

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 						__magic_name__    (       unittest.TestCase    ):
	UpperCAmelCase							    =						MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING


	def _UpperCamelCase	(						self		: Tuple			,						lowerCAmelCase__		: List[Any]			,						lowerCAmelCase__		: Union[str, Any]			,						lowerCAmelCase__		: List[Any]    )    ->      Optional[Any]:
			UpperCAmelCase					      =  hf_hub_download(
			    repo_id="nateraw/video-demo"			,						filename="archery.mp4"			,						repo_type="dataset"    )
			UpperCAmelCase					      =  VideoClassificationPipeline(model=lowerCamelCase__			,						image_processor=lowerCamelCase__			,						top_k=2    )
			UpperCAmelCase					      =  [
			    example_video_filepath,
			    "https://huggingface.co/datasets/nateraw/video-demo/resolve/main/archery.mp4",
			]
			return video_classifier, examples


	def _UpperCamelCase	(						self		: Optional[int]			,						lowerCAmelCase__		: List[Any]			,						lowerCAmelCase__		: Tuple    )    ->      List[Any]:







			for example in examples:
					UpperCAmelCase					      =  video_classifier(lowerCamelCase__    )

					self.assertEqual(
					    lowerCamelCase__			,						[
					        {"score": ANY(lowerCamelCase__    ), "label": ANY(lowerCamelCase__    )},
					        {"score": ANY(lowerCamelCase__    ), "label": ANY(lowerCamelCase__    )},
					    ]			,						)


	@require_torch
	def _UpperCamelCase	(						self		: Any    )    ->      List[Any]:
			UpperCAmelCase					      =  "hf-internal-testing/tiny-random-VideoMAEForVideoClassification"
			UpperCAmelCase					      =  VideoMAEFeatureExtractor(
			    size={"shortest_edge": 1_0}			,						crop_size={"height": 1_0, "width": 1_0}    )
			UpperCAmelCase					      =  pipeline(
			    "video-classification"			,						model=lowerCamelCase__			,						feature_extractor=lowerCamelCase__			,						frame_sampling_rate=4    )

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

			UpperCAmelCase					      =  video_classifier(
			    [
			        video_file_path,
			        video_file_path,
			    ]			,						top_k=2			,						)
			self.assertEqual(
			    nested_simplify(lowerCamelCase__			,						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		: List[str]    )    ->      Optional[int]:
			pass






import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowerCAmelCase__       = "src/diffusers"

# Matches is_xxx_available()
lowerCAmelCase__       = re.compile(r"is\_([a-z_]*)_available\(\)")
# Matches from xxx import bla
lowerCAmelCase__       = re.compile(r"\s+from\s+\S*\s+import\s+([^\(\s].*)\n")


lowerCAmelCase__       = "\n{0} = None\n"

lowerCAmelCase__       = "\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n"


lowerCAmelCase__       = "\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"
def      _lowerCAmelCase(	__A			):
  UpperCAmelCase					      =  _re_backend.findall(__A			)
  if len(__A			) == 0:
    return None

  return "_and_".join(__A			)
def      _lowerCAmelCase(	):
  with open(os.path.join(__A   ,       "__init__.py"			)   ,       "r"   ,       encoding="utf-8"   ,       newline="\n"			) as f:
    UpperCAmelCase					      =  f.readlines()

  # Get to the point we do the actual imports for type checking
  UpperCAmelCase					      =  0
  UpperCAmelCase					      =  {}
  # Go through the end of the file
  while line_index < len(__A			):
    # If the line contains is_backend_available, we grab all objects associated with the `else` block
    UpperCAmelCase					      =  find_backend(lines[line_index]			)
    if backend is not None:
      while not lines[line_index].startswith("else:"			):
        line_index += 1
      line_index += 1
      UpperCAmelCase					      =  []
      # Until we unindent, add backend objects to the list
      while line_index < len(__A			) and len(lines[line_index]			) > 1:
        UpperCAmelCase					      =  lines[line_index]
        UpperCAmelCase					      =  _re_single_line_import.search(__A			)
        if single_line_import_search is not None:
          objects.extend(single_line_import_search.groups()[0].split(", "			)			)
        elif line.startswith(" " * 8			):
          objects.append(line[8:-2]			)
        line_index += 1

      if len(__A			) > 0:
        UpperCAmelCase					      =  objects
    else:
      line_index += 1

  return backend_specific_objects
def      _lowerCAmelCase(	__A   ,       __A			):
  if name.isupper():
    return DUMMY_CONSTANT.format(__A			)
  elif name.islower():
    return DUMMY_FUNCTION.format(__A   ,       __A			)
  else:
    return DUMMY_CLASS.format(__A   ,       __A			)
def      _lowerCAmelCase(	__A=None			):
  if backend_specific_objects is None:
    UpperCAmelCase					      =  read_init()
  # For special correspondence backend to module name as used in the function requires_modulename
  UpperCAmelCase					      =  {}

  for backend, objects in backend_specific_objects.items():
    UpperCAmelCase					      =  "[" + ", ".join(F"\"{b}\"" for b in backend.split("_and_"			)			) + "]"
    UpperCAmelCase					      =  "# This file is autogenerated by the command `make fix-copies`, do not edit.\n"
    dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
    dummy_file += "\n".join([create_dummy_object(__A   ,       __A			) for o in objects]			)
    UpperCAmelCase					      =  dummy_file

  return dummy_files
def      _lowerCAmelCase(	__A=False			):
  UpperCAmelCase					      =  create_dummy_files()
  # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
  UpperCAmelCase					      =  {"torch": "pt"}

  # Locate actual dummy modules and read their content.
  UpperCAmelCase					      =  os.path.join(__A   ,       "utils"			)
  UpperCAmelCase					      =  {
      backend: os.path.join(__A   ,       F"dummy_{short_names.get(__A   ,       __A			)}_objects.py"			)
      for backend in dummy_files.keys()
  }

  UpperCAmelCase					      =  {}
  for backend, file_path in dummy_file_paths.items():
    if os.path.isfile(__A			):
      with open(__A   ,       "r"   ,       encoding="utf-8"   ,       newline="\n"			) as f:
        UpperCAmelCase					      =  f.read()
    else:
      UpperCAmelCase					      =  ""

  for backend in dummy_files.keys():
    if dummy_files[backend] != actual_dummies[backend]:
      if overwrite:
        print(
            F"Updating diffusers.utils.dummy_{short_names.get(__A   ,       __A			)}_objects.py as the main "
            "__init__ has new objects."			)
        with open(dummy_file_paths[backend]   ,       "w"   ,       encoding="utf-8"   ,       newline="\n"			) as f:
          f.write(dummy_files[backend]			)
      else:
        raise ValueError(
            "The main __init__ has objects that are not present in "
            F"diffusers.utils.dummy_{short_names.get(__A   ,       __A			)}_objects.py. Run `make fix-copies` "
            "to fix this."			)


if __name__ == "__main__":
      lowerCAmelCase__       = argparse.ArgumentParser()
      parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
      lowerCAmelCase__       = parser.parse_args()

      check_dummies(args.fix_and_overwrite)



