





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        __SCREAMING_SNAKE_CASE					(     unittest.TestCase       ):
							snake_case     :      Dict						     =       MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
														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 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  ):
														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 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			"""hf-internal-testing/tiny-random-VideoMAEForVideoClassification"""
														UpperCamelCase__				     =			VideoMAEFeatureExtractor(
														    size={"""shortest_edge""": 10}  , crop_size={"""height""": 10, """width""": 10}  )
														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""": 0.5199, """label""": """LABEL_0"""}, {"""score""": 0.4801, """label""": """LABEL_1"""}]  , )

														UpperCamelCase__				     =			video_classifier(
														    [
														        video_file_path,
														        video_file_path,
														    ]  , top_k=2  , )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  , decimals=4  )  , [
														        [{"""score""": 0.5199, """label""": """LABEL_0"""}, {"""score""": 0.4801, """label""": """LABEL_1"""}],
														        [{"""score""": 0.5199, """label""": """LABEL_0"""}, {"""score""": 0.4801, """label""": """LABEL_1"""}],
														    ]  , )







							@require_tf
							def 				_lowerCamelCase		(						self  ):
														pass











from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403





def     _UpperCamelCase     (a__   :str   ,			a__   :complex   ,			a__   :str = "x"   ,			a__   :float = 10**-10   ,			a__   :int = 1   ,			):






							"""simple docstring"""





							UpperCamelCase__				     =			symbols(a__       )
							UpperCamelCase__				     =			lambdify(a__   ,			a__       )
							UpperCamelCase__				     =			lambdify(a__   ,			diff(a__   ,			a__       )       )

							UpperCamelCase__				     =			starting_point

							while True:
														if diff_function(a__       ) != 0:
																					UpperCamelCase__				     =			prev_guess - multiplicity * func(a__       ) / diff_function(
																					    a__       )
														else:
																					raise ZeroDivisionError("""Could not find root"""       ) from None

														# Precision is checked by comparing the difference of consecutive guesses
														if abs(next_guess - prev_guess       ) < precision:
																					return next_guess

														UpperCamelCase__				     =			next_guess


# Let's Execute
if __name__ == "__main__":
					# Find root of trigonometric function
					# Find value of pi
					print(f"""The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}""")

					# Find root of polynomial
					# Find fourth Root of 5
					print(f"""The root of x**4 - 5 = 0 is {newton_raphson('x**4 -5', 0.4 +5J)}""")

					# Find value of e
					print(
					    "The root of log(y) - 1 = 0 is ",
					    f"""{newton_raphson('log(y) - 1', 2, variable='y')}""",
					)

					# Exponential Roots
					print(
					    "The root of exp(x) - 1 = 0 is",
					    f"""{newton_raphson('exp(x) - 1', 10, precision=0.0_05)}""",
					)

					# Find root of cos(x)
					print(f"""The root of cos(x) = 0 is {newton_raphson('cos(x)', 0)}""")




