


import unittest

from diffusers.models.unet_ad_blocks import *  # noqa F403
from diffusers.utils import torch_device

from .test_unet_blocks_common import UNetBlockTesterMixin






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    DownBlockaD  # noqa F405
       lowercase_				:			List[str]									=    """down"""
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           _lowercase :							str   	=	[-0.0_2_3_2, -0.9_8_6_9, 0.8_0_5_4, -0.0_6_3_7, -0.1_6_8_8, -1.4_2_6_4, 0.4_4_7_0, -1.3_3_9_4, 0.0_9_0_4]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Optional[Any]									=    ResnetDownsampleBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """down"""
       def     UpperCamelCase  (      self) ->     Any:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	[0.0_7_1_0, 0.2_4_1_0, -0.7_3_2_0, -1.0_7_5_7, -1.1_3_4_3, 0.3_5_4_0, -0.0_1_3_3, -0.2_5_7_6, 0.0_9_4_8]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Any									=    AttnDownBlockaD  # noqa F405
       lowercase_				:			Dict									=    """down"""
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	[0.0_6_3_6, 0.8_9_6_4, -0.6_2_3_4, -1.0_1_3_1, 0.0_8_4_4, 0.4_9_3_5, 0.3_4_3_7, 0.0_9_1_1, -0.2_9_5_7]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    CrossAttnDownBlockaD  # noqa F405
       lowercase_				:			Optional[int]									=    """down"""
       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase	,       _lowercase :							int   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							int   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							List[str]   	=	[0.2_2_3_8, -0.7_3_9_6, -0.2_2_5_5, -0.3_8_2_9, 0.1_9_2_5, 1.1_6_6_5, 0.0_6_0_3, -0.7_2_9_5, 0.1_9_8_3]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Dict									=    SimpleCrossAttnDownBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           return super().get_dummy_input(include_encoder_hidden_states=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           _lowercase	,       _lowercase :							Dict   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							Optional[Any]   	=	32
           return init_dict, inputs_dict




