


def     UpperCamelCase    (      _a		)					->							list[list]:
     '''simple docstring'''





     lowercase_       :Optional[Any]     =       current_set.copy()
     for row_index, row in enumerate(_a		):
          lowercase_       :Union[str, Any]     =       row[0]
          for column_index, column in enumerate(_a		):
               if magnitude == 0:
                    lowercase_       :Union[str, Any]     =       column
                    continue
               lowercase_       :int     =       column / magnitude
    # Subtract to cancel term
     lowercase_       :Dict     =       current_set[0]
     lowercase_       :Any     =       [first_row]
     lowercase_       :Dict     =       current_set[1::]
     for row in current_set:
          lowercase_       :Any     =       []
          # If first term is 0, it is already in form we want, so we preserve it
          if row[0] == 0:
               final_set.append(_a		)
               continue
          for column_index in range(len(_a		)		):
               temp_row.append(first_row[column_index] - row[column_index]		)
          final_set.append(_a		)
     # Create next recursion iteration set
     if len(final_set[0]		) != 3:
          lowercase_       :str     =       final_set[0]
          lowercase_       :Optional[Any]     =       []
          lowercase_       :Optional[Any]     =       []
          for row in final_set[1::]:
               current_first_column.append(row[0]		)
               next_iteration.append(row[1::]		)
          lowercase_       :Optional[int]     =       simplify(_a		)
          for i in range(len(_a		)		):
               resultant[i].insert(0       ,		current_first_column[i]		)
          resultant.insert(0       ,		_a		)
          lowercase_       :int     =       resultant
     return final_set




def     UpperCamelCase    (      _a		)					->							list:
     '''simple docstring'''





     if len(_a		) == 0:
          raise IndexError('''solve_simultaneous() requires n lists of length n+1'''		)
     lowercase_       :Optional[int]     =       len(_a		) + 1
     if any(len(_a		) != _length for item in equations		):
          raise IndexError('''solve_simultaneous() requires n lists of length n+1'''		)
     for row in equations:
          if any(not isinstance(_a       ,		(int, float)		) for column in row		):
               raise ValueError('''solve_simultaneous() requires lists of integers'''		)
     if len(_a		) == 1:
          return [equations[0][-1] / equations[0][0]]
     lowercase_       :int     =       equations.copy()
     if any(0 in row for row in data_set		):
          lowercase_       :Optional[int]     =       data_set.copy()
          lowercase_       :Dict     =       []
          for row_index, row in enumerate(_a		):
               if 0 not in row:
                    lowercase_       :int     =       data_set.pop(_a		)
                    break
          if not full_row:
               raise ValueError('''solve_simultaneous() requires at least 1 full equation'''		)
          data_set.insert(0       ,		_a		)
     lowercase_       :Any     =       data_set.copy()
     lowercase_       :List[Any]     =       simplify(_a		)
     lowercase_       :Optional[int]     =       simplified[::-1]
     lowercase_       :list     =       []
     for row in simplified:
          lowercase_       :Union[str, Any]     =       row[-1]
          if not solutions:
               if row[-2] == 0:
                    solutions.append(0		)
                    continue
               solutions.append(current_solution / row[-2]		)
               continue
          lowercase_       :int     =       row.copy()[: len(_a		) - 1 :]
          while temp_row[0] == 0:
               temp_row.pop(0		)
          if len(_a		) == 0:
               solutions.append(0		)
               continue
          lowercase_       :str     =       temp_row[1::]
          lowercase_       :Tuple     =       temp_row[::-1]
          for column_index, column in enumerate(_a		):
               current_solution -= column * solutions[column_index]
          solutions.append(_a		)
     lowercase_       :int     =       []
     for item in solutions:
          final.append(float(round(_a       ,		5		)		)		)
     return final[::-1]


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   SCREAMING_SNAKE_CASE       :		str         =				[
       [2, 1, 1, 1, 1, 4],
       [1, 2, 1, 1, 1, 5],
       [1, 1, 2, 1, 1, 6],
       [1, 1, 1, 2, 1, 7],
       [1, 1, 1, 1, 2, 8],
   ]
   print(solve_simultaneous(eq))
   print(solve_simultaneous([[4, 2]]))





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

SCREAMING_SNAKE_CASE       :		List[str]         =				logging.get_logger(__name__)






@add_end_docstrings(lowercase__     )
class      UpperCamelCase					(		lowercase__     ):


   '''simple docstring'''







   def __init__(     self   ,							*UpperCamelCase_   ,							**UpperCamelCase_		):
        super().__init__(*UpperCamelCase_   ,							**UpperCamelCase_		)
        requires_backends(self   ,							'''decord'''		)
        self.check_model_type(UpperCamelCase_		)
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_=None   ,							UpperCamelCase_=None   ,							UpperCamelCase_=None		):
        lowercase_       :int     =       {}
        if frame_sampling_rate is not None:
             lowercase_       :int     =       frame_sampling_rate
        if num_frames is not None:
             lowercase_       :int     =       num_frames

        lowercase_       :str     =       {}
        if top_k is not None:
             lowercase_       :Optional[int]     =       top_k
        return preprocess_params, {}, postprocess_params
   def __call__(     self   ,							UpperCamelCase_   ,							**UpperCamelCase_		):
        return super().__call__(UpperCamelCase_   ,							**UpperCamelCase_		)
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_   ,							UpperCamelCase_=None   ,							UpperCamelCase_=1		):
        if num_frames is None:
             lowercase_       :str     =       self.model.config.num_frames

        if video.startswith('''http://'''		) or video.startswith('''https://'''		):
             lowercase_       :str     =       BytesIO(requests.get(UpperCamelCase_		).content		)

        lowercase_       :Optional[int]     =       VideoReader(UpperCamelCase_		)
        videoreader.seek(0		)

        lowercase_       :Tuple     =       0
        lowercase_       :Optional[Any]     =       num_frames * frame_sampling_rate - 1
        lowercase_       :Any     =       np.linspace(UpperCamelCase_   ,							UpperCamelCase_   ,							num=UpperCamelCase_   ,							dtype=np.intaa		)

        lowercase_       :Dict     =       videoreader.get_batch(UpperCamelCase_		).asnumpy()
        lowercase_       :List[Any]     =       list(UpperCamelCase_		)

        lowercase_       :Any     =       self.image_processor(UpperCamelCase_   ,							return_tensors=self.framework		)
        return model_inputs
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_		):
        lowercase_       :List[str]     =       self.model(**UpperCamelCase_		)
        return model_outputs




   def 		UpperCamelCase  (     self   ,							UpperCamelCase_   ,							UpperCamelCase_=5		):
        if top_k > self.model.config.num_labels:
             lowercase_       :List[str]     =       self.model.config.num_labels

        if self.framework == "pt":
             lowercase_       :Optional[int]     =       model_outputs.logits.softmax(-1		)[0]
             lowercase_    ,      lowercase_       :Dict     =       probs.topk(UpperCamelCase_		)
        else:
             raise ValueError(f"Unsupported framework: {self.framework}"		)

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

