






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 					UpperCAmelCase		(       self				)       ->   Any:
          UpperCamelCase :int										=     '''<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 :str										=     dict(zip(SCREAMING_SNAKE_CASE_					,       range(len(SCREAMING_SNAKE_CASE_				)				)				)				)

          UpperCamelCase :List[Any]										=     {
              '''pad_token''': '''<pad>''',
              '''unk_token''': '''<unk>''',
              '''bos_token''': '''<s>''',
              '''eos_token''': '''</s>''',
          }
          UpperCamelCase :List[Any]										=     {
              '''feature_size''': 1,
              '''padding_value''': 0.0,
              '''sampling_rate''': 1_6000,
              '''return_attention_mask''': False,
              '''do_normalize''': True,
          }

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

          with open(self.feature_extraction_file					,       '''w'''					,       encoding='''utf-8'''				) as fp:
              fp.write(json.dumps(SCREAMING_SNAKE_CASE_				) + '''\n'''				)
      def 					UpperCAmelCase		(       self					,       **SCREAMING_SNAKE_CASE_				)       ->   List[Any]:
          UpperCamelCase :Dict										=     self.add_kwargs_tokens_map.copy()
          kwargs.update(SCREAMING_SNAKE_CASE_				)
          return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname					,       **SCREAMING_SNAKE_CASE_				)
      def 					UpperCAmelCase		(       self					,       **SCREAMING_SNAKE_CASE_				)       ->   List[Any]:
          return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname					,       **SCREAMING_SNAKE_CASE_				)
      def 					UpperCAmelCase		(       self				)       ->   int:
          shutil.rmtree(self.tmpdirname				)
      def 					UpperCAmelCase		(       self				)       ->   Union[str, Any]:
          UpperCamelCase :List[str]										=     self.get_tokenizer()
          UpperCamelCase :Tuple										=     self.get_feature_extractor()

          UpperCamelCase :Tuple										=     WavaVecaProcessor(tokenizer=SCREAMING_SNAKE_CASE_					,       feature_extractor=SCREAMING_SNAKE_CASE_				)

          processor.save_pretrained(self.tmpdirname				)
          UpperCamelCase :int										=     WavaVecaProcessor.from_pretrained(self.tmpdirname				)

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

          self.assertEqual(processor.feature_extractor.to_json_string()					,       feature_extractor.to_json_string()				)
          self.assertIsInstance(processor.feature_extractor					,       SCREAMING_SNAKE_CASE_				)
      def 					UpperCAmelCase		(       self				)       ->   str:
          UpperCamelCase :str										=     WavaVecaProcessor(tokenizer=self.get_tokenizer()					,       feature_extractor=self.get_feature_extractor()				)
          processor.save_pretrained(self.tmpdirname				)

          UpperCamelCase :Union[str, Any]										=     self.get_tokenizer(bos_token='''(BOS)'''					,       eos_token='''(EOS)'''				)
          UpperCamelCase :List[Any]										=     self.get_feature_extractor(do_normalize=SCREAMING_SNAKE_CASE_					,       padding_value=1.0				)

          UpperCamelCase :str										=     WavaVecaProcessor.from_pretrained(
              self.tmpdirname					,       bos_token='''(BOS)'''					,       eos_token='''(EOS)'''					,       do_normalize=SCREAMING_SNAKE_CASE_					,       padding_value=1.0				)

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

          self.assertEqual(processor.feature_extractor.to_json_string()					,       feature_extractor_add_kwargs.to_json_string()				)
          self.assertIsInstance(processor.feature_extractor					,       SCREAMING_SNAKE_CASE_				)
      def 					UpperCAmelCase		(       self				)       ->   Optional[int]:
          UpperCamelCase :Optional[int]										=     self.get_feature_extractor()
          UpperCamelCase :Optional[Any]										=     self.get_tokenizer()

