



import os
import sys
import unittest


_lowerCamelCase    :		Union[str, Any]		      =    os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))

import get_test_info  # noqa: E402
from get_test_info import (  # noqa: E402
    get_model_to_test_mapping,
    get_model_to_tester_mapping,
    get_test_to_tester_mapping,
)


_lowerCamelCase    :		List[Any]		      =    os.path.join("""tests""", """models""", """bert""", """test_modeling_bert.py""")
_lowerCamelCase    :		Union[str, Any]		      =    os.path.join("""tests""", """models""", """blip""", """test_modeling_blip.py""")


class 						lowercase    (							unittest.TestCase):
						'''simple docstring'''


						def       lowerCamelCase_				(  self    :				str	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     int						=				get_test_to_tester_mapping(snake_case	)
											SCREAMING_SNAKE_CASE							:     str						=				get_test_to_tester_mapping(snake_case	)

											SCREAMING_SNAKE_CASE							:     Dict						=				{'BertModelTest': 'BertModelTester'}

											SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				{
											    'BlipModelTest': 'BlipModelTester',
											    'BlipTextImageModelTest': 'BlipTextImageModelsModelTester',
											    'BlipTextModelTest': 'BlipTextModelTester',
											    'BlipTextRetrievalModelTest': 'BlipTextRetrievalModelTester',
											    'BlipVQAModelTest': 'BlipVQAModelTester',
											    'BlipVisionModelTest': 'BlipVisionModelTester',
											}

											self.assertEqual(get_test_info.to_json(snake_case	)       ,	snake_case	)
											self.assertEqual(get_test_info.to_json(snake_case	)       ,	snake_case	)







						def       lowerCamelCase_				(  self    :				Optional[int]	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Dict						=				get_model_to_test_mapping(snake_case	)
											SCREAMING_SNAKE_CASE							:     Tuple						=				get_model_to_test_mapping(snake_case	)

											SCREAMING_SNAKE_CASE							:     Any						=				{
											    'BertForMaskedLM': ['BertModelTest'],
											    'BertForMultipleChoice': ['BertModelTest'],
											    'BertForNextSentencePrediction': ['BertModelTest'],
											    'BertForPreTraining': ['BertModelTest'],
											    'BertForQuestionAnswering': ['BertModelTest'],
											    'BertForSequenceClassification': ['BertModelTest'],
											    'BertForTokenClassification': ['BertModelTest'],
											    'BertLMHeadModel': ['BertModelTest'],
											    'BertModel': ['BertModelTest'],
											}

											SCREAMING_SNAKE_CASE							:     Dict						=				{
											    'BlipForConditionalGeneration': ['BlipTextImageModelTest'],
											    'BlipForImageTextRetrieval': ['BlipTextRetrievalModelTest'],
											    'BlipForQuestionAnswering': ['BlipVQAModelTest'],
											    'BlipModel': ['BlipModelTest'],
											    'BlipTextModel': ['BlipTextModelTest'],
											    'BlipVisionModel': ['BlipVisionModelTest'],
											}

											self.assertEqual(get_test_info.to_json(snake_case	)       ,	snake_case	)
											self.assertEqual(get_test_info.to_json(snake_case	)       ,	snake_case	)







						def       lowerCamelCase_				(  self    :				List[str]	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				get_model_to_tester_mapping(snake_case	)
											SCREAMING_SNAKE_CASE							:     Any						=				get_model_to_tester_mapping(snake_case	)

											SCREAMING_SNAKE_CASE							:     Optional[int]						=				{
											    'BertForMaskedLM': ['BertModelTester'],
											    'BertForMultipleChoice': ['BertModelTester'],
											    'BertForNextSentencePrediction': ['BertModelTester'],
											    'BertForPreTraining': ['BertModelTester'],
											    'BertForQuestionAnswering': ['BertModelTester'],
											    'BertForSequenceClassification': ['BertModelTester'],
											    'BertForTokenClassification': ['BertModelTester'],
											    'BertLMHeadModel': ['BertModelTester'],
											    'BertModel': ['BertModelTester'],
											}

											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				{
											    'BlipForConditionalGeneration': ['BlipTextImageModelsModelTester'],
											    'BlipForImageTextRetrieval': ['BlipTextRetrievalModelTester'],
											    'BlipForQuestionAnswering': ['BlipVQAModelTester'],
											    'BlipModel': ['BlipModelTester'],
											    'BlipTextModel': ['BlipTextModelTester'],
											    'BlipVisionModel': ['BlipVisionModelTester'],
											}

											self.assertEqual(get_test_info.to_json(snake_case	)       ,	snake_case	)
											self.assertEqual(get_test_info.to_json(snake_case	)       ,	snake_case	)




from typing import Callable, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowerCamelCase    :		int		      =    logging.get_logger(__name__)

