
"""simple docstring"""







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

lowerCamelCase__   					=		logging.get_logger(__name__)




@add_end_docstrings(_lowerCamelCase)
class  A__       (	_lowerCamelCase):

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

		def 							__lowerCamelCase							(      self       ,		_SCREAMING_SNAKE_CASE=None       ,		_SCREAMING_SNAKE_CASE=None       ,		_SCREAMING_SNAKE_CASE=None ):
			__lowerCAmelCase			:						Union[str, Any]									=      {}
			if frame_sampling_rate is not None:
				__lowerCAmelCase			:						Optional[int]									=      frame_sampling_rate
			if num_frames is not None:
				__lowerCAmelCase			:						int									=      num_frames

			__lowerCAmelCase			:						Any									=      {}
			if top_k is not None:
				__lowerCAmelCase			:						Optional[Any]									=      top_k
			return preprocess_params, {}, postprocess_params

		def __call__(      self       ,		_SCREAMING_SNAKE_CASE       ,		**_SCREAMING_SNAKE_CASE ):
			return super().__call__(_SCREAMING_SNAKE_CASE       ,		**_SCREAMING_SNAKE_CASE )

		def 							__lowerCamelCase							(      self       ,		_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE=None       ,		_SCREAMING_SNAKE_CASE=1 ):
			if num_frames is None:
				__lowerCAmelCase			:						Union[str, Any]									=      self.model.config.num_frames

			if video.startswith('http://' ) or video.startswith('https://' ):
				__lowerCAmelCase			:						Tuple									=      BytesIO(requests.get(_SCREAMING_SNAKE_CASE ).content )

			__lowerCAmelCase			:						str									=      VideoReader(_SCREAMING_SNAKE_CASE )
			videoreader.seek(0 )

			__lowerCAmelCase			:						Union[str, Any]									=      0
			__lowerCAmelCase			:						str									=      num_frames * frame_sampling_rate - 1
			__lowerCAmelCase			:						Union[str, Any]									=      np.linspace(_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE       ,		num=_SCREAMING_SNAKE_CASE       ,		dtype=np.intaa )

			__lowerCAmelCase			:						int									=      videoreader.get_batch(_SCREAMING_SNAKE_CASE ).asnumpy()
			__lowerCAmelCase			:						Dict									=      list(_SCREAMING_SNAKE_CASE )

			__lowerCAmelCase			:						List[Any]									=      self.image_processor(_SCREAMING_SNAKE_CASE       ,		return_tensors=self.framework )
			return model_inputs

		def 							__lowerCamelCase							(      self       ,		_SCREAMING_SNAKE_CASE ):
			__lowerCAmelCase			:						List[Any]									=      self.model(**_SCREAMING_SNAKE_CASE )
			return model_outputs







		def 							__lowerCamelCase							(      self       ,		_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE=5 ):
			if top_k > self.model.config.num_labels:
				__lowerCAmelCase			:						List[str]									=      self.model.config.num_labels

			if self.framework == "pt":
				__lowerCAmelCase			:						Union[str, Any]									=      model_outputs.logits.softmax(-1 )[0]
				__lowerCAmelCase			,   __lowerCAmelCase			:						Any									=      probs.topk(_SCREAMING_SNAKE_CASE )
			else:
				raise ValueError(f"Unsupported framework: {self.framework}" )

			__lowerCAmelCase			:						Any									=      scores.tolist()
			__lowerCAmelCase			:						List[str]									=      ids.tolist()
			return [{"score": score, "label": self.model.config.idalabel[_id]} for score, _id in zip(_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE )]



"""simple docstring"""







from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass


@dataclass
class       SCREAMING_SNAKE_CASE__				:
       """simple docstring"""


       a  :				int
       a  :				TreeNode | None   =None
       a  :				TreeNode | None   =None

lowerCAmelCase__      				=   namedtuple('''CoinsDistribResult''', '''moves excess''')
def 					a__			(				SCREAMING_SNAKE_CASE    :    TreeNode | None				):


  '''simple docstring'''







  if root is None:
    return 0

  # Validation
  def count_nodes(SCREAMING_SNAKE_CASE    :    TreeNode | None				) -> int:
    if node is None:
      return 0

    return count_nodes(node.left				) + count_nodes(node.right				) + 1

  def count_coins(SCREAMING_SNAKE_CASE    :    TreeNode | None				) -> int:
    if node is None:
      return 0

    return count_coins(node.left				) + count_coins(node.right				) + node.data

  if count_nodes(SCREAMING_SNAKE_CASE				) != count_coins(SCREAMING_SNAKE_CASE				):
    raise ValueError("The nodes number should be same as the number of coins"				)

  # Main calculation
  def get_distrib(SCREAMING_SNAKE_CASE    :    TreeNode | None				) -> CoinsDistribResult:

    if node is None:
      return CoinsDistribResult(0				,      1				)

    lowerCAmelCase						,  lowerCAmelCase     :     List[str]								=							get_distrib(node.left				)
    lowerCAmelCase						,  lowerCAmelCase     :     List[str]								=							get_distrib(node.right				)

    lowerCAmelCase     :     Union[str, Any]								=							1 - left_distrib_excess
    lowerCAmelCase     :     List[Any]								=							1 - right_distrib_excess

    lowerCAmelCase     :     int								=							(
        left_distrib_moves
        + right_distrib_moves
        + abs(SCREAMING_SNAKE_CASE				)
        + abs(SCREAMING_SNAKE_CASE				)
    )
    lowerCAmelCase     :     int								=							node.data - coins_to_left - coins_to_right

    return CoinsDistribResult(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)

  return get_distrib(SCREAMING_SNAKE_CASE				)[0]


if __name__ == "__main__":
     import doctest

     doctest.testmod()





