
from io import BytesIO
from typing import List, Union

import requests

from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_decord_available():
							import numpy as np
							from decord import VideoReader


if is_torch_available():
							from ..models.auto.modeling_auto import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING

lowercase__	:Tuple										=					logging.get_logger(__name__)







@add_end_docstrings(SCREAMING_SNAKE_CASE__	)
class        lowercase	(      SCREAMING_SNAKE_CASE__	):




							def __init__(       self     ,*A__     ,**A__):
												super().__init__(*UpperCAmelCase__     ,**UpperCAmelCase__)
												requires_backends(self     ,'''decord''')
												self.check_model_type(UpperCAmelCase__)




							def 				A__   (       self     ,A__=None     ,A__=None     ,A__=None):
												lowercase					=		{}
												if frame_sampling_rate is not None:
																	lowercase					=		frame_sampling_rate
												if num_frames is not None:
																	lowercase					=		num_frames

												lowercase					=		{}
												if top_k is not None:
																	lowercase					=		top_k
												return preprocess_params, {}, postprocess_params




							def __call__(       self     ,A__     ,**A__):
												return super().__call__(UpperCAmelCase__     ,**UpperCAmelCase__)




							def 				A__   (       self     ,A__     ,A__=None     ,A__=1):
												if num_frames is None:
																	lowercase					=		self.model.config.num_frames

												if video.startswith('''http://''') or video.startswith('''https://'''):
																	lowercase					=		BytesIO(requests.get(UpperCAmelCase__).content)

												lowercase					=		VideoReader(UpperCAmelCase__)
												videoreader.seek(0)

												lowercase					=		0
												lowercase					=		num_frames * frame_sampling_rate - 1
												lowercase					=		np.linspace(UpperCAmelCase__     ,UpperCAmelCase__     ,num=UpperCAmelCase__     ,dtype=np.intaa)

												lowercase					=		videoreader.get_batch(UpperCAmelCase__).asnumpy()
												lowercase					=		list(UpperCAmelCase__)

												lowercase					=		self.image_processor(UpperCAmelCase__     ,return_tensors=self.framework)
												return model_inputs




							def 				A__   (       self     ,A__):
												lowercase					=		self.model(**UpperCAmelCase__)
												return model_outputs





							def 				A__   (       self     ,A__     ,A__=5):
												if top_k > self.model.config.num_labels:
																	lowercase					=		self.model.config.num_labels

												if self.framework == "pt":
																	lowercase					=		model_outputs.logits.softmax(-1)[0]
																	lowercase			,		lowercase					=		probs.topk(UpperCAmelCase__)
												else:
																	raise ValueError(f'Unsupported framework: {self.framework}')

												lowercase					=		scores.tolist()
												lowercase					=		ids.tolist()
												return [{"score": score, "label": self.model.config.idalabel[_id]} for score, _id in zip(UpperCAmelCase__     ,UpperCAmelCase__)]






from __future__ import annotations



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					if len(lowerCAmelCase__	) < 2:
										raise ValueError('''Monogons and Digons are not polygons in the Euclidean space'''	)
					if any(i <= 0 for i in nums	):
										raise ValueError('''All values must be greater than 0'''	)
					lowercase					=		nums.copy()
					copy_nums.sort()
					return copy_nums[-1] < sum(copy_nums[:-1]	)


if __name__ == "__main__":
							import doctest

							doctest.testmod()




