[int]											=  [input_ids, input_mask]
											lowercase       :    int											=  model(lowerCAmelCase					)
											self.parent.assertEqual(result.last_hidden_state.shape ,      (self.batch_size, self.seq_length, self.hidden_size)					)

					def        _lowerCAmelCase	(			self      :					Tuple ,      lowerCAmelCase      :					Optional[Any] ,      lowerCAmelCase      :					Optional[int] ,      lowerCAmelCase      :					List[Any] ,      lowerCAmelCase      :					Optional[Any] ,      lowerCAmelCase      :					Optional[Any] ,      lowerCAmelCase      :					str					):
											lowercase       :    Optional[int]											=  TFMPNetForMaskedLM(config=lowerCAmelCase					)
											lowercase       :    Dict											=  {'''input_ids''': input_ids, '''attention_mask''': input_mask}
											lowercase       :    Optional[Any]											=  model(lowerCAmelCase					)
											self.parent.assertEqual(result.logits.shape ,      (self.batch_size, self.seq_length, self.vocab_size)					)

					def        _lowerCAmelCase	(			self      :					str ,      lowerCAmelCase      :					Optional[Any] ,      lowerCAmelCase      :					List[str] ,      lowerCAmelCase      :					Any ,      lowerCAmelCase      :					Any ,      lowerCAmelCase      :					Any ,      lowerCAmelCase      :					Tuple					):
											lowercase       :    Tuple											=  TFMPNetForQuestionAnswering(config=lowerCAmelCase					)
											lowercase       :    List[str]											=  {
											    '''input_ids''': input_ids,
											    '''attention_mask''': input_mask,
											}
											lowercase       :    Dict											=  model(lowerCAmelCase					)
											self.parent.assertEqual(result.start_logits.shape ,      (self.batch_size, self.seq_length)					)
											self.parent.assertEqual(result.end_logits.shape ,      (self.batch_size, self.seq_length)					)

					def        _lowerCAmelCase	(			self      :					str ,      lowerCAmelCase      :					str ,      lowerCAmelCase      :					int ,      lowerCAmelCase      :					Optional[int] ,      lowerCAmelCase      :					Union[str, Any] ,      lowerCAmelCase      :					Optional[Any] ,      lowerCAmelCase      :					str					):
											lowercase       :    int											=  self.num_labels
											lowercase       :    List[str]											=  TFMPNetForSequenceClassification(lowerCAmelCase					)
											lowercase       :    List[Any]											=  {'''input_ids''': input_ids, '''attention_mask''': input_mask}
											lowercase       :    List[str]											=  model(lowerCAmelCase					)
											self.parent.assertEqual(result.logits.shape ,      (self.batch_size, self.num_labels)					)

					def        _lowerCAmelCase	(			self      :					int ,      lowerCAmelCase      :					Optional[Any] ,      lowerCAmelCase      :					Union[str, Any] ,      lowerCAmelCase      :					Optional[Any] ,      lowerCAmelCase      :					str ,      lowerCAmelCase      :					Tuple ,      lowerCAmelCase      :					Tuple					):
											lowercase       :    Optional[int]											=  self.num_choices
											lowercase       :    List[Any]											=  TFMPNetForMultipleChoice(lowerCAmelCase					)
											lowercase       :    str											=  tf.tile(tf.expand_dims(lowerCAmelCase ,      1					) ,      (1, self.num_choices, 1)					)
											lowercase       :    Tuple											=  tf.tile(tf.expand_dims(lowerCAmelCase ,      1					) ,      (1, self.num_choices, 1)					)
											lowercase       :    Any											=  {
											    '''input_ids''': multiple_choice_inputs_ids,
											    '''attention_mask''': multiple_choice_input_mask,
											}
											lowercase       :    List[Any]											=  model(lowerCAmelCase					)
											self.parent.assertEqual(result.logits.shape ,      (self.batch_size, self.num_choices)					)

					def        _lowerCAmelCase	(			self      :					List[str] ,      lowerCAmelCase      :					Optional[int] ,      lowerCAmelCase      :					Any ,      lowerCAmelCase      :					List[str] ,      lowerCAmelCase      :					Optional[int] ,      lowerCAmelCase      :					int ,      lowerCAmelCase      :					Any					):
											lowercase       :    List[str]											=  self.num_labels
											lowercase       :    Union[str, Any]											=  TFMPNetForTokenClassification(lowerCAmelCase					)
											lowercase       :    List[str]											=  {'''input_ids''': input_ids, '''attention_mask''': input_mask}
											lowercase       :    Tuple											=  model(lowerCAmelCase					)
											self.parent.assertEqual(result.logits.shape ,      (self.batch_size, self.seq_length, self.num_labels)					)




					def        _lowerCAmelCase	(			self      :					List[str]					):
											lowercase       :    int											=  self.prepare_config_and_inputs()
											((lowercase)				,				(lowercase)				,				(lowercase)				,				(lowercase)				,				(lowercase)				,				(lowercase))       :    int											=  config_and_inputs
											lowercase       :    List[str]											=  {'''input_ids''': input_ids, '''attention_mask''': input_mask}
											return config, inputs_dict







