


'''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 	UpperCamelCase__					( unittest.TestCase	):



     """simple docstring"""






     @slow
     def a	( self   ):

            '''simple docstring'''

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

                          _lowerCAmelCase    :							Dict   			=       FlaxAutoModel.from_pretrained(snake_case__   )
                          self.assertIsNotNone(snake_case__   )
                          self.assertIsInstance(snake_case__      ,	snake_case__   )







     @slow
     def a	( self   ):

            '''simple docstring'''

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

                          _lowerCAmelCase    :							List[Any]   			=       FlaxAutoModel.from_pretrained(snake_case__   )
                          self.assertIsNotNone(snake_case__   )
                          self.assertIsInstance(snake_case__      ,	snake_case__   )







     @slow
     def a	( self   ):

            '''simple docstring'''

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

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

                   eval(**snake_case__   ).block_until_ready()







     @slow
     def a	( self   ):

            '''simple docstring'''

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

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

                   eval(**snake_case__   ).block_until_ready()







     def a	( self   ):

            '''simple docstring'''

            with self.assertRaisesRegex(
                snake_case__      ,	'bert-base is not a local folder and is not a valid model identifier'   ):
                   _lowerCAmelCase    :							Any   			=       FlaxAutoModel.from_pretrained('bert-base'   )







     def a	( self   ):

            '''simple docstring'''

            with self.assertRaisesRegex(
                snake_case__      ,	R'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'   ):
                   _lowerCAmelCase    :							Union[str, Any]   			=       FlaxAutoModel.from_pretrained(snake_case__      ,	revision='aaaaaa'   )







     def a	( self   ):

            '''simple docstring'''

            with self.assertRaisesRegex(
                snake_case__      ,	'hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack'      ,	):
                   _lowerCAmelCase    :							Tuple   			=       FlaxAutoModel.from_pretrained('hf-internal-testing/config-no-model'   )







     def a	( self   ):

            '''simple docstring'''

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





'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCAmelCase    :     str					=						logging.get_logger(__name__)

lowerCAmelCase    :     int					=						{
    """facebook/data2vec-text-base""": """https://huggingface.co/data2vec/resolve/main/config.json""",
}
class 	UpperCamelCase__					( SCREAMING_SNAKE_CASE_	):



     """simple docstring"""






     __magic_name__    			=    "data2vec-text"







     def __init__( self      ,	snake_case__=3_0522      ,	snake_case__=768      ,	snake_case__=12      ,	snake_case__=12      ,	snake_case__=3072      ,	snake_case__="gelu"      ,	snake_case__=0.1      ,	snake_case__=0.1      ,	snake_case__=512      ,	snake_case__=2      ,	snake_case__=0.02      ,	snake_case__=1E-12      ,	snake_case__=1      ,	snake_case__=0      ,	snake_case__=2      ,	snake_case__="absolute"      ,	snake_case__=True      ,	snake_case__=None      ,	**snake_case__      ,	):

            '''simple docstring'''

            super().__init__(pad_token_id=snake_case__      ,	bos_token_id=snake_case__      ,	eos_token_id=snake_case__      ,	**snake_case__   )

            _lowerCAmelCase    :							List[Any]   			=       vocab_size
            _lowerCAmelCase    :							Tuple   			=       hidden_size
            _lowerCAmelCase    :							Dict   			=       num_hidden_layers
            _lowerCAmelCase    :							int   			=       num_attention_heads
            _lowerCAmelCase    :							str   			=       hidden_act
            _lowerCAmelCase    :							Any   			=       intermediate_size
            _lowerCAmelCase    :							Any   			=       hidden_dropout_prob
            _lowerCAmelCase    :							Optional[int]   			=       attention_probs_dropout_prob
            _lowerCAmelCase    :							str   			=       max_position_embeddings
            _lowerCAmelCase    :							Any   			=       type_vocab_size
            _lowerCAmelCase    :							int   			=       initializer_range
            _lowerCAmelCase    :							List[str]   			=       layer_norm_eps
            _lowerCAmelCase    :							List[Any]   			=       position_embedding_type
            _lowerCAmelCase    :							str   			=       use_cache
            _lowerCAmelCase    :							Union[str, Any]   			=       classifier_dropout
class 	UpperCamelCase__					( SCREAMING_SNAKE_CASE_	):



     """simple docstring"""






     @property
     def a	( self   ):

            '''simple docstring'''

            if self.task == "multiple-choice":
                   _lowerCAmelCase    :							Union[str, Any]   			=       {0: 'batch', 1: 'choice', 2: 'sequence'}
            else:
                   _lowerCAmelCase    :							List[Any]   			=       {0: 'batch', 1: 'sequence'}
            return OrderedDict(
                [
                    ('input_ids', dynamic_axis),
                    ('attention_mask', dynamic_axis),
                ]   )

