





from __future__ import annotations

import unittest

from transformers import DebertaVaConfig, 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 import (
			    TFDebertaVaForMaskedLM,
			    TFDebertaVaForQuestionAnswering,
			    TFDebertaVaForSequenceClassification,
			    TFDebertaVaForTokenClassification,
			    TFDebertaVaModel,
			)






class 					__A    :

			'''simple docstring'''







			def __init__(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase=1_3       ,  __lowerCAmelCase=7       ,  __lowerCAmelCase=True       ,  __lowerCAmelCase=True       ,  __lowerCAmelCase=True       ,  __lowerCAmelCase=True       ,  __lowerCAmelCase=9_9       ,  __lowerCAmelCase=3_2       ,  __lowerCAmelCase=2       ,  __lowerCAmelCase=4       ,  __lowerCAmelCase=3_7       ,  __lowerCAmelCase="gelu"       ,  __lowerCAmelCase=0.1       ,  __lowerCAmelCase=0.1       ,  __lowerCAmelCase=5_1_2       ,  __lowerCAmelCase=1_6       ,  __lowerCAmelCase=2       ,  __lowerCAmelCase=0.02       ,  __lowerCAmelCase=False       ,  __lowerCAmelCase=True       ,  __lowerCAmelCase="None"       ,  __lowerCAmelCase=3       ,  __lowerCAmelCase=4       ,  __lowerCAmelCase=None       ,  ):



				'''simple docstring'''







				lowerCamelCase__								=		parent
				lowerCamelCase__								=		batch_size
				lowerCamelCase__								=		seq_length
				lowerCamelCase__								=		is_training
				lowerCamelCase__								=		use_input_mask
				lowerCamelCase__								=		use_token_type_ids
				lowerCamelCase__								=		use_labels
				lowerCamelCase__								=		vocab_size
				lowerCamelCase__								=		hidden_size
				lowerCamelCase__								=		num_hidden_layers
				lowerCamelCase__								=		num_attention_heads
				lowerCamelCase__								=		intermediate_size
				lowerCamelCase__								=		hidden_act
				lowerCamelCase__								=		hidden_dropout_prob
				lowerCamelCase__								=		attention_probs_dropout_prob
				lowerCamelCase__								=		max_position_embeddings
				lowerCamelCase__								=		type_vocab_size
				lowerCamelCase__								=		type_sequence_label_size
				lowerCamelCase__								=		initializer_range
				lowerCamelCase__								=		num_labels
				lowerCamelCase__								=		num_choices
				lowerCamelCase__								=		relative_attention
				lowerCamelCase__								=		position_biased_input
				lowerCamelCase__								=		pos_att_type
				lowerCamelCase__								=		scope





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		ids_tensor([self.batch_size, self.seq_length]       ,  self.vocab_size							)

				lowerCamelCase__								=		None
				if self.use_input_mask:
					lowerCamelCase__								=		random_attention_mask([self.batch_size, self.seq_length]							)

				lowerCamelCase__								=		None
				if self.use_token_type_ids:
					lowerCamelCase__								=		ids_tensor([self.batch_size, self.seq_length]       ,  self.type_vocab_size							)

				lowerCamelCase__								=		None
				lowerCamelCase__								=		None
				lowerCamelCase__								=		None
				if self.use_labels:
					lowerCamelCase__								=		ids_tensor([self.batch_size]       ,  self.type_sequence_label_size							)
					lowerCamelCase__								=		ids_tensor([self.batch_size, self.seq_length]       ,  self.num_labels							)

				lowerCamelCase__								=		DebertaVaConfig(
				    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       ,  type_vocab_size=self.type_vocab_size       ,  relative_attention=self.relative_attention       ,  position_biased_input=self.position_biased_input       ,  initializer_range=self.initializer_range       ,  return_dict=__lowerCAmelCase       ,  )

				return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels





			def 		__lowerCamelCase				(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase							):



				'''simple docstring'''







				lowerCamelCase__								=		TFDebertaVaModel(config=__lowerCAmelCase							)
				lowerCamelCase__								=		{'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}

				lowerCamelCase__								=		[input_ids, input_mask]
				lowerCamelCase__								=		model(__lowerCAmelCase							)

				lowerCamelCase__								=		model(__lowerCAmelCase							)

				self.parent.assertEqual(result.last_hidden_state.shape       ,  (self.batch_size, self.seq_length, self.hidden_size)							)





			def 		__lowerCamelCase				(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase							):



				'''simple docstring'''







				lowerCamelCase__								=		TFDebertaVaForMaskedLM(config=__lowerCAmelCase							)
				lowerCamelCase__								=		{
				    '''input_ids''': input_ids,
				    '''attention_mask''': input_mask,
				    '''token_type_ids''': token_type_ids,
				}
				lowerCamelCase__								=		model(__lowerCAmelCase							)
				self.parent.assertEqual(result.logits.shape       ,  (self.batch_size, self.seq_length, self.vocab_size)							)





			def 		__lowerCamelCase				(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase							):



				'''simple docstring'''







				lowerCamelCase__								=		self.num_labels
				lowerCamelCase__								=		TFDebertaVaForSequenceClassification(config=__lowerCAmelCase							)
				lowerCamelCase__								=		{
				    '''input_ids''': input_ids,
				    '''attention_mask''': input_mask,
				    '''token_type_ids''': token_type_ids,
				}

				lowerCamelCase__								=		model(__lowerCAmelCase							)
				self.parent.assertEqual(result.logits.shape       ,  (self.batch_size, self.num_labels)							)





			def 		__lowerCamelCase				(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase							):