@require_tf
class 							UpperCAmelCase	(   __lowerCamelCase						, __lowerCamelCase						, unittest.TestCase					):
					a__: Optional[Any]			  =				(
					    (
					        TFMPNetForMaskedLM,
					        TFMPNetForMultipleChoice,
					        TFMPNetForQuestionAnswering,
					        TFMPNetForSequenceClassification,
					        TFMPNetForTokenClassification,
					        TFMPNetModel,
					    )
					    if is_tf_available()
					    else ()
					)
					a__: Tuple			  =				(
					    {
					        """feature-extraction""": TFMPNetModel,
					        """fill-mask""": TFMPNetForMaskedLM,
					        """question-answering""": TFMPNetForQuestionAnswering,
					        """text-classification""": TFMPNetForSequenceClassification,
					        """token-classification""": TFMPNetForTokenClassification,
					        """zero-shot""": TFMPNetForSequenceClassification,
					    }
					    if is_tf_available()
					    else {}
					)
					a__: Tuple			  =				False
					a__: Union[str, Any]			  =				False

					def        _lowerCAmelCase	(			self      :					str					):
											lowercase       :    Union[str, Any]											=  TFMPNetModelTester(self					)
											lowercase       :    Dict											=  ConfigTester(self ,      config_class=lowerCAmelCase ,      hidden_size=37					)

					def        _lowerCAmelCase	(			self      :					int					):
											self.config_tester.run_common_tests()

					def        _lowerCAmelCase	(			self      :					str					):
											lowercase       :    int											=  self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_mpnet_model(*lowerCAmelCase					)

					def        _lowerCAmelCase	(			self      :					Any					):
											lowercase       :    Tuple											=  self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_mpnet_for_masked_lm(*lowerCAmelCase					)

					def        _lowerCAmelCase	(			self      :					Union[str, Any]					):
											lowercase       :    List[str]											=  self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_mpnet_for_question_answering(*lowerCAmelCase					)

					def        _lowerCAmelCase	(			self      :					List[Any]					):
											lowercase       :    List[str]											=  self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_mpnet_for_sequence_classification(*lowerCAmelCase					)

					def        _lowerCAmelCase	(			self      :					Optional[int]					):
											lowercase       :    int											=  self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_mpnet_for_multiple_choice(*lowerCAmelCase					)

					def        _lowerCAmelCase	(			self      :					List[Any]					):
											lowercase       :    List[Any]											=  self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_mpnet_for_token_classification(*lowerCAmelCase					)




					@slow
					def        _lowerCAmelCase	(			self      :					List[str]					):
											for model_name in ["microsoft/mpnet-base"]:
																	lowercase       :    Optional[Any]											=  TFMPNetModel.from_pretrained(lowerCAmelCase					)
																	self.assertIsNotNone(lowerCAmelCase					)







@require_tf
class 							UpperCAmelCase	(   unittest.TestCase					):

					@slow
					def        _lowerCAmelCase	(			self      :					List[str]					):
											lowercase       :    Tuple											=  TFMPNetModel.from_pretrained('''microsoft/mpnet-base'''					)
											lowercase       :    Union[str, Any]											=  tf.constant([[0, 1, 2, 3, 4, 5]]					)
											lowercase       :    Optional[int]											=  model(lowerCAmelCase					)[0]

											lowercase       :    str											=  [1, 6, 768]
											self.assertEqual(output.shape ,      lowerCAmelCase					)

											lowercase       :    Any											=  tf.constant(
											    [
											        [
											            [-0.1_06_71_72, 0.08_21_64_73, 0.0_02_45_43],
											            [-0.03_46_58_79, 0.8_35_41_18, -0.03_25_22_88],
											            [-0.06_56_94_76, -0.12_42_41_11, -0.0_49_44_36],
											        ]
											    ]					)
											tf.debugging.assert_near(output[:, :3, :3] ,      lowerCAmelCase ,      atol=1E-4					)




class 							UpperCAmelCase	:

					def __init__(			self      :					Any ,      lowerCAmelCase      :					int					):
											lowercase       :    Tuple											=  data
											lowercase       :    BinaryTreeNode | None											=  None
											lowercase       :    BinaryTreeNode | None											=  None





def        lowerCamelCase_      (			UpperCAmelCase_							:				BinaryTreeNode | None							,			UpperCAmelCase_							:				int       ):
						if node is None:
												lowercase       :    Union[str, Any]											=  BinaryTreeNode(UpperCAmelCase_       )
												return node

						# binary search tree is not empty,
						# so we will insert it into the tree
						# if new_value is less than value of data in node,
						#  add it to left subtree and proceed recursively
						if new_value < node.data:
												lowercase       :    List[Any]											=  insert(node.left_child							,			UpperCAmelCase_       )
						else:
												# if new_value is greater than value of data in node,
												#  add it to right subtree and proceed recursively
												lowercase       :    Dict											=  insert(node.right_child							,			UpperCAmelCase_       )
						return node

def        lowerCamelCase_      (			UpperCAmelCase_							:				None | BinaryTreeNode       ):  # if node is None,return
						if node:
												lowercase       :    Optional[Any]											=  inorder(node.left_child       )
												lowercase       :    Tuple											=  [*inorder_array, node.data]
												lowercase       :    Optional[Any]											=  inorder_array + inorder(node.right_child       )
						else:
												lowercase       :    Optional[int]											=  []
						return inorder_array

def        lowerCamelCase_      (			):
						lowercase       :    Any											=  insert(UpperCAmelCase_							,			15       )
						insert(UpperCAmelCase_							,			10       )
						insert(UpperCAmelCase_							,			25       )
						insert(UpperCAmelCase_							,			6       )
						insert(UpperCAmelCase_							,			14       )
						insert(UpperCAmelCase_							,			20       )
						insert(UpperCAmelCase_							,			60       )
						return root

def        lowerCamelCase_      (			):
						# main function
						lowercase       :    Any											=  make_tree()
						print('''Printing values of binary search tree in Inorder Traversal.'''       )
						inorder(UpperCAmelCase_       )


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()


