
"""simple docstring"""

import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / "utils"))

from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


UpperCamelCase     :    List[str]       =			get_tests_dir("fixtures")

class __lowerCAmelCase		(				unittest.TestCase      ):





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	mock.Mock()
      __UpperCamelCase      =	500
      __UpperCamelCase      =	{}
      __UpperCamelCase      =	HTTPError
      __UpperCamelCase      =	{}

      # Download this model to make sure it's in the cache.
      __UpperCamelCase      =	WavaVecaFeatureExtractor.from_pretrained('hf-internal-testing/tiny-random-wav2vec2'				)
      # Under the mock environment we get a 500 error when trying to reach the model.
      with mock.patch('requests.Session.request'     ,					return_value=__UpperCAmelCase				) as mock_head:
       __UpperCamelCase      =	WavaVecaFeatureExtractor.from_pretrained('hf-internal-testing/tiny-random-wav2vec2'				)
       # This check we did call the fake head request
       mock_head.assert_called()







     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	WavaVecaFeatureExtractor.from_pretrained(
          'https://huggingface.co/hf-internal-testing/tiny-random-wav2vec2/resolve/main/preprocessor_config.json'				)


@is_staging_test
class __lowerCAmelCase		(				unittest.TestCase      ):





     @classmethod
     def 						UpperCAmelCase (     cls				):

      '''simple docstring'''




      __UpperCamelCase      =	TOKEN
      HfFolder.save_token(__UpperCAmelCase				)





     @classmethod
     def 						UpperCAmelCase (     cls				):

      '''simple docstring'''




      try:
       delete_repo(token=cls._token     ,					repo_id='test-feature-extractor'				)
      except HTTPError:
       pass

      try:
       delete_repo(token=cls._token     ,					repo_id='valid_org/test-feature-extractor-org'				)
      except HTTPError:
       pass

      try:
       delete_repo(token=cls._token     ,					repo_id='test-dynamic-feature-extractor'				)
      except HTTPError:
       pass





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	WavaVecaFeatureExtractor.from_pretrained(__UpperCAmelCase				)
      feature_extractor.push_to_hub('test-feature-extractor'     ,					use_auth_token=self._token				)

      __UpperCamelCase      =	WavaVecaFeatureExtractor.from_pretrained(F'{USER}/test-feature-extractor'				)
      for k, v in feature_extractor.__dict__.items():
       self.assertEqual(__UpperCAmelCase     ,					getattr(__UpperCAmelCase     ,					__UpperCAmelCase				)				)

      # Reset repo
      delete_repo(token=self._token     ,					repo_id='test-feature-extractor'				)

      # Push to hub via save_pretrained
      with tempfile.TemporaryDirectory() as tmp_dir:
       feature_extractor.save_pretrained(
           __UpperCAmelCase     ,					repo_id='test-feature-extractor'     ,					push_to_hub=__UpperCAmelCase     ,					use_auth_token=self._token				)

      __UpperCamelCase      =	WavaVecaFeatureExtractor.from_pretrained(F'{USER}/test-feature-extractor'				)
      for k, v in feature_extractor.__dict__.items():
       self.assertEqual(__UpperCAmelCase     ,					getattr(__UpperCAmelCase     ,					__UpperCAmelCase				)				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	WavaVecaFeatureExtractor.from_pretrained(__UpperCAmelCase				)
      feature_extractor.push_to_hub('valid_org/test-feature-extractor'     ,					use_auth_token=self._token				)

      __UpperCamelCase      =	WavaVecaFeatureExtractor.from_pretrained('valid_org/test-feature-extractor'				)
      for k, v in feature_extractor.__dict__.items():
       self.assertEqual(__UpperCAmelCase     ,					getattr(__UpperCAmelCase     ,					__UpperCAmelCase				)				)

      # Reset repo
      delete_repo(token=self._token     ,					repo_id='valid_org/test-feature-extractor'				)

      # Push to hub via save_pretrained
      with tempfile.TemporaryDirectory() as tmp_dir:
       feature_extractor.save_pretrained(
           __UpperCAmelCase     ,					repo_id='valid_org/test-feature-extractor-org'     ,					push_to_hub=__UpperCAmelCase     ,					use_auth_token=self._token				)

      __UpperCamelCase      =	WavaVecaFeatureExtractor.from_pretrained('valid_org/test-feature-extractor-org'				)
      for k, v in feature_extractor.__dict__.items():
       self.assertEqual(__UpperCAmelCase     ,					getattr(__UpperCAmelCase     ,					__UpperCAmelCase				)				)







     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      CustomFeatureExtractor.register_for_auto_class()
      __UpperCamelCase      =	CustomFeatureExtractor.from_pretrained(__UpperCAmelCase				)

      feature_extractor.push_to_hub('test-dynamic-feature-extractor'     ,					use_auth_token=self._token				)

      # This has added the proper auto_map field to the config
      self.assertDictEqual(
          feature_extractor.auto_map     ,					{'AutoFeatureExtractor': 'custom_feature_extraction.CustomFeatureExtractor'}     ,					)

      __UpperCamelCase      =	AutoFeatureExtractor.from_pretrained(
          F'{USER}/test-dynamic-feature-extractor'     ,					trust_remote_code=__UpperCAmelCase				)
      # Can't make an isinstance check because the new_feature_extractor is from the CustomFeatureExtractor class of a dynamic module
      self.assertEqual(new_feature_extractor.__class__.__name__     ,					'CustomFeatureExtractor'				)





"""simple docstring"""

from __future__ import annotations

from typing import Any






def 							A						(    snake_case				:list		)				->     int:
 if not postfix_notation:
  return 0

 __UpperCamelCase      =	{'+', '-', '*', '/'}
 __UpperCamelCase      =	[]

 for token in postfix_notation:
  if token in operations:
   __UpperCamelCase  ,     __UpperCamelCase      =	stack.pop(), stack.pop()
   if token == "+":
    stack.append(a + b		)
   elif token == "-":
    stack.append(a - b		)
   elif token == "*":
    stack.append(a * b		)
   else:
    if a * b < 0 and a % b != 0:
     stack.append(a // b + 1		)
    else:
     stack.append(a // b		)
  else:
   stack.append(int(snake_case		)		)

 return stack.pop()


if __name__ == "__main__":
      import doctest

      doctest.testmod()