       @unittest.skipIf(torch_device == 'mps',   'MPS result is not consistent')
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           _lowercase :							Tuple   	=	[0.7_9_2_1, -0.0_9_9_2, -0.1_9_6_2, -0.7_6_9_5, -0.4_2_4_2, 0.7_8_0_4, 0.4_7_3_7, 0.2_7_6_5, 0.3_3_3_8]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    SkipDownBlockaD  # noqa F405
       lowercase_				:			Union[str, Any]									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           return super().get_dummy_input(include_skip_sample=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           _lowercase :							int   	=	[-0.0_8_4_5, -0.2_0_8_7, -0.2_4_6_5, 0.0_9_7_1, 0.1_9_0_0, -0.0_4_8_4, 0.2_6_6_4, 0.4_1_7_9, 0.5_0_6_9]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    AttnSkipDownBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           return super().get_dummy_input(include_skip_sample=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	[0.5_5_3_9, 0.1_6_0_9, 0.4_9_2_4, 0.0_5_3_7, -0.1_9_9_5, 0.4_0_5_0, 0.0_9_7_9, -0.2_7_2_1, -0.0_6_4_2]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    DownEncoderBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           return super().get_dummy_input(include_temb=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           _lowercase :							Dict   	=	{
               'in_channels': 32,
               'out_channels': 32,
           }
           _lowercase :							int   	=	self.dummy_input
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           _lowercase :							List[str]   	=	[1.1_1_0_2, 0.5_3_0_2, 0.4_8_7_2, -0.0_0_2_3, -0.8_0_4_2, 0.0_4_8_3, -0.3_4_8_9, -0.5_6_3_2, 0.7_6_2_6]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			int									=    AttnDownEncoderBlockaD  # noqa F405
       lowercase_				:			Tuple									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           return super().get_dummy_input(include_temb=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							Any   	=	{
               'in_channels': 32,
               'out_channels': 32,
           }
           _lowercase :							Optional[int]   	=	self.dummy_input
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	[0.8_9_6_6, -0.1_4_8_6, 0.8_5_6_8, 0.8_1_4_1, -0.9_0_4_6, -0.1_3_4_2, -0.0_9_7_2, -0.7_4_1_7, 0.1_5_3_8]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			int									=    UNetMidBlockaD  # noqa F405
       lowercase_				:			Optional[int]									=    """mid"""
       def     UpperCamelCase  (      self) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							int   	=	{
               'in_channels': 32,
               'temb_channels': 1_28,
           }
           _lowercase :							Optional[Any]   	=	self.dummy_input
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase :							Dict   	=	[-0.1_0_6_2, 1.7_2_4_8, 0.3_4_9_4, 1.4_5_6_9, -0.0_9_1_0, -1.2_4_2_1, -0.9_9_8_4, 0.6_7_3_6, 1.0_0_2_8]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Dict									=    UNetMidBlockaDCrossAttn  # noqa F405
       lowercase_				:			Dict									=    """mid"""
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase	,       _lowercase :							Union[str, Any]   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							Any   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							Dict   	=	[0.0_1_8_7, 2.4_2_2_0, 0.4_4_8_4, 1.1_2_0_3, -0.6_1_2_1, -1.5_1_2_2, -0.8_2_7_0, 0.7_8_5_1, 1.8_3_3_5]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[Any]									=    UNetMidBlockaDSimpleCrossAttn  # noqa F405
       lowercase_				:			Any									=    """mid"""
       @property
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           return super().get_dummy_input(include_encoder_hidden_states=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase	,       _lowercase :							str   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							List[str]   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							int   	=	[0.7_1_4_3, 1.9_9_7_4, 0.5_4_4_8, 1.3_9_7_7, 0.1_2_8_2, -1.1_2_3_7, -1.4_2_3_8, 0.5_5_3_0, 0.8_8_8_0]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[Any]									=    UpBlockaD  # noqa F405
       lowercase_				:			List[str]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase :							Any   	=	[-0.2_0_4_1, -0.4_1_6_5, -0.3_0_2_2, 0.0_0_4_1, -0.6_6_2_8, -0.7_0_5_3, 0.1_9_2_8, -0.0_3_2_5, 0.0_5_2_3]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[str]									=    ResnetUpsampleBlockaD  # noqa F405
       lowercase_				:			Optional[int]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           _lowercase :							List[Any]   	=	[0.2_2_8_7, 0.3_5_4_9, -0.1_3_4_6, 0.4_7_9_7, -0.1_7_1_5, -0.9_6_4_9, 0.7_3_0_5, -0.5_8_6_4, -0.6_2_4_4]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Dict									=    CrossAttnUpBlockaD  # noqa F405
       lowercase_				:			List[str]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase	,       _lowercase :							Union[str, Any]   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							Tuple   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							Dict   	=	[-0.1_4_0_3, -0.3_5_1_5, -0.0_4_2_0, -0.1_4_2_5, 0.3_1_6_7, 0.5_0_9_4, -0.2_1_8_1, 0.5_9_3_1, 0.5_5_8_2]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Optional[int]									=    SimpleCrossAttnUpBlockaD  # noqa F405
       lowercase_				:			List[Any]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     Any:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase,   include_encoder_hidden_states=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           _lowercase	,       _lowercase :							int   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							Dict   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase :							List[str]   	=	[0.2_6_4_5, 0.1_4_8_0, 0.0_9_0_9, 0.8_0_4_4, -0.9_7_5_8, -0.9_0_8_3, 0.0_9_9_4, -1.1_4_5_3, -0.7_4_0_2]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[str]									=    AttnUpBlockaD  # noqa F405
       lowercase_				:			Optional[int]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       @unittest.skipIf(torch_device == 'mps',   'MPS result is not consistent')
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	[0.0_9_7_9, 0.1_3_2_6, 0.0_0_2_1, 0.0_6_5_9, 0.2_2_4_9, 0.0_0_5_9, 0.1_1_3_2, 0.5_9_5_2, 0.1_0_3_3]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[str]									=    SkipUpBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	[-0.0_8_9_3, -0.1_2_3_4, -0.1_5_0_6, -0.0_3_3_2, 0.0_1_2_3, -0.0_2_1_1, 0.0_5_6_6, 0.0_1_4_3, 0.0_3_6_2]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			int									=    AttnSkipUpBlockaD  # noqa F405
       lowercase_				:			Any									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Tuple   	=	[0.0_3_6_1, 0.0_6_1_7, 0.2_7_8_7, -0.0_3_5_0, 0.0_3_4_2, 0.3_4_2_1, -0.0_8_4_3, 0.0_9_1_3, 0.3_0_1_5]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[str]									=    UpDecoderBlockaD  # noqa F405
       lowercase_				:			int									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           return super().get_dummy_input(include_temb=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	{'in_channels': 32, 'out_channels': 32}