_lowerCamelCase    :		Union[str, Any]		      =    {
    """microsoft/xprophetnet-large-wiki100-cased""": (
        """https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json"""
    ),
}


class 						lowercase    (							SCREAMING_SNAKE_CASE_):
						'''simple docstring'''


						UpperCAmelCase			:		Tuple		=		'xlm-prophetnet'
						UpperCAmelCase			:		int		=		['past_key_values']
						UpperCAmelCase			:		List[Any]		=		{
						    'num_attention_heads': 'num_encoder_attention_heads',
						}







						def __init__(  self    :				List[Any]       ,	snake_case    :				Optional[float] = 0.1       ,	snake_case    :				Optional[Union[str, Callable]] = "gelu"       ,	snake_case    :				Optional[int] = 30522       ,	snake_case    :				Optional[int] = 1024       ,	snake_case    :				Optional[int] = 4096       ,	snake_case    :				Optional[int] = 12       ,	snake_case    :				Optional[int] = 16       ,	snake_case    :				Optional[int] = 4096       ,	snake_case    :				Optional[int] = 12       ,	snake_case    :				Optional[int] = 16       ,	snake_case    :				Optional[float] = 0.1       ,	snake_case    :				Optional[float] = 0.1       ,	snake_case    :				Optional[int] = 512       ,	snake_case    :				Optional[float] = 0.02       ,	snake_case    :				Optional[bool] = True       ,	snake_case    :				Optional[bool] = True       ,	snake_case    :				Optional[int] = 0       ,	snake_case    :				Optional[int] = 2       ,	snake_case    :				Optional[int] = 32       ,	snake_case    :				Optional[int] = 128       ,	snake_case    :				Optional[bool] = False       ,	snake_case    :				Optional[float] = 0.0       ,	snake_case    :				Optional[bool] = True       ,	snake_case    :				Optional[int] = 0       ,	snake_case    :				Optional[int] = 1       ,	snake_case    :				Optional[int] = 2       ,	**snake_case    :				Optional[int]       ,	):



											'''simple docstring'''


											SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				vocab_size
											SCREAMING_SNAKE_CASE							:     int						=				hidden_size
											SCREAMING_SNAKE_CASE							:     Dict						=				encoder_ffn_dim
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				num_encoder_layers
											SCREAMING_SNAKE_CASE							:     str						=				num_encoder_attention_heads
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				decoder_ffn_dim
											SCREAMING_SNAKE_CASE							:     Any						=				num_decoder_layers
											SCREAMING_SNAKE_CASE							:     List[str]						=				num_decoder_attention_heads
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				max_position_embeddings
											SCREAMING_SNAKE_CASE							:     Any						=				init_std  # Normal(0, this parameter)
											SCREAMING_SNAKE_CASE							:     List[str]						=				activation_function

											# parameters for xlmprophetnet
											SCREAMING_SNAKE_CASE							:     Tuple						=				ngram
											SCREAMING_SNAKE_CASE							:     Optional[int]						=				num_buckets
											SCREAMING_SNAKE_CASE							:     Any						=				relative_max_distance
											SCREAMING_SNAKE_CASE							:     Optional[int]						=				disable_ngram_loss
											SCREAMING_SNAKE_CASE							:     List[str]						=				eps

											# 3 Types of Dropout
											SCREAMING_SNAKE_CASE							:     Optional[Any]						=				attention_dropout
											SCREAMING_SNAKE_CASE							:     Any						=				activation_dropout
											SCREAMING_SNAKE_CASE							:     Optional[int]						=				dropout

											SCREAMING_SNAKE_CASE							:     Tuple						=				use_cache

											super().__init__(
											    pad_token_id=snake_case       ,	bos_token_id=snake_case       ,	eos_token_id=snake_case       ,	is_encoder_decoder=snake_case       ,	add_cross_attention=snake_case       ,	decoder_start_token_id=snake_case       ,	**snake_case       ,	)







						@property
						def       lowerCamelCase_				(  self    :				Optional[Any]	):



											'''simple docstring'''


											return self.num_encoder_layers + self.num_decoder_layers







						@num_hidden_layers.setter
						def       lowerCamelCase_				(  self    :				List[Any]       ,	snake_case    :				Optional[int]	):



											'''simple docstring'''


											raise NotImplementedError(
											    'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
											    ' `num_decoder_layers`.'	)