





from typing import List, Union

from ..utils import (
    add_end_docstrings,
    is_tf_available,
    is_torch_available,
    is_vision_available,
    logging,
    requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
  from PIL import Image

  from ..image_utils import load_image

if is_tf_available():
  import tensorflow as tf

  from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
  from ..tf_utils import stable_softmax

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

_snake_case           =							logging.get_logger(__name__)





@add_end_docstrings(SCREAMING_SNAKE_CASE__ )
class  lowerCAmelCase							(       SCREAMING_SNAKE_CASE__ ):







  def __init__(      self  :Optional[int]   ,							*_lowercase  :Dict   ,							**_lowercase  :Dict ):






     '''simple docstring'''





     super().__init__(*_SCREAMING_SNAKE_CASE   ,							**_SCREAMING_SNAKE_CASE )
     requires_backends(self   ,							"vision" )
     self.check_model_type(
         TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
         if self.framework == "tf"
         else MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING )







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






     '''simple docstring'''





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







  def __call__(      self  :int   ,							_lowercase  :Tuple   ,							**_lowercase  :List[str] ):






     '''simple docstring'''





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







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






     '''simple docstring'''





     lowercase__			       =  load_image(_SCREAMING_SNAKE_CASE )
     lowercase__			       =  self.image_processor(images=_SCREAMING_SNAKE_CASE   ,							return_tensors=self.framework )
     return model_inputs







  def   UpperCAmelCase					(      self  :Union[str, Any]   ,							_lowercase  :Any ):






     '''simple docstring'''





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







  def   UpperCAmelCase					(      self  :Any   ,							_lowercase  :List[str]   ,							_lowercase  :int=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__			       =  probs.topk(_SCREAMING_SNAKE_CASE )
     elif self.framework == "tf":
        lowercase__			       =  stable_softmax(model_outputs.logits   ,							axis=-1 )[0]
        lowercase__			       =  tf.math.top_k(_SCREAMING_SNAKE_CASE   ,							k=_SCREAMING_SNAKE_CASE )
        lowercase__			       =  topk.values.numpy(), topk.indices.numpy()
     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 )]













def _A       (   __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__	):
   if height >= 1:
      move_tower(height - 1  , __magic_name__  , __magic_name__  , __magic_name__	)
      move_disk(__magic_name__  , __magic_name__	)
      move_tower(height - 1  , __magic_name__  , __magic_name__  , __magic_name__	)


def _A       (   __magic_name__  , __magic_name__	):
   print("moving disk from"  , __magic_name__  , "to"  , __magic_name__	)


def _A       (   ):
   lowercase__			       =  int(input("Height of hanoi: "	).strip()	)
   move_tower(__magic_name__  , "A"  , "B"  , "C"	)


if __name__ == "__main__":
  main()






