


import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


UpperCAmelCase    =					"""__DUMMY_TRANSFORMERS_USER__"""
UpperCAmelCase    =					"""Dummy User"""
UpperCAmelCase    =					"""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"""

UpperCAmelCase    =					"""https://hub-ci.huggingface.co"""
UpperCAmelCase    =					CI_HUB_ENDPOINT + """/datasets/{repo_id}/resolve/{revision}/{path}"""
UpperCAmelCase    =					CI_HUB_ENDPOINT + """/{repo_id}/resolve/{revision}/{filename}"""
UpperCAmelCase    =					Path("""~/.huggingface/hub_ci_token""").expanduser()






@pytest.fixture
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      )->						Dict:




      """simple docstring"""

      monkeypatch.setattr(
          '''huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE'''      ,      SCREAMING_SNAKE_CASE      )






@pytest.fixture
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      )->						str:




      """simple docstring"""

      monkeypatch.setattr('''datasets.config.HF_ENDPOINT'''      ,      SCREAMING_SNAKE_CASE      )
      monkeypatch.setattr('''datasets.config.HUB_DATASETS_URL'''      ,      SCREAMING_SNAKE_CASE      )






@pytest.fixture
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      )->						str:




      """simple docstring"""

      monkeypatch.setattr('''huggingface_hub.hf_api.HfFolder.path_token'''      ,      SCREAMING_SNAKE_CASE      )






@pytest.fixture
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						Tuple:




      """simple docstring"""

      HfFolder.save_token(SCREAMING_SNAKE_CASE      )
      yield
      HfFolder.delete_token()






@pytest.fixture(scope='''session'''      )
def  __lowerCAmelCase					()->						Tuple:




      """simple docstring"""

      return HfApi(endpoint=SCREAMING_SNAKE_CASE      )






@pytest.fixture(scope='''session'''      )
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      )->						str:




      """simple docstring"""

      snake_case_ =   HfFolder.get_token()
      HfFolder.save_token(SCREAMING_SNAKE_CASE      )
      yield CI_HUB_USER_TOKEN
      if previous_token is not None:
            HfFolder.save_token(SCREAMING_SNAKE_CASE      )






@pytest.fixture
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      )->						Optional[int]:




      """simple docstring"""

      def _cleanup_repo(SCREAMING_SNAKE_CASE      ):
            hf_api.delete_repo(SCREAMING_SNAKE_CASE      ,      token=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      )

      return _cleanup_repo






@pytest.fixture
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      )->						Union[str, Any]:




      """simple docstring"""

      @contextmanager
      def _temporary_repo(SCREAMING_SNAKE_CASE      ):
            try:
                  yield repo_id
            finally:
                  cleanup_repo(SCREAMING_SNAKE_CASE      )

      return _temporary_repo






@pytest.fixture(scope='''session'''      )
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						Union[str, Any]:




      """simple docstring"""

      snake_case_ =   f'''repo_txt_data-{int(time.time() * 10E3      )}'''
      snake_case_ =   f'''{CI_HUB_USER}/{repo_name}'''
      hf_api.create_repo(SCREAMING_SNAKE_CASE      ,      token=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      ,      private=SCREAMING_SNAKE_CASE      )
      hf_api.upload_file(
          token=SCREAMING_SNAKE_CASE      ,      path_or_fileobj=str(SCREAMING_SNAKE_CASE      )      ,      path_in_repo='''data/text_data.txt'''      ,      repo_id=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      ,      )
      yield repo_id
      try:
            hf_api.delete_repo(SCREAMING_SNAKE_CASE      ,      token=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      )
      except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
            pass






@pytest.fixture()
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						List[Any]:




      """simple docstring"""

      return hf_private_dataset_repo_txt_data_






@pytest.fixture(scope='''session'''      )
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						Dict:




      """simple docstring"""

      snake_case_ =   f'''repo_zipped_txt_data-{int(time.time() * 10E3      )}'''
      snake_case_ =   f'''{CI_HUB_USER}/{repo_name}'''
      hf_api.create_repo(SCREAMING_SNAKE_CASE      ,      token=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      ,      private=SCREAMING_SNAKE_CASE      )
      hf_api.upload_file(
          token=SCREAMING_SNAKE_CASE      ,      path_or_fileobj=str(SCREAMING_SNAKE_CASE      )      ,      path_in_repo='''data.zip'''      ,      repo_id=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      ,      )
      yield repo_id
      try:
            hf_api.delete_repo(SCREAMING_SNAKE_CASE      ,      token=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      )
      except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
            pass