           _lowercase :							Optional[Any]   	=	self.dummy_input
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           _lowercase :							List[Any]   	=	[0.4_4_0_4, 0.1_9_9_8, -0.9_8_8_6, -0.3_3_2_0, -0.3_1_2_8, -0.7_0_3_4, -0.6_9_5_5, -0.2_3_3_8, -0.3_1_3_7]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Any									=    AttnUpDecoderBlockaD  # noqa F405
       lowercase_				:			str									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           return super().get_dummy_input(include_temb=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Any:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	{'in_channels': 32, 'out_channels': 32}

           _lowercase :							List[Any]   	=	self.dummy_input
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	[0.6_7_3_8, 0.4_4_9_1, 0.1_0_5_5, 1.0_7_1_0, 0.7_3_1_6, 0.3_3_3_9, 0.3_3_5_2, 0.1_0_2_3, 0.3_5_6_8]
           super().test_output(lowerCamelCase)






import unittest

from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device

from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
 import torch

 from transformers import (
     DebertaVaForMaskedLM,
     DebertaVaForMultipleChoice,
     DebertaVaForQuestionAnswering,
     DebertaVaForSequenceClassification,
     DebertaVaForTokenClassification,
     DebertaVaModel,
 )
 from transformers.models.deberta_va.modeling_deberta_va import DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST






class _lowerCamelCase(		_a     ):
       def __init__(      self,   lowerCamelCase,   lowerCamelCase=13,   lowerCamelCase=7,   lowerCamelCase=True,   lowerCamelCase=True,   lowerCamelCase=True,   lowerCamelCase=True,   lowerCamelCase=99,   lowerCamelCase=32,   lowerCamelCase=5,   lowerCamelCase=4,   lowerCamelCase=37,   lowerCamelCase="gelu",   lowerCamelCase=0.1,   lowerCamelCase=0.1,   lowerCamelCase=5_12,   lowerCamelCase=16,   lowerCamelCase=2,   lowerCamelCase=0.0_2,   lowerCamelCase=False,   lowerCamelCase=True,   lowerCamelCase="None",   lowerCamelCase=3,   lowerCamelCase=4,   lowerCamelCase=None,   ) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	parent
           _lowercase :							Optional[Any]   	=	batch_size
           _lowercase :							Optional[Any]   	=	seq_length
           _lowercase :							Dict   	=	is_training
           _lowercase :							Optional[Any]   	=	use_input_mask
           _lowercase :							Optional[int]   	=	use_token_type_ids
           _lowercase :							str   	=	use_labels
           _lowercase :							List[Any]   	=	vocab_size
           _lowercase :							Dict   	=	hidden_size
           _lowercase :							Any   	=	num_hidden_layers
           _lowercase :							Union[str, Any]   	=	num_attention_heads
           _lowercase :							int   	=	intermediate_size
           _lowercase :							List[str]   	=	hidden_act
           _lowercase :							Tuple   	=	hidden_dropout_prob
           _lowercase :							Optional[Any]   	=	attention_probs_dropout_prob
           _lowercase :							int   	=	max_position_embeddings
           _lowercase :							Any   	=	type_vocab_size
           _lowercase :							Tuple   	=	type_sequence_label_size
           _lowercase :							List[Any]   	=	initializer_range
           _lowercase :							Optional[Any]   	=	num_labels
           _lowercase :							Tuple   	=	num_choices
           _lowercase :							Dict   	=	relative_attention
           _lowercase :							Optional[int]   	=	position_biased_input
           _lowercase :							str   	=	pos_att_type
           _lowercase :							Optional[Any]   	=	scope
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							int   	=	ids_tensor([self.batch_size, self.seq_length],   self.vocab_size)

