


from collections import OrderedDict
from typing import Mapping

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


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

UpperCamelCase					:       str			    =     {
    """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json""",
    """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json""",
    """junnyu/roformer_chinese_char_small""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json"""
    ),
    """junnyu/roformer_chinese_char_base""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_discriminator""": (
        """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_generator""": (
        """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json"""
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}



class A__     ( A__  ):



  """simple docstring"""



  _lowercase									=		'roformer'

  def __init__( self			:  Union[str, Any]				,				lowerCamelCase__			:  List[Any]=50_000				,				lowerCamelCase__			:  Optional[int]=None				,				lowerCamelCase__			:  int=768				,				lowerCamelCase__			:  List[Any]=12				,				lowerCamelCase__			:  Dict=12				,				lowerCamelCase__			:  int=3_072				,				lowerCamelCase__			:  List[Any]="gelu"				,				lowerCamelCase__			:  Optional[int]=0.1				,				lowerCamelCase__			:  Union[str, Any]=0.1				,				lowerCamelCase__			:  Union[str, Any]=1_536				,				lowerCamelCase__			:  Dict=2				,				lowerCamelCase__			:  Union[str, Any]=0.02				,				lowerCamelCase__			:  List[str]=1E-12				,				lowerCamelCase__			:  Optional[Any]=0				,				lowerCamelCase__			:  Optional[int]=False				,				lowerCamelCase__			:  str=True				,				**lowerCamelCase__			:  str				,				):
        super().__init__(pad_token_id=lowerCamelCase__				,				**lowerCamelCase__       )

        a__	:  int     =   vocab_size
        a__	:  Optional[Any]     =   hidden_size if embedding_size is None else embedding_size
        a__	:  List[str]     =   hidden_size
        a__	:  Any     =   num_hidden_layers
        a__	:  Optional[int]     =   num_attention_heads
        a__	:  List[str]     =   hidden_act
        a__	:  Tuple     =   intermediate_size
        a__	:  Any     =   hidden_dropout_prob
        a__	:  Dict     =   attention_probs_dropout_prob
        a__	:  str     =   max_position_embeddings
        a__	:  Any     =   type_vocab_size
        a__	:  int     =   initializer_range
        a__	:  Optional[Any]     =   layer_norm_eps
        a__	:  Optional[int]     =   rotary_value
        a__	:  str     =   use_cache




class A__     ( A__  ):



  """simple docstring"""



  @property
  def    _UpperCamelCase( self			:  List[Any]       ):
        if self.task == "multiple-choice":
              a__	:  Union[str, Any]     =   {0: "batch", 1: "choice", 2: "sequence"}
        else:
              a__	:  List[str]     =   {0: "batch", 1: "sequence"}
        a__	:  Optional[int]     =   {0: "batch", 1: "sequence"}
        return OrderedDict(
            [
                ("input_ids", dynamic_axis),
                ("attention_mask", dynamic_axis),
                ("token_type_ids", dynamic_axis),
            ]       )








import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list





@require_torchaudio
@require_sentencepiece
class UpperCAmelCase_				( unittest.TestCase ):


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       '''laion/clap-htsat-unfused'''
       A_          =       tempfile.mkdtemp()


  def 						__UpperCAmelCase     (							self ,**__snake_case ):



       """simple docstring"""





       return RobertaTokenizer.from_pretrained(self.checkpoint ,**__snake_case )


  def 						__UpperCAmelCase     (							self ,**__snake_case ):



       """simple docstring"""





       return ClapFeatureExtractor.from_pretrained(self.checkpoint ,**__snake_case )


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       shutil.rmtree(self.tmpdirname )


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_tokenizer()
       A_          =       self.get_feature_extractor()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

       processor.save_pretrained(self.tmpdirname )
       A_          =       ClapProcessor.from_pretrained(self.tmpdirname )

       self.assertEqual(processor.tokenizer.get_vocab() ,tokenizer.get_vocab() )
       self.assertIsInstance(processor.tokenizer ,__snake_case )

       self.assertEqual(processor.feature_extractor.to_json_string() ,feature_extractor.to_json_string() )
       self.assertIsInstance(processor.feature_extractor ,__snake_case )


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       ClapProcessor(tokenizer=self.get_tokenizer() ,feature_extractor=self.get_feature_extractor() )
       processor.save_pretrained(self.tmpdirname )

       A_          =       self.get_tokenizer(bos_token='''(BOS)''' ,eos_token='''(EOS)''' )
       A_          =       self.get_feature_extractor(do_normalize=__snake_case ,padding_value=1.0 )

       A_          =       ClapProcessor.from_pretrained(
           self.tmpdirname ,bos_token='''(BOS)''' ,eos_token='''(EOS)''' ,do_normalize=__snake_case ,padding_value=1.0 )

       self.assertEqual(processor.tokenizer.get_vocab() ,tokenizer_add_kwargs.get_vocab() )
       self.assertIsInstance(processor.tokenizer ,__snake_case )

       self.assertEqual(processor.feature_extractor.to_json_string() ,feature_extractor_add_kwargs.to_json_string() )
       self.assertIsInstance(processor.feature_extractor ,__snake_case )


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_feature_extractor()
       A_          =       self.get_tokenizer()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

       A_          =       floats_list((3, 1_0_0_0) )

       A_          =       feature_extractor(__snake_case ,return_tensors='''np''' )
       A_          =       processor(audios=__snake_case ,return_tensors='''np''' )

       for key in input_feat_extract.keys():
            self.assertAlmostEqual(input_feat_extract[key].sum() ,input_processor[key].sum() ,delta=1E-2 )


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_feature_extractor()
       A_          =       self.get_tokenizer()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

       A_          =       '''This is a test string'''

       A_          =       processor(text=__snake_case )

       A_          =       tokenizer(__snake_case )

       for key in encoded_tok.keys():
            self.assertListEqual(encoded_tok[key] ,encoded_processor[key] )


  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_feature_extractor()
       A_          =       self.get_tokenizer()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

       A_          =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       A_          =       processor.batch_decode(__snake_case )
       A_          =       tokenizer.batch_decode(__snake_case )

       self.assertListEqual(__snake_case ,__snake_case )




  def 						__UpperCAmelCase     (							self ):



       """simple docstring"""





       A_          =       self.get_feature_extractor()
       A_          =       self.get_tokenizer()

       A_          =       ClapProcessor(tokenizer=__snake_case ,feature_extractor=__snake_case )

       self.assertListEqual(
           processor.model_input_names[2:] ,feature_extractor.model_input_names ,msg='''`processor` and `feature_extractor` model input names do not match''' ,)