          UpperCamelCase :int										=     WavaVecaProcessor(tokenizer=SCREAMING_SNAKE_CASE_					,       feature_extractor=SCREAMING_SNAKE_CASE_				)

          UpperCamelCase :Any										=     floats_list((3, 1000)				)

          UpperCamelCase :Any										=     feature_extractor(SCREAMING_SNAKE_CASE_					,       return_tensors='''np'''				)
          UpperCamelCase :Tuple										=     processor(SCREAMING_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				)       ->   Union[str, Any]:
          UpperCamelCase :str										=     self.get_feature_extractor()
          UpperCamelCase :Tuple										=     self.get_tokenizer()

          UpperCamelCase :List[Any]										=     WavaVecaProcessor(tokenizer=SCREAMING_SNAKE_CASE_					,       feature_extractor=SCREAMING_SNAKE_CASE_				)

          UpperCamelCase :str										=     '''This is a test string'''

          UpperCamelCase :Union[str, Any]										=     processor(text=SCREAMING_SNAKE_CASE_				)

          UpperCamelCase :Union[str, Any]										=     tokenizer(SCREAMING_SNAKE_CASE_				)

          for key in encoded_tok.keys():
              self.assertListEqual(encoded_tok[key]					,       encoded_processor[key]				)
      def 					UpperCAmelCase		(       self				)       ->   int:
          UpperCamelCase :Union[str, Any]										=     self.get_feature_extractor()
          UpperCamelCase :Dict										=     self.get_tokenizer()

          UpperCamelCase :Tuple										=     WavaVecaProcessor(tokenizer=SCREAMING_SNAKE_CASE_					,       feature_extractor=SCREAMING_SNAKE_CASE_				)

          UpperCamelCase :int										=     [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

          UpperCamelCase :str										=     processor.batch_decode(SCREAMING_SNAKE_CASE_				)
          UpperCamelCase :Union[str, Any]										=     tokenizer.batch_decode(SCREAMING_SNAKE_CASE_				)

          self.assertListEqual(SCREAMING_SNAKE_CASE_					,       SCREAMING_SNAKE_CASE_				)




      def 					UpperCAmelCase		(       self				)       ->   List[Any]:
          UpperCamelCase :List[Any]										=     self.get_feature_extractor()
          UpperCamelCase :List[str]										=     self.get_tokenizer()

          UpperCamelCase :Optional[Any]										=     WavaVecaProcessor(tokenizer=SCREAMING_SNAKE_CASE_					,       feature_extractor=SCREAMING_SNAKE_CASE_				)

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













from __future__ import annotations







class     UpperCAmelCase_		:



      """simple docstring"""
      def __init__(       self					,       SCREAMING_SNAKE_CASE_				)       ->   None:
          UpperCamelCase :Tuple										=     value
          UpperCamelCase :Node | None										=     None
          UpperCamelCase :Node | None										=     None







class     UpperCAmelCase_		:



      """simple docstring"""
      UpperCamelCase_       :      int
      def __init__(       self				)       ->   None:
          UpperCamelCase :List[Any]										=     0
      def 					UpperCAmelCase		(       self					,       SCREAMING_SNAKE_CASE_					,       SCREAMING_SNAKE_CASE_				)       ->   None:
          if node is None:
              return

          if path_sum == self.target:
              self.paths += 1

          if node.left:
              self.depth_first_search(node.left					,       path_sum + node.left.value				)
          if node.right:
              self.depth_first_search(node.right					,       path_sum + node.right.value				)




      def 					UpperCAmelCase		(       self					,       SCREAMING_SNAKE_CASE_					,       SCREAMING_SNAKE_CASE_ = None				)       ->   int:
          if node is None:
              return 0
          if target is not None:
              UpperCamelCase :Tuple										=     target

          self.depth_first_search(SCREAMING_SNAKE_CASE_					,       node.value				)
          self.path_sum(node.left				)
          self.path_sum(node.right				)

          return self.paths


if __name__ == "__main__":
 import doctest

 doctest.testmod()