           _lowercase :							Union[str, Any]   	=	None
           if self.use_input_mask:
               _lowercase :							int   	=	ids_tensor([self.batch_size, self.seq_length],   vocab_size=2)

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

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

           _lowercase :							Union[str, Any]   	=	self.get_config()

           return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           return 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,   initializer_range=self.initializer_range,   relative_attention=self.relative_attention,   position_biased_input=self.position_biased_input,   pos_att_type=self.pos_att_type,   )
       def     UpperCamelCase  (      self,   lowerCamelCase) ->     int:




           """simple docstring"""

           self.parent.assertListEqual(list(result.loss.size()),   [])
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							List[str]   	=	DebertaVaModel(config=lowerCamelCase)
           model.to(lowerCamelCase)
           model.eval()
           _lowercase :							int   	=	model(lowerCamelCase,   attention_mask=lowerCamelCase,   token_type_ids=lowerCamelCase)[0]
           _lowercase :							Optional[int]   	=	model(lowerCamelCase,   token_type_ids=lowerCamelCase)[0]
           _lowercase :							Dict   	=	model(lowerCamelCase)[0]

           self.parent.assertListEqual(list(sequence_output.size()),   [self.batch_size, self.seq_length, self.hidden_size])
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase) ->     List[Any]:




           """simple docstring"""

           _lowercase :							List[Any]   	=	DebertaVaForMaskedLM(config=lowerCamelCase)
           model.to(lowerCamelCase)
           model.eval()
           _lowercase :							str   	=	model(lowerCamelCase,   attention_mask=lowerCamelCase,   token_type_ids=lowerCamelCase,   labels=lowerCamelCase)

           self.parent.assertEqual(result.logits.shape,   (self.batch_size, self.seq_length, self.vocab_size))
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase) ->     List[str]:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	self.num_labels
           _lowercase :							Any   	=	DebertaVaForSequenceClassification(lowerCamelCase)
           model.to(lowerCamelCase)
           model.eval()
           _lowercase :							Any   	=	model(lowerCamelCase,   attention_mask=lowerCamelCase,   token_type_ids=lowerCamelCase,   labels=lowerCamelCase)
           self.parent.assertListEqual(list(result.logits.size()),   [self.batch_size, self.num_labels])
           self.check_loss_output(lowerCamelCase)
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	self.num_labels
           _lowercase :							Optional[int]   	=	DebertaVaForTokenClassification(config=lowerCamelCase)
           model.to(lowerCamelCase)
           model.eval()
           _lowercase :							Optional[Any]   	=	model(lowerCamelCase,   attention_mask=lowerCamelCase,   token_type_ids=lowerCamelCase,   labels=lowerCamelCase)
           self.parent.assertEqual(result.logits.shape,   (self.batch_size, self.seq_length, self.num_labels))
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	DebertaVaForQuestionAnswering(config=lowerCamelCase)
           model.to(lowerCamelCase)
           model.eval()
           _lowercase :							Union[str, Any]   	=	model(
               lowerCamelCase,   attention_mask=lowerCamelCase,   token_type_ids=lowerCamelCase,   start_positions=lowerCamelCase,   end_positions=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     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Any   	=	DebertaVaForMultipleChoice(config=lowerCamelCase)
           model.to(lowerCamelCase)
           model.eval()
           _lowercase :							Optional[int]   	=	input_ids.unsqueeze(1).expand(-1,   self.num_choices,   -1).contiguous()
           _lowercase :							List[Any]   	=	token_type_ids.unsqueeze(1).expand(-1,   self.num_choices,   -1).contiguous()
           _lowercase :							int   	=	input_mask.unsqueeze(1).expand(-1,   self.num_choices,   -1).contiguous()
           _lowercase :							str   	=	model(
               lowerCamelCase,   attention_mask=lowerCamelCase,   token_type_ids=lowerCamelCase,   labels=lowerCamelCase,   )
           self.parent.assertEqual(result.logits.shape,   (self.batch_size, self.num_choices))




