
"""simple docstring"""







import json
import os
import shutil
import tempfile
import unittest

from transformers.models.wavaveca import WavaVecaCTCTokenizer, WavaVecaFeatureExtractor, WavaVecaProcessor
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.utils import FEATURE_EXTRACTOR_NAME

from .test_feature_extraction_wavaveca import floats_list



class 		UpperCAmelCase_	(unittest.TestCase						):
 """simple docstring"""




 def   a      ( self       : Optional[int] )->					List[str]:



      """simple docstring"""

      UpperCAmelCase_						:    List[Any]    					=  """<pad> <s> </s> <unk> | E T A O N I H S R D L U M W C F G Y P B V K ' X J Q Z""".split(""" """ )
      UpperCAmelCase_						:    Any    					=  dict(zip(lowerCamelCase__     ,   range(len(lowerCamelCase__ ) ) ) )

      UpperCAmelCase_						:    str    					=  {
          """pad_token""": """<pad>""",
          """unk_token""": """<unk>""",
          """bos_token""": """<s>""",
          """eos_token""": """</s>""",
      }
      UpperCAmelCase_						:    int    					=  {
          """feature_size""": 1,
          """padding_value""": 0.0,
          """sampling_rate""": 1_60_00,
          """return_attention_mask""": False,
          """do_normalize""": True,
      }

      UpperCAmelCase_						:    str    					=  tempfile.mkdtemp()
      UpperCAmelCase_						:    int    					=  os.path.join(self.tmpdirname     ,   VOCAB_FILES_NAMES["""vocab_file"""] )
      UpperCAmelCase_						:    List[Any]    					=  os.path.join(self.tmpdirname     ,   lowerCamelCase__ )
      with open(self.vocab_file     ,   """w"""     ,   encoding="""utf-8""" ) as fp:
           fp.write(json.dumps(lowerCamelCase__ ) + """\n""" )

      with open(self.feature_extraction_file     ,   """w"""     ,   encoding="""utf-8""" ) as fp:
           fp.write(json.dumps(lowerCamelCase__ ) + """\n""" )




 def   a      ( self       : Union[str, Any]     ,   **a_       : List[str] )->					Optional[Any]:



      """simple docstring"""

      UpperCAmelCase_						:    str    					=  self.add_kwargs_tokens_map.copy()
      kwargs.update(lowerCamelCase__ )
      return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname     ,   **lowerCamelCase__ )




 def   a      ( self       : Optional[Any]     ,   **a_       : Optional[int] )->					Optional[Any]:



      """simple docstring"""

      return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname     ,   **lowerCamelCase__ )




 def   a      ( self       : Any )->					List[str]:



      """simple docstring"""

      shutil.rmtree(self.tmpdirname )




 def   a      ( self       : Optional[Any] )->					Optional[int]:



      """simple docstring"""

      UpperCAmelCase_						:    Any    					=  self.get_tokenizer()
      UpperCAmelCase_						:    List[Any]    					=  self.get_feature_extractor()

      UpperCAmelCase_						:    Optional[Any]    					=  WavaVecaProcessor(tokenizer=lowerCamelCase__     ,   feature_extractor=lowerCamelCase__ )

      processor.save_pretrained(self.tmpdirname )
      UpperCAmelCase_						:    Optional[int]    					=  WavaVecaProcessor.from_pretrained(self.tmpdirname )

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

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




 def   a      ( self       : Dict )->					Optional[int]:



      """simple docstring"""

      UpperCAmelCase_						:    Union[str, Any]    					=  WavaVecaProcessor(tokenizer=self.get_tokenizer()     ,   feature_extractor=self.get_feature_extractor() )
      processor.save_pretrained(self.tmpdirname )

      UpperCAmelCase_						:    Dict    					=  self.get_tokenizer(bos_token="""(BOS)"""     ,   eos_token="""(EOS)""" )
      UpperCAmelCase_						:    Optional[Any]    					=  self.get_feature_extractor(do_normalize=lowerCamelCase__     ,   padding_value=1.0 )

      UpperCAmelCase_						:    Optional[Any]    					=  WavaVecaProcessor.from_pretrained(
          self.tmpdirname     ,   bos_token="""(BOS)"""     ,   eos_token="""(EOS)"""     ,   do_normalize=lowerCamelCase__     ,   padding_value=1.0 )

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

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




 def   a      ( self       : Union[str, Any] )->					Dict:



      """simple docstring"""

      UpperCAmelCase_						:    Dict    					=  self.get_feature_extractor()
      UpperCAmelCase_						:    Dict    					=  self.get_tokenizer()

      UpperCAmelCase_						:    Dict    					=  WavaVecaProcessor(tokenizer=lowerCamelCase__     ,   feature_extractor=lowerCamelCase__ )

      UpperCAmelCase_						:    Optional[Any]    					=  floats_list((3, 10_00) )

      UpperCAmelCase_						:    Dict    					=  feature_extractor(lowerCamelCase__     ,   return_tensors="""np""" )
      UpperCAmelCase_						:    Union[str, Any]    					=  processor(lowerCamelCase__     ,   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   a      ( self       : List[str] )->					List[str]:



      """simple docstring"""

      UpperCAmelCase_						:    List[str]    					=  self.get_feature_extractor()
      UpperCAmelCase_						:    Union[str, Any]    					=  self.get_tokenizer()

      UpperCAmelCase_						:    Any    					=  WavaVecaProcessor(tokenizer=lowerCamelCase__     ,   feature_extractor=lowerCamelCase__ )

      UpperCAmelCase_						:    Optional[Any]    					=  """This is a test string"""

      UpperCAmelCase_						:    Optional[Any]    					=  processor(text=lowerCamelCase__ )

      UpperCAmelCase_						:    Optional[int]    					=  tokenizer(lowerCamelCase__ )

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




 def   a      ( self       : int )->					int:



      """simple docstring"""

      UpperCAmelCase_						:    Optional[int]    					=  self.get_feature_extractor()
      UpperCAmelCase_						:    Optional[Any]    					=  self.get_tokenizer()

      UpperCAmelCase_						:    Optional[Any]    					=  WavaVecaProcessor(tokenizer=lowerCamelCase__     ,   feature_extractor=lowerCamelCase__ )

      UpperCAmelCase_						:    Tuple    					=  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

      UpperCAmelCase_						:    Tuple    					=  processor.batch_decode(lowerCamelCase__ )
      UpperCAmelCase_						:    List[Any]    					=  tokenizer.batch_decode(lowerCamelCase__ )

      self.assertListEqual(lowerCamelCase__     ,   lowerCamelCase__ )






 def   a      ( self       : Optional[Any] )->					Optional[int]:



      """simple docstring"""

      UpperCAmelCase_						:    Optional[Any]    					=  self.get_feature_extractor()
      UpperCAmelCase_						:    List[Any]    					=  self.get_tokenizer()

      UpperCAmelCase_						:    Tuple    					=  WavaVecaProcessor(tokenizer=lowerCamelCase__     ,   feature_extractor=lowerCamelCase__ )

      self.assertListEqual(
          processor.model_input_names     ,   feature_extractor.model_input_names     ,   msg="""`processor` and `feature_extractor` model input names do not match"""     ,   )



"""simple docstring"""







import warnings

from .generation import FlaxGenerationMixin



class 		UpperCAmelCase_	(lowerCamelCase_						):
 """simple docstring"""




 warnings.warn(
     """Importing `FlaxGenerationMixin` from `src/transformers/generation_flax_utils.py` is deprecated and will """
     """be removed in Transformers v5. Import as `from transformers import FlaxGenerationMixin` instead."""  , lowerCamelCase_  , )

