





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

_snake_case           =					logging.get_logger(__name__)





@add_end_docstrings(__lowercase   )
class    lowerCAmelCase				(  __lowercase   ):







  def __init__(     self    :Optional[Any]       ,				*_lowercase    :str       ,				**_lowercase    :str   ):






     '''simple docstring'''





     super().__init__(*SCREAMING_SNAKE_CASE_       ,				**SCREAMING_SNAKE_CASE_   )
     requires_backends(self       ,				"decord"   )
     self.check_model_type(SCREAMING_SNAKE_CASE_   )







  def     UpperCAmelCase	(     self    :List[str]       ,				_lowercase    :str=None       ,				_lowercase    :int=None       ,				_lowercase    :Union[str, Any]=None   ):






     '''simple docstring'''





     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    :List[Any]       ,				_lowercase    :Optional[Any]       ,				**_lowercase    :Optional[int]   ):






     '''simple docstring'''





     return super().__call__(SCREAMING_SNAKE_CASE_       ,				**SCREAMING_SNAKE_CASE_   )







  def     UpperCAmelCase	(     self    :Dict       ,				_lowercase    :Optional[Any]       ,				_lowercase    :List[Any]=None       ,				_lowercase    :Union[str, Any]=1   ):






     '''simple docstring'''





     if num_frames is None:
        lowercase__					  =    self.model.config.num_frames

     if video.startswith("http://"   ) or video.startswith("https://"   ):
        lowercase__					  =    BytesIO(requests.get(SCREAMING_SNAKE_CASE_   ).content   )

     lowercase__					  =    VideoReader(SCREAMING_SNAKE_CASE_   )
     videoreader.seek(0   )

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

     lowercase__					  =    videoreader.get_batch(SCREAMING_SNAKE_CASE_   ).asnumpy()
     lowercase__					  =    list(SCREAMING_SNAKE_CASE_   )

     lowercase__					  =    self.image_processor(SCREAMING_SNAKE_CASE_       ,				return_tensors=self.framework   )
     return model_inputs







  def     UpperCAmelCase	(     self    :str       ,				_lowercase    :str   ):






     '''simple docstring'''





     lowercase__					  =    self.model(**SCREAMING_SNAKE_CASE_   )
     return model_outputs







  def     UpperCAmelCase	(     self    :List[str]       ,				_lowercase    :Tuple       ,				_lowercase    :Union[str, Any]=5   ):






     '''simple docstring'''





     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(SCREAMING_SNAKE_CASE_   )
     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(SCREAMING_SNAKE_CASE_       ,				SCREAMING_SNAKE_CASE_   )]








"""simple docstring"""




from __future__ import annotations



def 							_lowerCamelCase			(			__a,				__a = None     ):
		SCREAMING_SNAKE_CASE_    			=			word_bank or []
		# create a table
		SCREAMING_SNAKE_CASE_    			=			len(__a     ) + 1

		SCREAMING_SNAKE_CASE_    			=			[]
		for _ in range(__a     ):
				table.append([]     )
		# seed value
		SCREAMING_SNAKE_CASE_    			=			[[]]  # because empty string has empty combination

		# iterate through the indices
		for i in range(__a     ):
				# condition
				if table[i] != []:
						for word in word_bank:
								# slice condition
								if target[i : i + len(__a     )] == word:
										SCREAMING_SNAKE_CASE_    			=			[
										    [word, *way] for way in table[i]
										]
										# adds the word to every combination the current position holds
										# now,push that combination to the table[i+len(word)]
										table[i + len(__a     )] += new_combinations

    # combinations are in reverse order so reverse for better output
		for combination in table[len(__a     )]:
				combination.reverse()

		return table[len(__a     )]


if __name__ == "__main__":
						print(all_construct('jwajalapa', ['jwa', 'j', 'w', 'a', 'la', 'lapa']))
						print(all_construct('rajamati', ['s', 'raj', 'amat', 'raja', 'ma', 'i', 't']))
						print(
						    all_construct(
						        'hexagonosaurus',
						        ['h', 'ex', 'hex', 'ag', 'ago', 'ru', 'auru', 'rus', 'go', 'no', 'o', 's'],
						    )
						)