       def     UpperCamelCase  (      self) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							Any   	=	self.prepare_config_and_inputs()
           (
               (
               _lowercase
           )	,       (
               _lowercase
           )	,       (
               _lowercase
           )	,       (
               _lowercase
           )	,       (
               _lowercase
           )	,       (
               _lowercase
           )	,       (
               _lowercase
           )	,       
           ) :							List[str]   	=	config_and_inputs
           _lowercase :							int   	=	{'input_ids': input_ids, 'token_type_ids': token_type_ids, 'attention_mask': input_mask}
           return config, inputs_dict






@require_torch
class _lowerCamelCase(		_a,				_a,				unittest.TestCase     ):
       lowercase_				:			Any									=    (
           (
               DebertaVaModel,
               DebertaVaForMaskedLM,
               DebertaVaForSequenceClassification,
               DebertaVaForTokenClassification,
               DebertaVaForQuestionAnswering,
               DebertaVaForMultipleChoice,
           )
           if is_torch_available()
           else ()
       )
       lowercase_				:			Any									=    (
           {
               """feature-extraction""": DebertaVaModel,
               """fill-mask""": DebertaVaForMaskedLM,
               """question-answering""": DebertaVaForQuestionAnswering,
               """text-classification""": DebertaVaForSequenceClassification,
               """token-classification""": DebertaVaForTokenClassification,
               """zero-shot""": DebertaVaForSequenceClassification,
           }
           if is_torch_available()
           else {}
       )

       lowercase_				:			int									=    True
       lowercase_				:			str									=    False
       lowercase_				:			str									=    False
       lowercase_				:			str									=    False
       lowercase_				:			List[Any]									=    False
       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							List[Any]   	=	DebertaVaModelTester(self)
           _lowercase :							List[Any]   	=	ConfigTester(self,   config_class=lowerCamelCase,   hidden_size=37)
       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           self.config_tester.run_common_tests()
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							Tuple   	=	self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_model(*lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							int   	=	self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_sequence_classification(*lowerCamelCase)
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_masked_lm(*lowerCamelCase)
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           _lowercase :							List[Any]   	=	self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_question_answering(*lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_token_classification(*lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							Tuple   	=	self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_multiple_choice(*lowerCamelCase)




       @slow
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           for model_name in DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
               _lowercase :							Dict   	=	DebertaVaModel.from_pretrained(lowerCamelCase)
               self.assertIsNotNone(lowerCamelCase)






@require_torch
@require_sentencepiece
@require_tokenizers
class _lowerCamelCase(		unittest.TestCase     ):
       @unittest.skip(reason='Model not available yet')
       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           pass




       @slow
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Dict   	=	DebertaVaModel.from_pretrained('microsoft/deberta-v2-xlarge')

           _lowercase :							str   	=	torch.tensor([[0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]])
           _lowercase :							Any   	=	torch.tensor([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])
           with torch.no_grad():
               _lowercase :							Tuple   	=	model(lowerCamelCase,   attention_mask=lowerCamelCase)[0]
           # compare the actual values for a slice.
           _lowercase :							int   	=	torch.tensor(
               [[[0.2_3_5_6, 0.1_9_4_8, 0.0_3_6_9], [-0.1_0_6_3, 0.3_5_8_6, -0.5_1_5_2], [-0.6_3_9_9, -0.0_2_5_9, -0.2_5_2_5]]])
           self.assertTrue(torch.allclose(output[:, 1:4, 1:4],   lowerCamelCase,   atol=1E-4),   F'''{output[:, 1:4, 1:4]}''')


