
'''simple docstring'''




import warnings

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


lowercase			:				Optional[int]    		=			logging.get_logger(__name__)

lowercase			:				Any    		=			{
    'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}





class  A				(							__snake_case						):
     __magic_name__						=		'''mvp'''
     __magic_name__						=		['''past_key_values''']
     __magic_name__						=		{'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}





     def __init__(							self						,			SCREAMING_SNAKE_CASE=50267						,			SCREAMING_SNAKE_CASE=1024						,			SCREAMING_SNAKE_CASE=12						,			SCREAMING_SNAKE_CASE=4096						,			SCREAMING_SNAKE_CASE=16						,			SCREAMING_SNAKE_CASE=12						,			SCREAMING_SNAKE_CASE=4096						,			SCREAMING_SNAKE_CASE=16						,			SCREAMING_SNAKE_CASE=0.0						,			SCREAMING_SNAKE_CASE=0.0						,			SCREAMING_SNAKE_CASE="gelu"						,			SCREAMING_SNAKE_CASE=1024						,			SCREAMING_SNAKE_CASE=0.1						,			SCREAMING_SNAKE_CASE=0.0						,			SCREAMING_SNAKE_CASE=0.0						,			SCREAMING_SNAKE_CASE=0.02						,			SCREAMING_SNAKE_CASE=0.0						,			SCREAMING_SNAKE_CASE=False						,			SCREAMING_SNAKE_CASE=True						,			SCREAMING_SNAKE_CASE=1						,			SCREAMING_SNAKE_CASE=0						,			SCREAMING_SNAKE_CASE=2						,			SCREAMING_SNAKE_CASE=True						,			SCREAMING_SNAKE_CASE=2						,			SCREAMING_SNAKE_CASE=2						,			SCREAMING_SNAKE_CASE=False						,			SCREAMING_SNAKE_CASE=100						,			SCREAMING_SNAKE_CASE=800						,			**SCREAMING_SNAKE_CASE						,			) ->				List[str]:






         """simple docstring"""






         A       :   Tuple					=						vocab_size
         A       :   Tuple					=						max_position_embeddings
         A       :   Union[str, Any]					=						d_model
         A       :   Optional[Any]					=						encoder_ffn_dim
         A       :   Optional[Any]					=						encoder_layers
         A       :   List[str]					=						encoder_attention_heads
         A       :   Any					=						decoder_ffn_dim
         A       :   List[Any]					=						decoder_layers
         A       :   Optional[Any]					=						decoder_attention_heads
         A       :   Optional[int]					=						dropout
         A       :   Optional[Any]					=						attention_dropout
         A       :   List[str]					=						activation_dropout
         A       :   Union[str, Any]					=						activation_function
         A       :   Dict					=						init_std
         A       :   Optional[int]					=						encoder_layerdrop
         A       :   int					=						decoder_layerdrop
         A       :   Optional[int]					=						classifier_dropout
         A       :   List[str]					=						use_cache
         A       :   Tuple					=						encoder_layers
         A       :   Any					=						scale_embedding  # scale factor will be sqrt(d_model) if True
         A       :   Union[str, Any]					=						use_prompt
         A       :   Optional[Any]					=						prompt_length
         A       :   Tuple					=						prompt_mid_dim

         super().__init__(
             pad_token_id=SCREAMING_SNAKE_CASE						,			bos_token_id=SCREAMING_SNAKE_CASE						,			eos_token_id=SCREAMING_SNAKE_CASE						,			is_encoder_decoder=SCREAMING_SNAKE_CASE						,			decoder_start_token_id=SCREAMING_SNAKE_CASE						,			forced_eos_token_id=SCREAMING_SNAKE_CASE						,			**SCREAMING_SNAKE_CASE						,			)

         if self.forced_bos_token_id is None and kwargs.get('''force_bos_token_to_be_generated'''						,			SCREAMING_SNAKE_CASE	):
             A       :   Tuple					=						self.bos_token_id
             warnings.warn(
                 F'Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '
                 '''The config can simply be saved and uploaded again to be fixed.'''	)






'''simple docstring'''




import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
      import jax

      from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
      from transformers.models.bert.modeling_flax_bert import FlaxBertModel
      from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel





@require_flax
class  A				(							unittest.TestCase						):





     @slow
     def 				__lowerCAmelCase							(							self	) ->				List[Any]:






         """simple docstring"""






         for model_name in ["bert-base-cased", "bert-large-uncased"]:
             with self.subTest(SCREAMING_SNAKE_CASE	):
                 A       :   int					=						AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)

                 A       :   List[str]					=						FlaxAutoModel.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				int:






         """simple docstring"""






         for model_name in ["roberta-base", "roberta-large"]:
             with self.subTest(SCREAMING_SNAKE_CASE	):
                 A       :   Any					=						AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)

                 A       :   Any					=						FlaxAutoModel.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				Any:






         """simple docstring"""






         for model_name in ["bert-base-cased", "bert-large-uncased"]:
             A       :   Optional[int]					=						AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   List[str]					=						FlaxBertModel.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   Optional[Any]					=						tokenizer('''Do you support jax jitted function?'''						,			return_tensors=TensorType.JAX	)

             @jax.jit
             def eval(**SCREAMING_SNAKE_CASE	):
                 return model(**SCREAMING_SNAKE_CASE	)

             eval(**SCREAMING_SNAKE_CASE	).block_until_ready()





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






         """simple docstring"""






         for model_name in ["roberta-base", "roberta-large"]:
             A       :   List[str]					=						AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   Union[str, Any]					=						FlaxRobertaModel.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   int					=						tokenizer('''Do you support jax jitted function?'''						,			return_tensors=TensorType.JAX	)

             @jax.jit
             def eval(**SCREAMING_SNAKE_CASE	):
                 return model(**SCREAMING_SNAKE_CASE	)

             eval(**SCREAMING_SNAKE_CASE	).block_until_ready()





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






         """simple docstring"""






         with self.assertRaisesRegex(
             SCREAMING_SNAKE_CASE						,			'''bert-base is not a local folder and is not a valid model identifier'''	):
             A       :   List[Any]					=						FlaxAutoModel.from_pretrained('''bert-base'''	)





     def 				__lowerCAmelCase							(							self	) ->				Tuple:






         """simple docstring"""






         with self.assertRaisesRegex(
             SCREAMING_SNAKE_CASE						,			R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''	):
             A       :   Optional[int]					=						FlaxAutoModel.from_pretrained(SCREAMING_SNAKE_CASE						,			revision='''aaaaaa'''	)





     def 				__lowerCAmelCase							(							self	) ->				str:






         """simple docstring"""






         with self.assertRaisesRegex(
             SCREAMING_SNAKE_CASE						,			'''hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack'''						,			):
             A       :   List[str]					=						FlaxAutoModel.from_pretrained('''hf-internal-testing/config-no-model'''	)





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






         """simple docstring"""






         with self.assertRaisesRegex(SCREAMING_SNAKE_CASE						,			'''Use `from_pt=True` to load this model'''	):
             A       :   Any					=						FlaxAutoModel.from_pretrained('''hf-internal-testing/tiny-bert-pt-only'''	)