				'''simple docstring'''







				lowerCamelCase__								=		self.num_labels
				lowerCamelCase__								=		TFDebertaVaForTokenClassification(config=__lowerCAmelCase							)
				lowerCamelCase__								=		{
				    '''input_ids''': input_ids,
				    '''attention_mask''': input_mask,
				    '''token_type_ids''': token_type_ids,
				}
				lowerCamelCase__								=		model(__lowerCAmelCase							)
				self.parent.assertEqual(result.logits.shape       ,  (self.batch_size, self.seq_length, self.num_labels)							)





			def 		__lowerCamelCase				(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase       ,  __lowerCAmelCase							):



				'''simple docstring'''







				lowerCamelCase__								=		TFDebertaVaForQuestionAnswering(config=__lowerCAmelCase							)
				lowerCamelCase__								=		{
				    '''input_ids''': input_ids,
				    '''attention_mask''': input_mask,
				    '''token_type_ids''': token_type_ids,
				}

				lowerCamelCase__								=		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							):



				'''simple docstring'''







				lowerCamelCase__								=		self.prepare_config_and_inputs()
				(
				    (
				    lowerCamelCase__
				)				,	(
				    lowerCamelCase__
				)				,	(
				    lowerCamelCase__
				)				,	(
				    lowerCamelCase__
				)				,	(
				    lowerCamelCase__
				)				,	(
				    lowerCamelCase__
				)				,	(
				    lowerCamelCase__
				)				,	
				)								=		config_and_inputs
				lowerCamelCase__								=		{'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': input_mask}
				return config, inputs_dict






@require_tf
class 					__A    (    lowerCAmelCase			,				lowerCAmelCase			,				unittest.TestCase ):

			'''simple docstring'''







			lowerCAmelCase_							     =						(
			    (
			        TFDebertaVaModel,
			        TFDebertaVaForMaskedLM,
			        TFDebertaVaForQuestionAnswering,
			        TFDebertaVaForSequenceClassification,
			        TFDebertaVaForTokenClassification,
			    )
			    if is_tf_available()
			    else ()
			)
			lowerCAmelCase_							     =						(
			    {
			        """feature-extraction""": TFDebertaVaModel,
			        """fill-mask""": TFDebertaVaForMaskedLM,
			        """question-answering""": TFDebertaVaForQuestionAnswering,
			        """text-classification""": TFDebertaVaForSequenceClassification,
			        """token-classification""": TFDebertaVaForTokenClassification,
			        """zero-shot""": TFDebertaVaForSequenceClassification,
			    }
			    if is_tf_available()
			    else {}
			)

			lowerCAmelCase_							     =						False
			lowerCAmelCase_							     =						False





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		TFDebertaVaModelTester(self							)
				lowerCamelCase__								=		ConfigTester(self       ,  config_class=__lowerCAmelCase       ,  hidden_size=3_7							)





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				self.config_tester.run_common_tests()





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		self.model_tester.prepare_config_and_inputs()
				self.model_tester.create_and_check_model(*__lowerCAmelCase							)





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		self.model_tester.prepare_config_and_inputs()
				self.model_tester.create_and_check_for_masked_lm(*__lowerCAmelCase							)





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		self.model_tester.prepare_config_and_inputs()
				self.model_tester.create_and_check_for_question_answering(*__lowerCAmelCase							)





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		self.model_tester.prepare_config_and_inputs()
				self.model_tester.create_and_check_for_sequence_classification(*__lowerCAmelCase							)





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		self.model_tester.prepare_config_and_inputs()
				self.model_tester.create_and_check_for_token_classification(*__lowerCAmelCase							)





			@slow
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		TFDebertaVaModel.from_pretrained('''kamalkraj/deberta-v2-xlarge'''							)
				self.assertIsNotNone(__lowerCAmelCase							)






@require_tf
class 					__A    (    unittest.TestCase ):

			'''simple docstring'''







			@unittest.skip(reason='''Model not available yet'''							)
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				pass





			@slow
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		TFDebertaVaModel.from_pretrained('''kamalkraj/deberta-v2-xlarge'''							)
				lowerCamelCase__								=		tf.constant([[0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2]]							)
				lowerCamelCase__								=		tf.constant([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]							)
				lowerCamelCase__								=		model(__lowerCAmelCase       ,  attention_mask=__lowerCAmelCase							)[0]

				lowerCamelCase__								=		tf.constant(
				    [[[0.2356, 0.1948, 0.0369], [-0.1063, 0.3586, -0.5152], [-0.6399, -0.0259, -0.2525]]]							)
				tf.debugging.assert_near(output[:, 1:4, 1:4]       ,  __lowerCAmelCase       ,  atol=1E-4							)










def lowerCAmelCase__(__snake_case       ,__snake_case							)				->      float:







	'''simple docstring'''







	if mass < 0:
		raise ValueError('''The mass of a body cannot be negative'''							)
	return 0.5 * mass * abs(__snake_case							) * abs(__snake_case							)


if __name__ == "__main__":
			import doctest

			doctest.testmod(verbose=True)



