





'''simple docstring'''




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

lowercase__       : Optional[int]         =       logging.get_logger(__name__)


@add_end_docstrings(a__				)
class 					SCREAMING_SNAKE_CASE       (a__				):


     def __init__(		self		,      *_UpperCAmelCase		,      **_UpperCAmelCase):

          '''simple docstring'''






          super().__init__(*_UpperCAmelCase		,      **_UpperCAmelCase)
          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 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase=None):

          '''simple docstring'''






          __A		:					int						=			{}
          if top_k is not None:
               __A		:					Optional[int]						=			top_k
          return {}, {}, postprocess_params


     def __call__(		self		,      _UpperCAmelCase		,      **_UpperCAmelCase):

          '''simple docstring'''






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


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase):

          '''simple docstring'''






          __A		:					Optional[Any]						=			load_image(_UpperCAmelCase)
          __A		:					List[Any]						=			self.image_processor(images=_UpperCAmelCase		,      return_tensors=self.framework)
          return model_inputs


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase):

          '''simple docstring'''






          __A		:					Dict						=			self.model(**_UpperCAmelCase)
          return model_outputs


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase=5):

          '''simple docstring'''






          if top_k > self.model.config.num_labels:
               __A		:					Optional[int]						=			self.model.config.num_labels

          if self.framework == "pt":
               __A		:					List[str]						=			model_outputs.logits.softmax(-1)[0]
               __A					,__A		:					Optional[int]						=			probs.topk(_UpperCAmelCase)
          elif self.framework == "tf":
               __A		:					Tuple						=			stable_softmax(model_outputs.logits		,      axis=-1)[0]
               __A		:					Dict						=			tf.math.top_k(_UpperCAmelCase		,      k=_UpperCAmelCase)
               __A					,__A		:					Optional[int]						=			topk.values.numpy(), topk.indices.numpy()
          else:
               raise ValueError(F'Unsupported framework: {self.framework}')

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






'''simple docstring'''




import math
import sys






def 			_lowerCAmelCase     (    __snake_case    :					int     )	->	int:
     if number != int(__snake_case     ):
          raise ValueError('the value of input must be a natural number'     )
     if number < 0:
          raise ValueError('the value of input must not be a negative number'     )
     if number == 0:
          return 1
     __A		:					str						=			[-1] * (number + 1)
     __A		:					Dict						=			0
     for i in range(1					,				number + 1     ):
          __A		:					int						=			sys.maxsize
          __A		:					int						=			int(math.sqrt(__snake_case     )     )
          for j in range(1					,				root + 1     ):
               __A		:					str						=			1 + answers[i - (j**2)]
               __A		:					Dict						=			min(__snake_case					,				__snake_case     )
          __A		:					Union[str, Any]						=			answer
     return answers[number]


if __name__ == "__main__":
  import doctest

  doctest.testmod()