@pytest.fixture()
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						int:




      """simple docstring"""

      return hf_private_dataset_repo_zipped_txt_data_






@pytest.fixture(scope='''session'''      )
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						Union[str, Any]:




      """simple docstring"""

      snake_case_ =   f'''repo_zipped_img_data-{int(time.time() * 10E3      )}'''
      snake_case_ =   f'''{CI_HUB_USER}/{repo_name}'''
      hf_api.create_repo(SCREAMING_SNAKE_CASE      ,      token=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      ,      private=SCREAMING_SNAKE_CASE      )
      hf_api.upload_file(
          token=SCREAMING_SNAKE_CASE      ,      path_or_fileobj=str(SCREAMING_SNAKE_CASE      )      ,      path_in_repo='''data.zip'''      ,      repo_id=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      ,      )
      yield repo_id
      try:
            hf_api.delete_repo(SCREAMING_SNAKE_CASE      ,      token=SCREAMING_SNAKE_CASE      ,      repo_type='''dataset'''      )
      except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
            pass






@pytest.fixture()
def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						Tuple:




      """simple docstring"""

      return hf_private_dataset_repo_zipped_img_data_



import unittest

from huggingface_hub import hf_hub_download

from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_decord,
    require_tf,
    require_torch,
    require_torch_or_tf,
    require_vision,
)

from .test_pipelines_common import ANY







@is_pipeline_test
@require_torch_or_tf
@require_vision
@require_decord
class lowerCAmelCase_		(				unittest.TestCase ):

 '''simple docstring'''

 __snake_case				=						MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING



 def 		UpperCamelCase__  (			self	,   _UpperCAmelCase	,   _UpperCAmelCase	,   _UpperCAmelCase      ):
       snake_case_ =   hf_hub_download(
           repo_id='''nateraw/video-demo'''	,   filename='''archery.mp4'''	,   repo_type='''dataset'''      )
       snake_case_ =   VideoClassificationPipeline(model=_UpperCAmelCase	,   image_processor=_UpperCAmelCase	,   top_k=2      )
       snake_case_ =   [
           example_video_filepath,
           '''https://huggingface.co/datasets/nateraw/video-demo/resolve/main/archery.mp4''',
       ]
       return video_classifier, examples



 def 		UpperCamelCase__  (			self	,   _UpperCAmelCase	,   _UpperCAmelCase      ):
       for example in examples:
             snake_case_ =   video_classifier(_UpperCAmelCase      )

             self.assertEqual(
                 _UpperCAmelCase	,   [
                     {'''score''': ANY(_UpperCAmelCase      ), '''label''': ANY(_UpperCAmelCase      )},
                     {'''score''': ANY(_UpperCAmelCase      ), '''label''': ANY(_UpperCAmelCase      )},
                 ]	,   )



 @require_torch
 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   '''hf-internal-testing/tiny-random-VideoMAEForVideoClassification'''
       snake_case_ =   VideoMAEFeatureExtractor(
           size={'''shortest_edge''': 10}	,   crop_size={'''height''': 10, '''width''': 10}      )
       snake_case_ =   pipeline(
           '''video-classification'''	,   model=_UpperCAmelCase	,   feature_extractor=_UpperCAmelCase	,   frame_sampling_rate=4      )

       snake_case_ =   hf_hub_download(repo_id='''nateraw/video-demo'''	,   filename='''archery.mp4'''	,   repo_type='''dataset'''      )
       snake_case_ =   video_classifier(_UpperCAmelCase	,   top_k=2      )
       self.assertEqual(
           nested_simplify(_UpperCAmelCase	,   decimals=4      )	,   [{'''score''': 0.5_199, '''label''': '''LABEL_0'''}, {'''score''': 0.4_801, '''label''': '''LABEL_1'''}]	,   )

       snake_case_ =   video_classifier(
           [
               video_file_path,
               video_file_path,
           ]	,   top_k=2	,   )
       self.assertEqual(
           nested_simplify(_UpperCAmelCase	,   decimals=4      )	,   [
               [{'''score''': 0.5_199, '''label''': '''LABEL_0'''}, {'''score''': 0.4_801, '''label''': '''LABEL_1'''}],
               [{'''score''': 0.5_199, '''label''': '''LABEL_0'''}, {'''score''': 0.4_801, '''label''': '''LABEL_1'''}],
           ]	,   )





 @require_tf
 def 		UpperCamelCase__  (			self      ):
       pass